ss1<-lm(B1_10~postawa+branza+wielkosc+warszafka+inne_firmy+indyw_kons+global,baza1)
summary(ss1)
##
## Call:
## lm(formula = B1_10 ~ postawa + branza + wielkosc + warszafka +
## inne_firmy + indyw_kons + global, data = baza1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.999 -0.963 0.151 1.047 2.202
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.936033 0.341014 8.61 4.1e-16 ***
## postawareal 0.238148 0.186675 1.28 0.203
## postawakonserw -0.050741 0.177499 -0.29 0.775
## branzahandel 0.286041 0.228966 1.25 0.213
## branzausługi -0.168086 0.194726 -0.86 0.389
## branzaadm,edu,samo -0.272978 0.246679 -1.11 0.269
## wielkosc10-49 osób 0.073662 0.186988 0.39 0.694
## wielkosc50 i więcej osób -0.080003 0.194032 -0.41 0.680
## warszafkaTRUE 0.177570 0.159955 1.11 0.268
## inne_firmyTRUE -0.000728 0.235361 0.00 0.998
## indyw_konsTRUE 0.266827 0.181360 1.47 0.142
## globalTRUE 0.362472 0.167437 2.16 0.031 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.31 on 303 degrees of freedom
## (6 observations deleted due to missingness)
## Multiple R-squared: 0.0596, Adjusted R-squared: 0.0255
## F-statistic: 1.75 on 11 and 303 DF, p-value: 0.0627
ss1<-lm(B1_11~postawa+branza+wielkosc+warszafka+inne_firmy+indyw_kons+global,baza1)
summary(ss1)
##
## Call:
## lm(formula = B1_11 ~ postawa + branza + wielkosc + warszafka +
## inne_firmy + indyw_kons + global, data = baza1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.067 -0.835 0.173 1.021 2.108
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.14389 0.32695 9.62 <2e-16 ***
## postawareal 0.00614 0.17971 0.03 0.973
## postawakonserw -0.38904 0.17131 -2.27 0.024 *
## branzahandel 0.18790 0.22048 0.85 0.395
## branzausługi 0.18261 0.18834 0.97 0.333
## branzaadm,edu,samo 0.06877 0.23793 0.29 0.773
## wielkosc10-49 osób 0.20233 0.18031 1.12 0.263
## wielkosc50 i więcej osób 0.28469 0.18605 1.53 0.127
## warszafkaTRUE 0.34971 0.15414 2.27 0.024 *
## inne_firmyTRUE -0.10643 0.22669 -0.47 0.639
## indyw_konsTRUE 0.06853 0.17414 0.39 0.694
## globalTRUE 0.25743 0.16072 1.60 0.110
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.26 on 299 degrees of freedom
## (10 observations deleted due to missingness)
## Multiple R-squared: 0.0666, Adjusted R-squared: 0.0323
## F-statistic: 1.94 on 11 and 299 DF, p-value: 0.0342
ss1<-lm(B1_10~informacja+branza+wielkosc+warszafka+inne_firmy+indyw_kons+global,baza1)
summary(ss1)
##
## Call:
## lm(formula = B1_10 ~ informacja + branza + wielkosc + warszafka +
## inne_firmy + indyw_kons + global, data = baza1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.819 -0.995 0.113 1.053 2.143
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.07585 0.32925 9.34 <2e-16 ***
## informacja 0.20262 0.08534 2.37 0.018 *
## branzahandel 0.26550 0.22777 1.17 0.245
## branzausługi -0.21030 0.19513 -1.08 0.282
## branzaadm,edu,samo -0.34540 0.24587 -1.40 0.161
## wielkosc10-49 osób 0.01093 0.18600 0.06 0.953
## wielkosc50 i więcej osób -0.19542 0.19589 -1.00 0.319
## warszafkaTRUE 0.15055 0.15870 0.95 0.344
## inne_firmyTRUE -0.00108 0.23375 0.00 0.996
## indyw_konsTRUE 0.26818 0.17967 1.49 0.137
## globalTRUE 0.39238 0.16672 2.35 0.019 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.31 on 306 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.0671, Adjusted R-squared: 0.0366
## F-statistic: 2.2 on 10 and 306 DF, p-value: 0.0176
ss1<-lm(B1_11~informacja+branza+wielkosc+warszafka+inne_firmy+indyw_kons+global,baza1)
summary(ss1)
##
## Call:
## lm(formula = B1_11 ~ informacja + branza + wielkosc + warszafka +
## inne_firmy + indyw_kons + global, data = baza1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.165 -0.776 0.146 0.799 2.535
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.3112 0.2978 11.12 < 2e-16 ***
## informacja 0.5427 0.0774 7.01 1.5e-11 ***
## branzahandel 0.0826 0.2072 0.40 0.690
## branzausługi 0.0141 0.1783 0.08 0.937
## branzaadm,edu,samo -0.1103 0.2238 -0.49 0.622
## wielkosc10-49 osób 0.0908 0.1691 0.54 0.592
## wielkosc50 i więcej osób 0.0436 0.1768 0.25 0.805
## warszafkaTRUE 0.3120 0.1441 2.17 0.031 *
## inne_firmyTRUE -0.1594 0.2121 -0.75 0.453
## indyw_konsTRUE 0.0362 0.1625 0.22 0.824
## globalTRUE 0.3162 0.1508 2.10 0.037 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.18 on 301 degrees of freedom
## (9 observations deleted due to missingness)
## Multiple R-squared: 0.178, Adjusted R-squared: 0.151
## F-statistic: 6.52 on 10 and 301 DF, p-value: 3.98e-09
Tylko takie obrazki są mało informatywne, tzn można dać rozrzut i linię, to jest nudne, trzeba wymyślić coś ciekawszego
ggplot(baza1,aes(x=B1_11,y=B1_10))+geom_point(position=position_jitter(),colour="darkgreen")+geom_smooth(method="lm",se=F,size=1.6)+labs(x="globalizacja jako szansa",y="globalizacja jako zagrożenie")+theme_bw()+theme(text=element_text(size=40))
## Warning: Removed 9 rows containing missing values (stat_smooth).
## Warning: Removed 9 rows containing missing values (geom_point).
## Warning: conversion failure on 'globalizacja jako zagrożenie' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'globalizacja jako zagrożenie' in 'mbcsToSbcs': dot substituted for <bc>
## Warning: conversion failure on 'globalizacja jako zagrożenie' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'globalizacja jako zagrożenie' in 'mbcsToSbcs': dot substituted for <bc>
## Warning: conversion failure on 'globalizacja jako zagrożenie' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'globalizacja jako zagrożenie' in 'mbcsToSbcs': dot substituted for <bc>
ggsave("dcz1.png",width=16,height=16,dpi=250)
## Warning: Removed 9 rows containing missing values (stat_smooth).
## Warning: Removed 9 rows containing missing values (geom_point).
ggplot(baza1,aes(x=B1_11,y=zmiany))+geom_point(position=position_jitter(),colour="darkgreen")+geom_smooth(method="lm",se=F,size=1.6)+labs(x="globalizacja jako szansa",y="zmiany")+theme_bw()+theme(text=element_text(size=40))
## Warning: Removed 9 rows containing missing values (stat_smooth).
## Warning: Removed 9 rows containing missing values (geom_point).
ggsave("dcz2.png",width=16,height=16,dpi=250)
## Warning: Removed 9 rows containing missing values (stat_smooth).
## Warning: Removed 9 rows containing missing values (geom_point).
ggplot(baza1,aes(x=B1_11,y=adaptacja))+geom_point(position=position_jitter(),colour="darkgreen")+geom_smooth(method="lm",se=F,size=1.6)+labs(x="globalizacja jako szansa",y="zachowania adaptacyjne")+theme_bw()+theme(text=element_text(size=40))
## Warning: Removed 9 rows containing missing values (stat_smooth).
## Warning: Removed 9 rows containing missing values (geom_point).
ggsave("dcz3.png",width=16,height=16,dpi=250)
## Warning: Removed 9 rows containing missing values (stat_smooth).
## Warning: Removed 9 rows containing missing values (geom_point).
ss1<-lm(adaptacja~B1_10+B1_11+branza+wielkosc+warszafka+inne_firmy+indyw_kons+global,baza1)
summary(ss1)
##
## Call:
## lm(formula = adaptacja ~ B1_10 + B1_11 + branza + wielkosc +
## warszafka + inne_firmy + indyw_kons + global, data = baza1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.1159 -0.5321 0.0064 0.5372 1.9881
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.08578 0.24340 -4.46 1.2e-05 ***
## B1_10 0.00372 0.03678 0.10 0.9194
## B1_11 0.23149 0.03816 6.07 3.9e-09 ***
## branzahandel -0.11032 0.14274 -0.77 0.4402
## branzausługi 0.10958 0.12182 0.90 0.3691
## branzaadm,edu,samo -0.03545 0.15380 -0.23 0.8179
## wielkosc10-49 osób 0.34271 0.11615 2.95 0.0034 **
## wielkosc50 i więcej osób 0.50508 0.11949 4.23 3.1e-05 ***
## warszafkaTRUE 0.00995 0.10010 0.10 0.9209
## inne_firmyTRUE -0.09277 0.14613 -0.63 0.5260
## indyw_konsTRUE -0.07073 0.11253 -0.63 0.5302
## globalTRUE 0.20579 0.10471 1.97 0.0503 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.813 on 300 degrees of freedom
## (9 observations deleted due to missingness)
## Multiple R-squared: 0.218, Adjusted R-squared: 0.189
## F-statistic: 7.6 on 11 and 300 DF, p-value: 1.47e-11
ss1<-lm(A6_2~B1_10+B1_11+branza+wielkosc+warszafka+inne_firmy+indyw_kons+global,baza1)
summary(ss1)
##
## Call:
## lm(formula = A6_2 ~ B1_10 + B1_11 + branza + wielkosc + warszafka +
## inne_firmy + indyw_kons + global, data = baza1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.893 -0.621 0.206 0.506 1.640
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.4069 0.2725 12.50 <2e-16 ***
## B1_10 -0.0162 0.0412 -0.39 0.69
## B1_11 0.0410 0.0426 0.96 0.34
## branzahandel -0.1311 0.1591 -0.82 0.41
## branzausługi 0.1130 0.1360 0.83 0.41
## branzaadm,edu,samo -0.1676 0.1732 -0.97 0.33
## wielkosc10-49 osób 0.0131 0.1299 0.10 0.92
## wielkosc50 i więcej osób 0.1342 0.1334 1.01 0.32
## warszafkaTRUE -0.1635 0.1121 -1.46 0.15
## inne_firmyTRUE 0.2079 0.1637 1.27 0.21
## indyw_konsTRUE -0.0196 0.1259 -0.16 0.88
## globalTRUE 0.0542 0.1170 0.46 0.64
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.906 on 297 degrees of freedom
## (12 observations deleted due to missingness)
## Multiple R-squared: 0.0373, Adjusted R-squared: 0.00162
## F-statistic: 1.05 on 11 and 297 DF, p-value: 0.406
ss1<-lm(A6_3~B1_10+B1_11+branza+wielkosc+warszafka+inne_firmy+indyw_kons+global,baza1)
summary(ss1)
##
## Call:
## lm(formula = A6_3 ~ B1_10 + B1_11 + branza + wielkosc + warszafka +
## inne_firmy + indyw_kons + global, data = baza1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.7493 -0.6695 0.0633 0.5586 1.4541
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.005320 0.247365 16.19 <2e-16 ***
## B1_10 -0.066602 0.037481 -1.78 0.077 .
## B1_11 0.033144 0.038845 0.85 0.394
## branzahandel 0.044294 0.145070 0.31 0.760
## branzausługi 0.143561 0.123804 1.16 0.247
## branzaadm,edu,samo -0.000807 0.157018 -0.01 0.996
## wielkosc10-49 osób 0.213054 0.118050 1.80 0.072 .
## wielkosc50 i więcej osób 0.218795 0.121645 1.80 0.073 .
## warszafkaTRUE -0.108639 0.102108 -1.06 0.288
## inne_firmyTRUE -0.062810 0.148837 -0.42 0.673
## indyw_konsTRUE -0.060816 0.114393 -0.53 0.595
## globalTRUE -0.059097 0.106448 -0.56 0.579
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.826 on 299 degrees of freedom
## (10 observations deleted due to missingness)
## Multiple R-squared: 0.038, Adjusted R-squared: 0.00259
## F-statistic: 1.07 on 11 and 299 DF, p-value: 0.383
globalizacja jako szansa
zarówno warszawa, jak i działalność globalna ma wpływ brane oddzielnie, natomiast wrzucone do jednego modelu - wazniejszy jest wpływ warszawy
ss1<-lm(B1_11~global,baza1)
summary(ss1)
##
## Call:
## lm(formula = B1_11 ~ global, data = baza1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.731 -0.731 0.270 1.270 1.597
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.4035 0.0972 35.01 <2e-16 ***
## globalTRUE 0.3270 0.1446 2.26 0.024 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.27 on 310 degrees of freedom
## (9 observations deleted due to missingness)
## Multiple R-squared: 0.0162, Adjusted R-squared: 0.0131
## F-statistic: 5.11 on 1 and 310 DF, p-value: 0.0244
ss1<-lm(B1_11~warszafka,baza1)
summary(ss1)
##
## Call:
## lm(formula = B1_11 ~ warszafka, data = baza1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.727 -0.727 0.273 1.273 1.636
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.364 0.103 32.59 <2e-16 ***
## warszafkaTRUE 0.362 0.144 2.52 0.012 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.27 on 310 degrees of freedom
## (9 observations deleted due to missingness)
## Multiple R-squared: 0.0201, Adjusted R-squared: 0.0169
## F-statistic: 6.36 on 1 and 310 DF, p-value: 0.0122
ss1<-lm(B1_11~warszafka+global,baza1)
summary(ss1)
##
## Call:
## lm(formula = B1_11 ~ warszafka + global, data = baza1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.841 -0.841 0.159 1.159 1.723
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.277 0.114 28.66 <2e-16 ***
## warszafkaTRUE 0.305 0.147 2.08 0.039 *
## globalTRUE 0.259 0.148 1.76 0.080 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.26 on 309 degrees of freedom
## (9 observations deleted due to missingness)
## Multiple R-squared: 0.0298, Adjusted R-squared: 0.0235
## F-statistic: 4.74 on 2 and 309 DF, p-value: 0.00937
ss1<-lm(B1_11~warszafka+global+branza+wielkosc+inne_firmy+indyw_kons,baza1)
summary(ss1)
##
## Call:
## lm(formula = B1_11 ~ warszafka + global + branza + wielkosc +
## inne_firmy + indyw_kons, data = baza1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.949 -0.881 0.238 1.073 2.041
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.9850 0.3167 9.42 <2e-16 ***
## warszafkaTRUE 0.3278 0.1551 2.11 0.035 *
## globalTRUE 0.2554 0.1621 1.58 0.116
## branzahandel 0.2052 0.2223 0.92 0.357
## branzausługi 0.2191 0.1894 1.16 0.248
## branzaadm,edu,samo 0.0773 0.2393 0.32 0.747
## wielkosc10-49 osób 0.2240 0.1809 1.24 0.217
## wielkosc50 i więcej osób 0.3287 0.1853 1.77 0.077 .
## inne_firmyTRUE -0.0839 0.2281 -0.37 0.713
## indyw_konsTRUE 0.0582 0.1750 0.33 0.740
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.27 on 302 degrees of freedom
## (9 observations deleted due to missingness)
## Multiple R-squared: 0.0437, Adjusted R-squared: 0.0152
## F-statistic: 1.53 on 9 and 302 DF, p-value: 0.135
globalizacja jako zagrożenie
Tutaj wpływa działalnosć za granicą
ss1<-lm(B1_10~global,baza1)
summary(ss1)
##
## Call:
## lm(formula = B1_10 ~ global, data = baza1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.560 -1.204 0.440 0.795 1.796
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.2045 0.0997 32.13 <2e-16 ***
## globalTRUE 0.3557 0.1495 2.38 0.018 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.32 on 315 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.0177, Adjusted R-squared: 0.0145
## F-statistic: 5.66 on 1 and 315 DF, p-value: 0.018
ss1<-lm(B1_10~warszafka,baza1)
summary(ss1)
##
## Call:
## lm(formula = B1_10 ~ warszafka, data = baza1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.444 -1.277 0.556 0.723 1.723
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.277 0.107 30.63 <2e-16 ***
## warszafkaTRUE 0.167 0.150 1.12 0.27
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.33 on 315 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.00394, Adjusted R-squared: 0.000775
## F-statistic: 1.25 on 1 and 315 DF, p-value: 0.265
ss1<-lm(B1_10~warszafka+global,baza1)
summary(ss1)
##
## Call:
## lm(formula = B1_10 ~ warszafka + global, data = baza1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.593 -1.167 0.407 0.833 1.833
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.1672 0.1178 26.89 <2e-16 ***
## warszafkaTRUE 0.0912 0.1528 0.60 0.55
## globalTRUE 0.3348 0.1537 2.18 0.03 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.32 on 314 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.0188, Adjusted R-squared: 0.0125
## F-statistic: 3 on 2 and 314 DF, p-value: 0.0511
ss1<-lm(B1_10~warszafka+global+branza+wielkosc+inne_firmy+indyw_kons,baza1)
summary(ss1)
##
## Call:
## lm(formula = B1_10 ~ warszafka + global + branza + wielkosc +
## inne_firmy + indyw_kons, data = baza1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.82 -1.01 0.12 1.05 2.14
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.9532 0.3276 9.01 <2e-16 ***
## warszafkaTRUE 0.1599 0.1598 1.00 0.318
## globalTRUE 0.3677 0.1676 2.19 0.029 *
## branzahandel 0.3078 0.2288 1.35 0.179
## branzausługi -0.1370 0.1941 -0.71 0.481
## branzaadm,edu,samo -0.2791 0.2461 -1.13 0.258
## wielkosc10-49 osób 0.0638 0.1861 0.34 0.732
## wielkosc50 i więcej osób -0.0888 0.1921 -0.46 0.644
## inne_firmyTRUE 0.0279 0.2352 0.12 0.905
## indyw_konsTRUE 0.2787 0.1810 1.54 0.125
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.32 on 307 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.0499, Adjusted R-squared: 0.0221
## F-statistic: 1.79 on 9 and 307 DF, p-value: 0.0688
P.S. jest jeszcze rola postaw
ss1<-lm(B1_10~postawa,baza1)
summary(ss1)
##
## Call:
## lm(formula = B1_10 ~ postawa, data = baza1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.598 -1.262 0.402 0.738 1.738
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.2800 0.1188 27.62 <2e-16 ***
## postawareal 0.3177 0.1854 1.71 0.088 .
## postawakonserw -0.0179 0.1767 -0.10 0.920
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.33 on 312 degrees of freedom
## (6 observations deleted due to missingness)
## Multiple R-squared: 0.012, Adjusted R-squared: 0.0057
## F-statistic: 1.9 on 2 and 312 DF, p-value: 0.151
ss1<-lm(B1_11~postawa,baza1)
summary(ss1)
##
## Call:
## lm(formula = B1_11 ~ postawa, data = baza1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.693 -0.694 0.306 1.306 1.743
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.6935 0.1138 32.46 <2e-16 ***
## postawareal -0.0191 0.1778 -0.11 0.914
## postawakonserw -0.4361 0.1698 -2.57 0.011 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.27 on 308 degrees of freedom
## (10 observations deleted due to missingness)
## Multiple R-squared: 0.0247, Adjusted R-squared: 0.0184
## F-statistic: 3.9 on 2 and 308 DF, p-value: 0.0212
Pamiętać - położenie w Warszawie jest skorelowane z działalnością w kraju i za granicą
table(baza1$global, baza1$warszafka)
##
## FALSE TRUE
## FALSE 105 75
## TRUE 51 90
Lokalizacja a obszar działania
table(baza1$A4,baza1$CS)
##
## gmina wiejska miasto 100-199 tys. miasto 10-19 tys.
## 1 12 1 3
## 2 6 2 8
## 3 2 1 2
## 4 5 1 10
## 5 9 1 8
## 6 1 0 3
##
## miasto 200-499 tys. miasto 20-49 tys. miasto 50-99 tys.
## 1 0 12 0
## 2 2 6 0
## 3 0 3 1
## 4 4 5 3
## 5 5 7 2
## 6 3 5 2
##
## miasto do 9 tys. miasto ponad 1000 tys.
## 1 8 8
## 2 4 2
## 3 0 50
## 4 4 15
## 5 3 56
## 6 2 34
w1<-wpct(baza1$A4[baza1$CS%in%c("miasto ponad 1000 tys.")],baza1$waga[baza1$CS%in%c("miasto ponad 1000 tys.")])
w1
## 1 2 3 4 5 6
## 0.11693 0.01899 0.30886 0.06594 0.32518 0.16410
w2<-wpct(baza1$A4[baza1$CS%in%c("miasto 200-499 tys.","miasto 100-199 tys.")],baza1$waga[baza1$CS%in%c("miasto 200-499 tys.","miasto 100-199 tys.")])
w2
## 1 2 3 4 5 6
## 0.002786 0.024396 0.268477 0.372641 0.310490 0.021210
w3<-wpct(baza1$A4[baza1$CS%in%c("miasto 50-99 tys.","miasto 20-49 tys.","miasto 10-19 tys.","miasto do 9 tys.")],baza1$waga[baza1$CS%in%c("miasto 50-99 tys.","miasto 20-49 tys.","miasto 10-19 tys.","miasto do 9 tys.")])
w3
## 1 2 3 4 5 6
## 0.027112 0.179149 0.162849 0.280206 0.342365 0.008319
w4<-wpct(baza1$A4[baza1$CS%in%c("gmina wiejska")],baza1$waga[baza1$CS%in%c("gmina wiejska")])
w4
## 1 2 3 4 5 6
## 0.3335061 0.0982707 0.1232628 0.2301003 0.2141224 0.0007376
m<-rbind(w1,w2,w3,w4)
rownames(m)<-c("Warszawa","Radom i płock","miasta inne","wieś")
m
## 1 2 3 4 5 6
## Warszawa 0.116926 0.01899 0.3089 0.06594 0.3252 0.1641015
## Radom i płock 0.002786 0.02440 0.2685 0.37264 0.3105 0.0212098
## miasta inne 0.027112 0.17915 0.1628 0.28021 0.3424 0.0083188
## wieś 0.333506 0.09827 0.1233 0.23010 0.2141 0.0007376
## 1 2 3 4 5 6
## 0.11475 0.06359 0.25569 0.14073 0.31746 0.10777
##
## produkcja handel usługi adm,edu,samo
## 2-9 osób 19 27 49 10
## 10-49 osób 33 22 35 16
## 50 i więcej osób 38 10 29 33
## 1 2 3 4 5 6
## 0.07223 0.07434 0.11168 0.29470 0.37149 0.07556
## 1 2 3 4 5 6
## 0.12122 0.06230 0.30376 0.08153 0.28469 0.14649
## 1 2 3 4 5 6
## 0.10945 0.06029 0.30087 0.14979 0.36907 0.01052
## 1 2 3 4 5 6
## 0.3051 0.1695 0.2034 0.1525 0.1356 0.0339
## 1 2 3 4 5 6
## 0.11398 0.06149 0.25872 0.14161 0.31872 0.10547
## 1 2 3 4 5 6
## 0.1262 0.1091 0.2026 0.1102 0.3124 0.1395
## 1 2 3 4 5 6
## 0.1588 0.1296 0.1140 0.1564 0.1943 0.2468
prop.table(table(baza1\(A4[baza1\)wielkosc==“50 i więcej osób”])) ##### Tu jest kilka zaskoczeń. za granicą działają głósnie firmy usługowe, rzadko produkcyjne, a wśród największych firm jest więcej produkcyjnych
Zmienne: wielkosc branza warszafka inne_firmy indyw_kons A4 - globalnie istotne_irt reakcja_irt adaptacja - deklarowana zmiany - wprowadzone zmiany informacja - pozyskiwanie informacji postawa kompetencje samorzad_irt
A6_1 kondycja branzy A6_2 satysfakcja firma A6_3 satysfakcja adaptacja
D2_5 istotność nowych technologii
data<-subset(baza1,select=c("wielkosc","branza","warszafka","inne_firmy","indyw_kons","global","postawa","istotne_irt","reakcja_irt","adaptacja","resistance","zmiany","informacja","kompetencje","samorzad_irt","D2_5","A6_1","A6_2","A6_3"))
data$postawa_tak<-data$postawa!="konserw"
describe(data)
## vars n mean sd median trimmed mad min max range
## wielkosc* 1 321 2.02 0.82 2.00 2.02 1.48 1.00 3.00 2.00
## branza* 2 321 2.44 1.09 3.00 2.42 1.48 1.00 4.00 3.00
## warszafka* 3 321 0.51 0.50 1.00 0.52 0.00 0.00 1.00 1.00
## inne_firmy* 4 321 0.85 0.35 1.00 0.94 0.00 0.00 1.00 1.00
## indyw_kons* 5 321 0.68 0.47 1.00 0.73 0.00 0.00 1.00 1.00
## global* 6 321 0.44 0.50 0.00 0.42 0.00 0.00 1.00 1.00
## postawa* 7 318 1.93 0.85 2.00 1.91 1.48 1.00 3.00 2.00
## istotne_irt 8 321 -0.01 0.89 0.03 -0.01 0.77 -3.06 2.68 5.74
## reakcja_irt 9 321 0.11 0.81 0.06 0.08 0.71 -3.54 2.68 6.22
## adaptacja 10 321 0.01 0.90 0.03 0.02 0.88 -2.07 2.39 4.46
## resistance 11 321 0.00 0.75 -0.02 0.01 0.69 -1.84 1.95 3.79
## zmiany 12 321 0.01 0.89 0.01 0.00 0.87 -2.10 2.75 4.85
## informacja 13 321 0.01 0.90 -0.03 -0.01 0.92 -2.35 3.08 5.43
## kompetencje 14 321 -0.01 0.92 0.03 -0.01 0.87 -3.39 1.82 5.21
## samorzad_irt 15 321 0.17 0.72 -0.38 0.07 0.08 -0.44 2.13 2.57
## D2_5 16 319 3.59 1.20 4.00 3.70 1.48 1.00 5.00 4.00
## A6_1 17 311 3.29 0.96 3.00 3.32 1.48 1.00 5.00 4.00
## A6_2 18 318 3.64 0.91 4.00 3.70 1.48 1.00 5.00 4.00
## A6_3 19 318 3.93 0.83 4.00 3.98 1.48 1.00 5.00 4.00
## postawa_tak* 20 318 0.67 0.47 1.00 0.71 0.00 0.00 1.00 1.00
## skew kurtosis se
## wielkosc* -0.03 -1.52 0.05
## branza* -0.07 -1.32 0.06
## warszafka* -0.06 -2.00 0.03
## inne_firmy* -1.99 1.97 0.02
## indyw_kons* -0.78 -1.40 0.03
## global* 0.24 -1.95 0.03
## postawa* 0.14 -1.61 0.05
## istotne_irt 0.00 0.65 0.05
## reakcja_irt 0.16 1.57 0.05
## adaptacja -0.03 -0.24 0.05
## resistance -0.13 -0.14 0.04
## zmiany 0.25 0.26 0.05
## informacja 0.22 0.10 0.05
## kompetencje -0.20 0.27 0.05
## samorzad_irt 0.83 -0.53 0.04
## D2_5 -0.55 -0.59 0.07
## A6_1 -0.36 -0.02 0.05
## A6_2 -0.41 -0.06 0.05
## A6_3 -0.47 -0.11 0.05
## postawa_tak* -0.73 -1.47 0.03
hh<-data[,8:19]
names(hh)<-c("istotność trendów","reakcja na trendy","deklarowana adaptacyjność","opór wobec zmian","wprowadzone zmiany","pozyskiwanie informacji","kompetencja pracowników","współpraca z samorządem","istotność nowych technologii","kondycja branży","kondycja firmy","zdolność do adaptacji")
mm<-cor(hh,use="pairwise.complete.obs")
corrplot(mm, shade.col=NA, tl.col="black", tl.srt=90, addCoef.col="black",method="shade",insig="n",tl.pos="lt")
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## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <82>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <85>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <bc>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <82>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <85>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <bc>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <82>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <85>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <bc>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <82>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <85>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <bc>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <82>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <85>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <bc>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <82>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <85>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <bc>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <82>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <85>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <bc>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <82>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <85>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <bc>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <82>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <85>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <bc>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <82>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <85>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <bc>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <82>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'współpraca z samorządem' in 'mbcsToSbcs': dot substituted for <85>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność nowych technologii' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'kondycja branży' in 'mbcsToSbcs': dot substituted for <bc>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'zdolność do adaptacji' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <c4>
## Warning: conversion failure on 'istotność trendów' in 'mbcsToSbcs': dot substituted for <87>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c5>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <9b>
## Warning: conversion failure on 'deklarowana adaptacyjność' in 'mbcsToSbcs': dot substituted for <c4>
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jpeg("model_kor.jpeg",width=3000,height=3000,quality=100,res=400)
par(cex=.75)
corrplot(mm, shade.col=NA, tl.col="black", tl.srt=90, addCoef.col="black",method="shade",insig="n",tl.pos="lt")
par(cex=1)
dev.off()
## pdf
## 2
rola specyfiki firmy
summary(lm(istotne_irt~wielkosc+branza+warszafka+inne_firmy+indyw_kons+global+D2_5,data))
##
## Call:
## lm(formula = istotne_irt ~ wielkosc + branza + warszafka + inne_firmy +
## indyw_kons + global + D2_5, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.1516 -0.4596 0.0128 0.5174 2.4383
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.674492 0.239128 -7.00 1.6e-11 ***
## wielkosc10-49 osób 0.246889 0.113684 2.17 0.031 *
## wielkosc50 i więcej osób 0.094007 0.117893 0.80 0.426
## branzahandel 0.217468 0.140452 1.55 0.123
## branzausługi 0.185273 0.118691 1.56 0.120
## branzaadm,edu,samo 0.351843 0.149805 2.35 0.019 *
## warszafkaTRUE -0.000712 0.097544 -0.01 0.994
## inne_firmyTRUE 0.241537 0.140924 1.71 0.088 .
## indyw_konsTRUE 0.071101 0.110591 0.64 0.521
## globalTRUE 0.035459 0.102509 0.35 0.730
## D2_5 0.308967 0.038407 8.04 1.9e-14 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.806 on 308 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.204, Adjusted R-squared: 0.178
## F-statistic: 7.89 on 10 and 308 DF, p-value: 2.64e-11
summary(lm(reakcja_irt~wielkosc+branza+warszafka+inne_firmy+indyw_kons+global+D2_5,data))
##
## Call:
## lm(formula = reakcja_irt ~ wielkosc + branza + warszafka + inne_firmy +
## indyw_kons + global + D2_5, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.0055 -0.4531 -0.0157 0.4336 2.4501
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.0335 0.2248 -4.60 6.3e-06 ***
## wielkosc10-49 osób 0.1561 0.1069 1.46 0.145
## wielkosc50 i więcej osób 0.0116 0.1108 0.10 0.917
## branzahandel 0.2280 0.1320 1.73 0.085 .
## branzausługi 0.2860 0.1116 2.56 0.011 *
## branzaadm,edu,samo 0.0531 0.1408 0.38 0.706
## warszafkaTRUE 0.0089 0.0917 0.10 0.923
## inne_firmyTRUE 0.1876 0.1325 1.42 0.158
## indyw_konsTRUE 0.0821 0.1040 0.79 0.430
## globalTRUE -0.1568 0.0964 -1.63 0.105
## D2_5 0.2177 0.0361 6.03 4.7e-09 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.758 on 308 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.149, Adjusted R-squared: 0.121
## F-statistic: 5.38 on 10 and 308 DF, p-value: 2.43e-07
summary(lm(adaptacja~wielkosc+branza+warszafka+inne_firmy+indyw_kons+global+D2_5,data))
##
## Call:
## lm(formula = adaptacja ~ wielkosc + branza + warszafka + inne_firmy +
## indyw_kons + global + D2_5, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.5891 -0.4691 -0.0148 0.4801 1.9631
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.6732 0.2205 -7.59 3.9e-13 ***
## wielkosc10-49 osób 0.3341 0.1048 3.19 0.0016 **
## wielkosc50 i więcej osób 0.4668 0.1087 4.29 2.4e-05 ***
## branzahandel -0.0248 0.1295 -0.19 0.8485
## branzausługi 0.0988 0.1095 0.90 0.3673
## branzaadm,edu,samo 0.0562 0.1382 0.41 0.6842
## warszafkaTRUE -0.0130 0.0900 -0.14 0.8855
## inne_firmyTRUE 0.0362 0.1300 0.28 0.7807
## indyw_konsTRUE -0.0960 0.1020 -0.94 0.3474
## globalTRUE 0.2377 0.0945 2.51 0.0125 *
## D2_5 0.3630 0.0354 10.25 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.743 on 308 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.339, Adjusted R-squared: 0.318
## F-statistic: 15.8 on 10 and 308 DF, p-value: <2e-16
summary(lm(resistance~wielkosc+branza+warszafka+inne_firmy+indyw_kons+global+D2_5,data))
##
## Call:
## lm(formula = resistance ~ wielkosc + branza + warszafka + inne_firmy +
## indyw_kons + global + D2_5, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.8749 -0.3956 0.0055 0.4593 2.0762
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.6800 0.2157 3.15 0.00177 **
## wielkosc10-49 osób -0.1037 0.1025 -1.01 0.31272
## wielkosc50 i więcej osób -0.3262 0.1063 -3.07 0.00235 **
## branzahandel -0.1385 0.1267 -1.09 0.27497
## branzausługi -0.0710 0.1070 -0.66 0.50779
## branzaadm,edu,samo -0.0768 0.1351 -0.57 0.56996
## warszafkaTRUE -0.0802 0.0880 -0.91 0.36254
## inne_firmyTRUE -0.0776 0.1271 -0.61 0.54212
## indyw_konsTRUE 0.0871 0.0997 0.87 0.38315
## globalTRUE 0.0313 0.0924 0.34 0.73507
## D2_5 -0.1205 0.0346 -3.48 0.00058 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.727 on 308 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.0815, Adjusted R-squared: 0.0516
## F-statistic: 2.73 on 10 and 308 DF, p-value: 0.00311
summary(lm(zmiany~wielkosc+branza+warszafka+inne_firmy+indyw_kons+global+D2_5,data))
##
## Call:
## lm(formula = zmiany ~ wielkosc + branza + warszafka + inne_firmy +
## indyw_kons + global + D2_5, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.755 -0.481 -0.035 0.487 2.574
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.9020 0.2261 -8.41 1.5e-15 ***
## wielkosc10-49 osób 0.2318 0.1075 2.16 0.03187 *
## wielkosc50 i więcej osób 0.4312 0.1115 3.87 0.00013 ***
## branzahandel 0.3333 0.1328 2.51 0.01261 *
## branzausługi 0.1606 0.1122 1.43 0.15347
## branzaadm,edu,samo -0.0764 0.1417 -0.54 0.58999
## warszafkaTRUE 0.0903 0.0922 0.98 0.32828
## inne_firmyTRUE 0.2569 0.1333 1.93 0.05485 .
## indyw_konsTRUE 0.1039 0.1046 0.99 0.32107
## globalTRUE 0.0587 0.0969 0.61 0.54541
## D2_5 0.3379 0.0363 9.30 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.762 on 308 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.289, Adjusted R-squared: 0.265
## F-statistic: 12.5 on 10 and 308 DF, p-value: <2e-16
summary(lm(informacja~wielkosc+branza+warszafka+inne_firmy+indyw_kons+global+D2_5,data))
##
## Call:
## lm(formula = informacja ~ wielkosc + branza + warszafka + inne_firmy +
## indyw_kons + global + D2_5, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.4361 -0.5451 0.0239 0.4722 2.8190
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.5477 0.2438 -6.35 7.8e-10 ***
## wielkosc10-49 osób 0.2290 0.1159 1.98 0.04910 *
## wielkosc50 i więcej osób 0.4345 0.1202 3.61 0.00035 ***
## branzahandel 0.2194 0.1432 1.53 0.12650
## branzausługi 0.3046 0.1210 2.52 0.01234 *
## branzaadm,edu,samo 0.3467 0.1527 2.27 0.02393 *
## warszafkaTRUE -0.0101 0.0995 -0.10 0.91891
## inne_firmyTRUE 0.2634 0.1437 1.83 0.06778 .
## indyw_konsTRUE 0.0325 0.1128 0.29 0.77321
## globalTRUE -0.1445 0.1045 -1.38 0.16779
## D2_5 0.2615 0.0392 6.68 1.1e-10 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.822 on 308 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.195, Adjusted R-squared: 0.169
## F-statistic: 7.46 on 10 and 308 DF, p-value: 1.25e-10
summary(lm(kompetencje~wielkosc+branza+warszafka+inne_firmy+indyw_kons+global+D2_5,data))
##
## Call:
## lm(formula = kompetencje ~ wielkosc + branza + warszafka + inne_firmy +
## indyw_kons + global + D2_5, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.9146 -0.5486 0.0146 0.4987 2.0474
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.4568 0.2521 -1.81 0.071 .
## wielkosc10-49 osób -0.1929 0.1199 -1.61 0.109
## wielkosc50 i więcej osób -0.0483 0.1243 -0.39 0.698
## branzahandel 0.0276 0.1481 0.19 0.852
## branzausługi 0.2250 0.1252 1.80 0.073 .
## branzaadm,edu,samo 0.2649 0.1580 1.68 0.095 .
## warszafkaTRUE 0.1214 0.1029 1.18 0.239
## inne_firmyTRUE -0.3766 0.1486 -2.53 0.012 *
## indyw_konsTRUE -0.0929 0.1166 -0.80 0.426
## globalTRUE -0.2154 0.1081 -1.99 0.047 *
## D2_5 0.2254 0.0405 5.56 5.7e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.85 on 308 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.17, Adjusted R-squared: 0.143
## F-statistic: 6.31 on 10 and 308 DF, p-value: 8.26e-09
summary(lm(samorzad_irt~wielkosc+branza+warszafka+inne_firmy+indyw_kons+global+D2_5,data))
##
## Call:
## lm(formula = samorzad_irt ~ wielkosc + branza + warszafka + inne_firmy +
## indyw_kons + global + D2_5, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.5720 -0.3791 -0.0884 0.3897 1.8953
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.0971 0.1709 -0.57 0.570
## wielkosc10-49 osób 0.0281 0.0813 0.35 0.729
## wielkosc50 i więcej osób 0.4888 0.0843 5.80 1.6e-08 ***
## branzahandel -0.2508 0.1004 -2.50 0.013 *
## branzausługi -0.0794 0.0848 -0.94 0.350
## branzaadm,edu,samo 0.5666 0.1071 5.29 2.3e-07 ***
## warszafkaTRUE -0.1585 0.0697 -2.27 0.024 *
## inne_firmyTRUE -0.0582 0.1007 -0.58 0.564
## indyw_konsTRUE 0.0668 0.0790 0.85 0.399
## globalTRUE -0.1013 0.0733 -1.38 0.168
## D2_5 0.0533 0.0275 1.94 0.053 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.576 on 308 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.382, Adjusted R-squared: 0.362
## F-statistic: 19.1 on 10 and 308 DF, p-value: <2e-16
summary(glm(postawa!="konserw"~wielkosc+branza+warszafka+inne_firmy+indyw_kons+global+D2_5,data,family="binomial"))
##
## Call:
## glm(formula = postawa != "konserw" ~ wielkosc + branza + warszafka +
## inne_firmy + indyw_kons + global + D2_5, family = "binomial",
## data = data)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.040 -1.147 0.648 0.879 1.554
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.8330 0.6710 -2.73 0.0063 **
## wielkosc10-49 osób 0.4016 0.3132 1.28 0.1997
## wielkosc50 i więcej osób 0.6117 0.3303 1.85 0.0640 .
## branzahandel 0.3336 0.3934 0.85 0.3965
## branzausługi 0.1772 0.3350 0.53 0.5968
## branzaadm,edu,samo 0.2291 0.4157 0.55 0.5815
## warszafkaTRUE -0.1750 0.2740 -0.64 0.5230
## inne_firmyTRUE 0.4365 0.3861 1.13 0.2582
## indyw_konsTRUE -0.2351 0.3126 -0.75 0.4519
## globalTRUE 0.0302 0.2874 0.11 0.9164
## D2_5 0.5520 0.1100 5.02 5.2e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 400.40 on 315 degrees of freedom
## Residual deviance: 365.91 on 305 degrees of freedom
## (5 observations deleted due to missingness)
## AIC: 387.9
##
## Number of Fisher Scoring iterations: 4
postrzeganie a podejmowane działania
summary(lm(adaptacja~istotne_irt+reakcja_irt+wielkosc+branza+warszafka+inne_firmy+indyw_kons+global+D2_5,data))
##
## Call:
## lm(formula = adaptacja ~ istotne_irt + reakcja_irt + wielkosc +
## branza + warszafka + inne_firmy + indyw_kons + global + D2_5,
## data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.118 -0.444 0.013 0.417 2.076
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.1250 0.2259 -4.98 1.1e-06 ***
## istotne_irt 0.2547 0.0530 4.81 2.4e-06 ***
## reakcja_irt 0.1177 0.0564 2.09 0.0376 *
## wielkosc10-49 osób 0.2528 0.0999 2.53 0.0119 *
## wielkosc50 i więcej osób 0.4415 0.1028 4.29 2.4e-05 ***
## branzahandel -0.1070 0.1231 -0.87 0.3855
## branzausługi 0.0180 0.1046 0.17 0.8636
## branzaadm,edu,samo -0.0396 0.1317 -0.30 0.7637
## warszafkaTRUE -0.0138 0.0850 -0.16 0.8708
## inne_firmyTRUE -0.0474 0.1235 -0.38 0.7014
## indyw_konsTRUE -0.1238 0.0964 -1.28 0.2004
## globalTRUE 0.2471 0.0898 2.75 0.0063 **
## D2_5 0.2587 0.0374 6.92 2.6e-11 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.702 on 306 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.414, Adjusted R-squared: 0.391
## F-statistic: 18 on 12 and 306 DF, p-value: <2e-16
summary(lm(zmiany~istotne_irt+reakcja_irt+wielkosc+branza+warszafka+inne_firmy+indyw_kons+global+D2_5,data))
##
## Call:
## lm(formula = zmiany ~ istotne_irt + reakcja_irt + wielkosc +
## branza + warszafka + inne_firmy + indyw_kons + global + D2_5,
## data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.0970 -0.4277 -0.0005 0.4410 2.1378
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.3205 0.2295 -5.75 2.1e-08 ***
## istotne_irt 0.2173 0.0538 4.04 6.9e-05 ***
## reakcja_irt 0.2106 0.0573 3.68 0.00028 ***
## wielkosc10-49 osób 0.1453 0.1014 1.43 0.15318
## wielkosc50 i więcej osób 0.4083 0.1044 3.91 0.00011 ***
## branzahandel 0.2380 0.1251 1.90 0.05797 .
## branzausługi 0.0601 0.1062 0.57 0.57176
## branzaadm,edu,samo -0.1640 0.1338 -1.23 0.22105
## warszafkaTRUE 0.0886 0.0863 1.03 0.30543
## inne_firmyTRUE 0.1649 0.1254 1.31 0.18970
## indyw_konsTRUE 0.0712 0.0980 0.73 0.46793
## globalTRUE 0.0840 0.0912 0.92 0.35789
## D2_5 0.2249 0.0380 5.92 8.5e-09 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.713 on 306 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.381, Adjusted R-squared: 0.357
## F-statistic: 15.7 on 12 and 306 DF, p-value: <2e-16
zmiany a sytuacja w firmie
summary(lm(A6_1~zmiany+adaptacja+wielkosc+branza+warszafka+inne_firmy+indyw_kons+global+D2_5,data))
##
## Call:
## lm(formula = A6_1 ~ zmiany + adaptacja + wielkosc + branza +
## warszafka + inne_firmy + indyw_kons + global + D2_5, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.8737 -0.4785 -0.0182 0.6738 2.0324
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.3307 0.3248 10.25 <2e-16 ***
## zmiany 0.1652 0.0824 2.01 0.046 *
## adaptacja 0.0309 0.0851 0.36 0.717
## wielkosc10-49 osób 0.1343 0.1375 0.98 0.329
## wielkosc50 i więcej osób 0.0146 0.1457 0.10 0.920
## branzahandel -0.2030 0.1690 -1.20 0.231
## branzausługi 0.1315 0.1416 0.93 0.354
## branzaadm,edu,samo -0.1858 0.1835 -1.01 0.312
## warszafkaTRUE -0.2594 0.1176 -2.21 0.028 *
## inne_firmyTRUE -0.0180 0.1721 -0.10 0.917
## indyw_konsTRUE 0.1052 0.1317 0.80 0.425
## globalTRUE 0.1705 0.1227 1.39 0.166
## D2_5 -0.0192 0.0549 -0.35 0.727
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.951 on 296 degrees of freedom
## (12 observations deleted due to missingness)
## Multiple R-squared: 0.0703, Adjusted R-squared: 0.0326
## F-statistic: 1.87 on 12 and 296 DF, p-value: 0.0382
summary(lm(A6_2~zmiany+adaptacja+wielkosc+branza+warszafka+inne_firmy+indyw_kons+global+D2_5,data))
##
## Call:
## lm(formula = A6_2 ~ zmiany + adaptacja + wielkosc + branza +
## warszafka + inne_firmy + indyw_kons + global + D2_5, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.866 -0.575 0.133 0.517 1.755
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.87658 0.30104 12.88 <2e-16 ***
## zmiany 0.05718 0.07658 0.75 0.4558
## adaptacja 0.21025 0.07909 2.66 0.0083 **
## wielkosc10-49 osób -0.07140 0.12838 -0.56 0.5785
## wielkosc50 i więcej osób 0.02423 0.13570 0.18 0.8584
## branzahandel -0.12685 0.15788 -0.80 0.4224
## branzausługi 0.09374 0.13214 0.71 0.4786
## branzaadm,edu,samo -0.14238 0.16819 -0.85 0.3979
## warszafkaTRUE -0.17287 0.10885 -1.59 0.1133
## inne_firmyTRUE 0.17181 0.15812 1.09 0.2781
## indyw_konsTRUE -0.00956 0.12385 -0.08 0.9385
## globalTRUE 0.00106 0.11511 0.01 0.9927
## D2_5 -0.07048 0.05072 -1.39 0.1657
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.893 on 303 degrees of freedom
## (5 observations deleted due to missingness)
## Multiple R-squared: 0.0718, Adjusted R-squared: 0.035
## F-statistic: 1.95 on 12 and 303 DF, p-value: 0.0283
summary(lm(A6_3~zmiany+adaptacja+wielkosc+branza+warszafka+inne_firmy+indyw_kons+global+D2_5,data))
##
## Call:
## lm(formula = A6_3 ~ zmiany + adaptacja + wielkosc + branza +
## warszafka + inne_firmy + indyw_kons + global + D2_5, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.6612 -0.4750 0.0031 0.5789 1.6671
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.03708 0.26785 15.07 < 2e-16 ***
## zmiany 0.03781 0.06829 0.55 0.58017
## adaptacja 0.26828 0.06977 3.85 0.00015 ***
## wielkosc10-49 osób 0.10936 0.11428 0.96 0.33937
## wielkosc50 i więcej osób 0.06630 0.12058 0.55 0.58286
## branzahandel 0.03512 0.14022 0.25 0.80241
## branzausługi 0.11201 0.11742 0.95 0.34091
## branzaadm,edu,samo 0.03284 0.14891 0.22 0.82563
## warszafkaTRUE -0.13551 0.09690 -1.40 0.16300
## inne_firmyTRUE -0.06251 0.14231 -0.44 0.66081
## indyw_konsTRUE -0.06382 0.10951 -0.58 0.56049
## globalTRUE -0.15834 0.10206 -1.55 0.12184
## D2_5 0.00455 0.04559 0.10 0.92049
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.793 on 303 degrees of freedom
## (5 observations deleted due to missingness)
## Multiple R-squared: 0.121, Adjusted R-squared: 0.0858
## F-statistic: 3.46 on 12 and 303 DF, p-value: 8.4e-05
wszystkie zmienne a sytuacja w firmie
summary(lm(A6_1~istotne_irt+reakcja_irt+adaptacja+zmiany+informacja+kompetencje+samorzad_irt+D2_5+postawa,data))
##
## Call:
## lm(formula = A6_1 ~ istotne_irt + reakcja_irt + adaptacja + zmiany +
## informacja + kompetencje + samorzad_irt + D2_5 + postawa,
## data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.5662 -0.4923 -0.0691 0.6568 2.0921
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.4072 0.2244 15.18 <2e-16 ***
## istotne_irt -0.0701 0.0802 -0.87 0.38
## reakcja_irt -0.0838 0.0783 -1.07 0.29
## adaptacja 0.0345 0.0865 0.40 0.69
## zmiany 0.1767 0.0856 2.06 0.04 *
## informacja 0.0307 0.0848 0.36 0.72
## kompetencje 0.0794 0.0665 1.19 0.23
## samorzad_irt 0.1066 0.0811 1.31 0.19
## D2_5 -0.0149 0.0573 -0.26 0.79
## postawareal -0.1406 0.1360 -1.03 0.30
## postawakonserw -0.1136 0.1364 -0.83 0.41
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.95 on 295 degrees of freedom
## (15 observations deleted due to missingness)
## Multiple R-squared: 0.0578, Adjusted R-squared: 0.0258
## F-statistic: 1.81 on 10 and 295 DF, p-value: 0.0587
summary(lm(A6_2~istotne_irt+reakcja_irt+adaptacja+zmiany+informacja+kompetencje+samorzad_irt+D2_5+postawa,data))
##
## Call:
## lm(formula = A6_2 ~ istotne_irt + reakcja_irt + adaptacja + zmiany +
## informacja + kompetencje + samorzad_irt + D2_5 + postawa,
## data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.104 -0.573 0.165 0.506 1.738
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.9671 0.2070 19.17 <2e-16 ***
## istotne_irt 0.0461 0.0743 0.62 0.535
## reakcja_irt 0.0322 0.0727 0.44 0.658
## adaptacja 0.1718 0.0799 2.15 0.032 *
## zmiany 0.0602 0.0790 0.76 0.446
## informacja 0.0435 0.0782 0.56 0.578
## kompetencje 0.0592 0.0608 0.97 0.331
## samorzad_irt 0.0351 0.0742 0.47 0.636
## D2_5 -0.1125 0.0526 -2.14 0.033 *
## postawareal 0.1129 0.1269 0.89 0.374
## postawakonserw 0.0871 0.1251 0.70 0.487
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.887 on 302 degrees of freedom
## (8 observations deleted due to missingness)
## Multiple R-squared: 0.0677, Adjusted R-squared: 0.0368
## F-statistic: 2.19 on 10 and 302 DF, p-value: 0.0182
summary(lm(A6_3~istotne_irt+reakcja_irt+adaptacja+zmiany+informacja+kompetencje+samorzad_irt+D2_5+postawa,data))
##
## Call:
## lm(formula = A6_3 ~ istotne_irt + reakcja_irt + adaptacja + zmiany +
## informacja + kompetencje + samorzad_irt + D2_5 + postawa,
## data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.8541 -0.4316 0.0069 0.5105 1.4738
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.0235 0.1818 22.13 < 2e-16 ***
## istotne_irt -0.0228 0.0649 -0.35 0.72584
## reakcja_irt 0.0584 0.0637 0.92 0.36057
## adaptacja 0.2516 0.0692 3.63 0.00033 ***
## zmiany 0.0609 0.0693 0.88 0.38040
## informacja -0.1113 0.0681 -1.64 0.10303
## kompetencje 0.1565 0.0528 2.96 0.00329 **
## samorzad_irt 0.1130 0.0644 1.75 0.08027 .
## D2_5 -0.0205 0.0462 -0.44 0.65744
## postawareal -0.1115 0.1101 -1.01 0.31215
## postawakonserw -0.0649 0.1094 -0.59 0.55299
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.775 on 303 degrees of freedom
## (7 observations deleted due to missingness)
## Multiple R-squared: 0.151, Adjusted R-squared: 0.123
## F-statistic: 5.38 on 10 and 303 DF, p-value: 2.53e-07
summary(lm(A6_2+A6_3~istotne_irt+reakcja_irt+adaptacja+zmiany+informacja+kompetencje+samorzad_irt+D2_5+postawa,data))
##
## Call:
## lm(formula = A6_2 + A6_3 ~ istotne_irt + reakcja_irt + adaptacja +
## zmiany + informacja + kompetencje + samorzad_irt + D2_5 +
## postawa, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.952 -0.855 0.099 0.954 3.059
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 7.9815 0.3336 23.93 < 2e-16 ***
## istotne_irt 0.0251 0.1191 0.21 0.83333
## reakcja_irt 0.0925 0.1171 0.79 0.43041
## adaptacja 0.4375 0.1281 3.41 0.00073 ***
## zmiany 0.1041 0.1272 0.82 0.41390
## informacja -0.0519 0.1256 -0.41 0.67994
## kompetencje 0.2116 0.0974 2.17 0.03061 *
## samorzad_irt 0.1354 0.1190 1.14 0.25607
## D2_5 -0.1310 0.0848 -1.54 0.12348
## postawareal 0.0239 0.2033 0.12 0.90667
## postawakonserw 0.0226 0.2011 0.11 0.91048
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.42 on 300 degrees of freedom
## (10 observations deleted due to missingness)
## Multiple R-squared: 0.123, Adjusted R-squared: 0.094
## F-statistic: 4.22 on 10 and 300 DF, p-value: 1.72e-05
współpraca z samorządem
summary(lm(samorzad_irt~istotne_irt+reakcja_irt+adaptacja+zmiany+informacja+kompetencje+D2_5+postawa,data))
##
## Call:
## lm(formula = samorzad_irt ~ istotne_irt + reakcja_irt + adaptacja +
## zmiany + informacja + kompetencje + D2_5 + postawa, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.296 -0.541 -0.182 0.518 1.923
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.1628 0.1604 1.02 0.311
## istotne_irt -0.0501 0.0576 -0.87 0.385
## reakcja_irt -0.1016 0.0561 -1.81 0.071 .
## adaptacja 0.0840 0.0613 1.37 0.172
## zmiany -0.0148 0.0612 -0.24 0.809
## informacja 0.2505 0.0587 4.27 2.6e-05 ***
## kompetencje 0.0327 0.0469 0.70 0.486
## D2_5 0.0111 0.0408 0.27 0.786
## postawareal -0.1555 0.0975 -1.60 0.112
## postawakonserw 0.0503 0.0968 0.52 0.604
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.689 on 306 degrees of freedom
## (5 observations deleted due to missingness)
## Multiple R-squared: 0.116, Adjusted R-squared: 0.0895
## F-statistic: 4.44 on 9 and 306 DF, p-value: 1.75e-05
summary(lm(samorzad_irt~wielkosc+branza+warszafka+inne_firmy+indyw_kons+global+D2_5,data))
##
## Call:
## lm(formula = samorzad_irt ~ wielkosc + branza + warszafka + inne_firmy +
## indyw_kons + global + D2_5, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.5720 -0.3791 -0.0884 0.3897 1.8953
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.0971 0.1709 -0.57 0.570
## wielkosc10-49 osób 0.0281 0.0813 0.35 0.729
## wielkosc50 i więcej osób 0.4888 0.0843 5.80 1.6e-08 ***
## branzahandel -0.2508 0.1004 -2.50 0.013 *
## branzausługi -0.0794 0.0848 -0.94 0.350
## branzaadm,edu,samo 0.5666 0.1071 5.29 2.3e-07 ***
## warszafkaTRUE -0.1585 0.0697 -2.27 0.024 *
## inne_firmyTRUE -0.0582 0.1007 -0.58 0.564
## indyw_konsTRUE 0.0668 0.0790 0.85 0.399
## globalTRUE -0.1013 0.0733 -1.38 0.168
## D2_5 0.0533 0.0275 1.94 0.053 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.576 on 308 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.382, Adjusted R-squared: 0.362
## F-statistic: 19.1 on 10 and 308 DF, p-value: <2e-16
summary(lm(samorzad_irt~wielkosc+branza+warszafka+inne_firmy+indyw_kons+global+D2_5+istotne_irt+reakcja_irt+adaptacja+zmiany+informacja+kompetencje+D2_5+postawa,data))
##
## Call:
## lm(formula = samorzad_irt ~ wielkosc + branza + warszafka + inne_firmy +
## indyw_kons + global + D2_5 + istotne_irt + reakcja_irt +
## adaptacja + zmiany + informacja + kompetencje + D2_5 + postawa,
## data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.5384 -0.3920 -0.0554 0.4079 1.6279
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.1067 0.2002 0.53 0.5944
## wielkosc10-49 osób -0.0169 0.0824 -0.21 0.8372
## wielkosc50 i więcej osób 0.3863 0.0872 4.43 1.3e-05 ***
## branzahandel -0.2701 0.1006 -2.69 0.0076 **
## branzausługi -0.1089 0.0853 -1.28 0.2026
## branzaadm,edu,samo 0.5444 0.1083 5.03 8.6e-07 ***
## warszafkaTRUE -0.1671 0.0691 -2.42 0.0162 *
## inne_firmyTRUE -0.0802 0.1020 -0.79 0.4322
## indyw_konsTRUE 0.0635 0.0785 0.81 0.4192
## globalTRUE -0.1081 0.0747 -1.45 0.1490
## D2_5 0.0147 0.0339 0.43 0.6657
## istotne_irt -0.0427 0.0479 -0.89 0.3729
## reakcja_irt -0.0428 0.0470 -0.91 0.3625
## adaptacja 0.0697 0.0532 1.31 0.1913
## zmiany 0.0619 0.0519 1.19 0.2339
## informacja 0.1366 0.0499 2.74 0.0065 **
## kompetencje -0.0104 0.0402 -0.26 0.7952
## postawareal -0.0321 0.0813 -0.39 0.6934
## postawakonserw 0.1303 0.0801 1.63 0.1045
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.565 on 297 degrees of freedom
## (5 observations deleted due to missingness)
## Multiple R-squared: 0.423, Adjusted R-squared: 0.388
## F-statistic: 12.1 on 18 and 297 DF, p-value: <2e-16
Rola informacji
with(data,sobel(informacja,zmiany,A6_2))
## $`Mod1: Y~X`
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.6447 0.05033 72.416 7.794e-199
## pred 0.1571 0.05621 2.795 5.500e-03
##
## $`Mod2: Y~X+M`
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.64426 0.05028 72.481 1.569e-198
## pred 0.11175 0.06626 1.687 9.265e-02
## med 0.08601 0.06665 1.290 1.979e-01
##
## $`Mod3: M~X`
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.005602 0.04243 0.132 8.951e-01
## pred 0.527634 0.04739 11.134 1.641e-24
##
## $Indirect.Effect
## [1] 0.04538
##
## $SE
## [1] 0.0354
##
## $z.value
## [1] 1.282
##
## $N
## [1] 318
modelfirm<-"
SAT=~A6_2+A6_3
ADAPT=~zmiany+adaptacja
SAT~informacja+ADAPT
ADAPT~informacja
"
seall<-sem(modelfirm,data)
summary(seall,rsquare=T)
## lavaan (0.5-17) converged normally after 30 iterations
##
## Used Total
## Number of observations 315 321
##
## Estimator ML
## Minimum Function Test Statistic 8.181
## Degrees of freedom 3
## P-value (Chi-square) 0.042
##
## Parameter estimates:
##
## Information Expected
## Standard Errors Standard
##
## Estimate Std.err Z-value P(>|z|)
## Latent variables:
## SAT =~
## A6_2 1.000
## A6_3 1.582 0.422 3.748 0.000
## ADAPT =~
## zmiany 1.000
## adaptacja 1.076 0.094 11.459 0.000
##
## Regressions:
## SAT ~
## informacja -0.101 0.055 -1.823 0.068
## ADAPT 0.371 0.119 3.105 0.002
## ADAPT ~
## informacja 0.510 0.047 10.808 0.000
##
## Variances:
## A6_2 0.583 0.075
## A6_3 0.100 0.147
## zmiany 0.341 0.042
## adaptacja 0.269 0.042
## SAT 0.192 0.056
## ADAPT 0.246 0.040
##
## R-Square:
##
## A6_2 0.285
## A6_3 0.853
## zmiany 0.571
## adaptacja 0.661
## SAT 0.172
## ADAPT 0.458
fitMeasures(seall, c("cfi", "rmsea"))
## cfi rmsea
## 0.987 0.074
semPaths(seall,what="stand",layout="tree2",posCol="darkblue",style="lisrel")
jpeg("model_sem2.jpeg",width=3000,height=3000,quality=100,res=400)
semPaths(seall,what="stand",layout="tree2",posCol="darkblue",style="lisrel")
dev.off()
## pdf
## 2
modelfirm<-"
ADAPT=~zmiany+adaptacja
ADAPT~istotne_irt+reakcja_irt+informacja
istotne_irt~informacja
reakcja_irt~informacja+istotne_irt
"
seall<-sem(modelfirm,data)
summary(seall,rsquare=T)
## lavaan (0.5-17) converged normally after 19 iterations
##
## Number of observations 321
##
## Estimator ML
## Minimum Function Test Statistic 4.852
## Degrees of freedom 2
## P-value (Chi-square) 0.088
##
## Parameter estimates:
##
## Information Expected
## Standard Errors Standard
##
## Estimate Std.err Z-value P(>|z|)
## Latent variables:
## ADAPT =~
## zmiany 1.000
## adaptacja 0.977 0.083 11.826 0.000
##
## Regressions:
## ADAPT ~
## istotne_irt 0.164 0.050 3.277 0.001
## reakcja_irt 0.170 0.048 3.536 0.000
## informacja 0.397 0.049 8.110 0.000
## istotne_irt ~
## informacja 0.547 0.046 11.958 0.000
## reakcja_irt ~
## informacja 0.104 0.054 1.911 0.056
## istotne_irt 0.347 0.055 6.306 0.000
##
## Variances:
## zmiany 0.288 0.040
## adaptacja 0.326 0.041
## istotne_irt 0.542 0.043
## reakcja_irt 0.527 0.042
## ADAPT 0.226 0.038
##
## R-Square:
##
## zmiany 0.634
## adaptacja 0.594
## istotne_irt 0.308
## reakcja_irt 0.204
## ADAPT 0.548
fitMeasures(seall, c("cfi", "rmsea"))
## cfi rmsea
## 0.994 0.067
semPaths(seall,what="stand",layout="tree2",posCol="darkblue",style="lisrel")
jpeg("model_sem1.jpeg",width=3000,height=3000,quality=100,res=400)
semPaths(seall,what="stand",layout="tree2",posCol="darkblue",style="lisrel")
dev.off()
## pdf
## 2
summary(lm(informacja~samorzad_irt,data))
##
## Call:
## lm(formula = informacja ~ samorzad_irt, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.144 -0.543 -0.021 0.520 3.288
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.0508 0.0497 -1.02 0.31
## samorzad_irt 0.3482 0.0672 5.18 3.9e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.865 on 319 degrees of freedom
## Multiple R-squared: 0.0776, Adjusted R-squared: 0.0747
## F-statistic: 26.8 on 1 and 319 DF, p-value: 3.91e-07
rola postaw
summary(lm(A6_3~istotne_irt*postawa+reakcja_irt*postawa+adaptacja*postawa+zmiany*postawa+informacja+kompetencje+samorzad_irt,data))
##
## Call:
## lm(formula = A6_3 ~ istotne_irt * postawa + reakcja_irt * postawa +
## adaptacja * postawa + zmiany * postawa + informacja + kompetencje +
## samorzad_irt, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.8968 -0.5150 0.0704 0.5079 1.5722
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.9477 0.0728 54.23 < 2e-16 ***
## istotne_irt -0.0341 0.0984 -0.35 0.72918
## postawareal -0.1754 0.1162 -1.51 0.13230
## postawakonserw -0.0913 0.1122 -0.81 0.41651
## reakcja_irt 0.1086 0.0953 1.14 0.25550
## adaptacja 0.3803 0.1082 3.51 0.00051 ***
## zmiany -0.0968 0.1028 -0.94 0.34669
## informacja -0.1023 0.0689 -1.49 0.13837
## kompetencje 0.1510 0.0519 2.91 0.00390 **
## samorzad_irt 0.1005 0.0643 1.56 0.11928
## istotne_irt:postawareal 0.0114 0.1477 0.08 0.93871
## istotne_irt:postawakonserw -0.0126 0.1463 -0.09 0.93144
## postawareal:reakcja_irt -0.0365 0.1506 -0.24 0.80864
## postawakonserw:reakcja_irt -0.1235 0.1506 -0.82 0.41317
## postawareal:adaptacja -0.0980 0.1646 -0.60 0.55200
## postawakonserw:adaptacja -0.3216 0.1542 -2.09 0.03792 *
## postawareal:zmiany 0.3285 0.1806 1.82 0.06986 .
## postawakonserw:zmiany 0.2579 0.1532 1.68 0.09332 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.768 on 298 degrees of freedom
## (5 observations deleted due to missingness)
## Multiple R-squared: 0.178, Adjusted R-squared: 0.132
## F-statistic: 3.81 on 17 and 298 DF, p-value: 1.04e-06
summary(lm(A6_3~adaptacja*postawa+zmiany*postawa,data))
##
## Call:
## lm(formula = A6_3 ~ adaptacja * postawa + zmiany * postawa, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.7209 -0.5419 0.0838 0.5014 1.4637
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.9750 0.0707 56.25 < 2e-16 ***
## adaptacja 0.4193 0.1021 4.11 5.1e-05 ***
## postawareal -0.2166 0.1140 -1.90 0.058 .
## postawakonserw -0.0845 0.1115 -0.76 0.449
## zmiany -0.1045 0.0947 -1.10 0.271
## adaptacja:postawareal -0.1312 0.1550 -0.85 0.398
## adaptacja:postawakonserw -0.3508 0.1476 -2.38 0.018 *
## postawareal:zmiany 0.3606 0.1724 2.09 0.037 *
## postawakonserw:zmiany 0.2322 0.1432 1.62 0.106
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.776 on 307 degrees of freedom
## (5 observations deleted due to missingness)
## Multiple R-squared: 0.137, Adjusted R-squared: 0.114
## F-statistic: 6.09 on 8 and 307 DF, p-value: 2.78e-07
summary(lm(A6_3~zmiany*postawa,data))
##
## Call:
## lm(formula = A6_3 ~ zmiany * postawa, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.7746 -0.5992 0.0291 0.5196 1.3944
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.0074 0.0725 55.27 <2e-16 ***
## zmiany 0.1316 0.0777 1.69 0.091 .
## postawareal -0.2323 0.1172 -1.98 0.048 *
## postawakonserw -0.1273 0.1136 -1.12 0.263
## zmiany:postawareal 0.3212 0.1463 2.20 0.029 *
## zmiany:postawakonserw 0.0345 0.1206 0.29 0.775
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.801 on 310 degrees of freedom
## (5 observations deleted due to missingness)
## Multiple R-squared: 0.0712, Adjusted R-squared: 0.0562
## F-statistic: 4.75 on 5 and 310 DF, p-value: 0.000337
summary(lm(A6_3~adaptacja*postawa,data))
##
## Call:
## lm(formula = A6_3 ~ adaptacja * postawa, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.687 -0.547 0.079 0.493 1.422
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.9682 0.0707 56.12 < 2e-16 ***
## adaptacja 0.3509 0.0815 4.31 2.2e-05 ***
## postawareal -0.1687 0.1120 -1.51 0.13
## postawakonserw -0.1022 0.1099 -0.93 0.35
## adaptacja:postawareal 0.0517 0.1272 0.41 0.68
## adaptacja:postawakonserw -0.2120 0.1207 -1.76 0.08 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.779 on 310 degrees of freedom
## (5 observations deleted due to missingness)
## Multiple R-squared: 0.121, Adjusted R-squared: 0.106
## F-statistic: 8.51 on 5 and 310 DF, p-value: 1.46e-07
ggplot(data,aes(x=zmiany,y=A6_3,colour=postawa))+geom_point()+geom_smooth(method="lm",se=F)
## Warning: Removed 2 rows containing missing values (stat_smooth).
## Warning: Removed 1 rows containing missing values (stat_smooth).
## Warning: Removed 3 rows containing missing values (geom_point).
summary(lm(zmiany~postawa*istotne_irt,data))
##
## Call:
## lm(formula = zmiany ~ postawa * istotne_irt, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.9599 -0.5119 -0.0011 0.4550 2.2846
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.1865 0.0671 2.78 0.0058 **
## postawareal 0.0455 0.1069 0.43 0.6705
## postawakonserw -0.4856 0.1018 -4.77 2.8e-06 ***
## istotne_irt 0.5178 0.0739 7.01 1.5e-11 ***
## postawareal:istotne_irt -0.3410 0.1159 -2.94 0.0035 **
## postawakonserw:istotne_irt -0.0332 0.1187 -0.28 0.7797
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.757 on 312 degrees of freedom
## (3 observations deleted due to missingness)
## Multiple R-squared: 0.289, Adjusted R-squared: 0.278
## F-statistic: 25.4 on 5 and 312 DF, p-value: <2e-16
ggplot(data,aes(x=istotne_irt,y=zmiany,colour=postawa))+geom_point()+geom_smooth(method="lm",se=F)
summary(lm(A6_3~adaptacja*zmiany,data))
##
## Call:
## lm(formula = A6_3 ~ adaptacja * zmiany, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.5368 -0.3361 -0.0022 0.6567 1.6452
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.9588 0.0496 79.79 < 2e-16 ***
## adaptacja 0.2631 0.0625 4.21 3.4e-05 ***
## zmiany 0.0436 0.0634 0.69 0.49
## adaptacja:zmiany -0.0663 0.0466 -1.42 0.16
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.786 on 314 degrees of freedom
## (3 observations deleted due to missingness)
## Multiple R-squared: 0.105, Adjusted R-squared: 0.0964
## F-statistic: 12.3 on 3 and 314 DF, p-value: 1.3e-07