Team : R is well
2015.06.09
총 매출에 오프라인,웹,모바일 판매 비중 분석.
adimem<-read.csv("adimemall.csv")
std.fitdum <- lm(scale(sales) ~ scale(age) + scale(web) + scale(offline) + scale(mobile) + scale(visit) + scale(quantity) + gender + grade , data=adimem)
summary(std.fitdum)
Call:
lm(formula = scale(sales) ~ scale(age) + scale(web) + scale(offline) +
scale(mobile) + scale(visit) + scale(quantity) + gender +
grade, data = adimem)
Residuals:
Min 1Q Median 3Q Max
-4.659e-14 -7.800e-17 -3.000e-17 2.200e-17 9.755e-14
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.190e-15 8.920e-17 2.455e+01 < 2e-16 ***
scale(age) -2.136e-16 5.857e-17 -3.647e+00 0.000272 ***
scale(web) 5.204e-01 9.042e-17 5.756e+15 < 2e-16 ***
scale(offline) 8.333e-01 1.253e-16 6.651e+15 < 2e-16 ***
scale(mobile) 3.741e-01 7.647e-17 4.891e+15 < 2e-16 ***
scale(visit) 1.720e-17 1.153e-16 1.490e-01 0.881425
scale(quantity) -5.885e-17 1.344e-16 -4.380e-01 0.661497
genderM -4.373e-17 1.170e-16 -3.740e-01 0.708616
gradeGOLD -4.397e-17 5.815e-16 -7.600e-02 0.939733
gradeSILVER 5.778e-17 2.166e-16 2.670e-01 0.789653
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2.589e-15 on 1989 degrees of freedom
Multiple R-squared: 1, Adjusted R-squared: 1
F-statistic: 3.311e+31 on 9 and 1989 DF, p-value: < 2.2e-16
fit_dum <- lm(sales ~ age + gender + grade + visit + quantity , data=adimem)
summary(fit_dum)
Call:
lm(formula = sales ~ age + gender + grade + visit + quantity,
data = adimem)
Residuals:
Min 1Q Median 3Q Max
-2196024 -41973 -14153 30194 1524699
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 15081.71 9760.24 1.545 0.122
age 12.94 264.05 0.049 0.961
genderM -1848.49 5306.66 -0.348 0.728
gradeGOLD 468591.61 24400.07 19.205 <2e-16 ***
gradeSILVER 91901.07 9635.05 9.538 <2e-16 ***
visit 34075.36 2494.97 13.658 <2e-16 ***
quantity 31193.83 1021.16 30.547 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 118400 on 1992 degrees of freedom
Multiple R-squared: 0.8397, Adjusted R-squared: 0.8393
F-statistic: 1740 on 6 and 1992 DF, p-value: < 2.2e-16
성별 95% 신뢰수준에서 유의미한 차이가 있다고 말할 수 없음.
adimem<-read.csv("adimemall.csv")
library(ez)
gender<-ezANOVA(data=adimem, dv=sales, wid=id, between=gender, detailed = T, return_aov = T)
print(gender)
$ANOVA
Effect DFn DFd SSn SSd F p p<.05
1 gender 1 1997 105153922483 1.740776e+14 1.206314 0.2721957
ges
1 0.0006036987
$`Levene's Test for Homogeneity of Variance`
DFn DFd SSn SSd F p p<.05
1 1 1997 172358765679 1.565763e+14 2.198293 0.1383215
$aov
Call:
aov(formula = formula(aov_formula), data = data)
Terms:
gender Residuals
Sum of Squares 1.051539e+11 1.740776e+14
Deg. of Freedom 1 1997
Residual standard error: 295244.9
Estimated effects may be unbalanced
등급간 95% 신뢰수준에서 유의미한 차이가 있다고 말할 수 있음.
grade<-ezANOVA(data=adimem, dv=sales, wid=id, between=grade, detailed = T, return_aov = T)
print(grade)
$ANOVA
Effect DFn DFd SSn SSd F p p<.05 ges
1 grade 2 1996 1.007296e+14 7.345318e+13 1368.602 0 * 0.5782983
$`Levene's Test for Homogeneity of Variance`
DFn DFd SSn SSd F p p<.05
1 2 1996 2.667455e+13 2.879147e+13 924.621 6.403002e-285 *
$aov
Call:
aov(formula = formula(aov_formula), data = data)
Terms:
grade Residuals
Sum of Squares 1.007296e+14 7.345318e+13
Deg. of Freedom 2 1996
Residual standard error: 191833.8
Estimated effects may be unbalanced
TukeyHSD(grade$aov)
Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = formula(aov_formula), data = data)
$grade
diff lwr upr p adj
GOLD-BRONZE 1397559.3 1328872.0 1466246.5 0
SILVER-BRONZE 326311.4 294362.7 358260.0 0
SILVER-GOLD -1071247.9 -1145441.9 -997053.9 0
등급간 95% 신뢰수준에서 유의미한 차이가 있다고 말할 수 있음.
agerange<-ezANOVA(data=adimem, dv=sales, wid=id, between=agerange, detailed = T, return_aov = T)
print(agerange)
$ANOVA
Effect DFn DFd SSn SSd F p p<.05
1 agerange 5 1993 3.120015e+12 1.710628e+14 7.270067 9.282381e-07 *
ges
1 0.0179123
$`Levene's Test for Homogeneity of Variance`
DFn DFd SSn SSd F p p<.05
1 5 1993 2.564092e+12 1.525197e+14 6.701082 3.353963e-06 *
$aov
Call:
aov(formula = formula(aov_formula), data = data)
Terms:
agerange Residuals
Sum of Squares 3.120015e+12 1.710628e+14
Deg. of Freedom 5 1993
Residual standard error: 292970.7
Estimated effects may be unbalanced
TukeyHSD(agerange$aov)
Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = formula(aov_formula), data = data)
$agerange
diff lwr upr p adj
20th-10th less 45690.5508 -47968.623 139349.72 0.7322175
30th-10th less 118246.7032 24215.442 212277.96 0.0046127
40th-10th less 120061.5585 20823.807 219299.31 0.0075140
50th-10th less 118324.7256 -7669.106 244318.56 0.0799251
60th over-10th less 61872.9676 -159324.957 283070.89 0.9679237
30th-20th 72556.1524 28739.891 116372.41 0.0000365
40th-20th 74371.0078 20277.403 128464.61 0.0012745
50th-20th 72634.1748 -21983.119 167251.47 0.2428925
60th over-20th 16182.4168 -188772.477 221137.31 0.9999210
40th-30th 1814.8554 -52920.465 56550.18 0.9999989
50th-30th 78.0224 -94907.606 95063.65 1.0000000
60th over-30th -56373.7355 -261498.931 148751.46 0.9702848
50th-40th -1736.8330 -101879.346 98405.68 1.0000000
60th over-40th -58188.5909 -265752.073 149374.89 0.9676136
60th over-50th -56451.7579 -278057.068 165153.55 0.9787053
gender_grade<-ezANOVA(data=adimem, dv=sales, wid=id, between=.(gender,grade), detailed = T, return_aov = T, type=3)
print(gender_grade)
$ANOVA
Effect DFn DFd SSn SSd F p
1 (Intercept) 1 1993 1.587171e+14 7.084507e+13 4464.99874 0.000000e+00
2 gender 1 1993 2.503342e+12 7.084507e+13 70.42354 8.939466e-17
3 grade 2 1993 1.025298e+14 7.084507e+13 1442.17417 0.000000e+00
4 gender:grade 2 1993 2.492903e+12 7.084507e+13 35.06493 1.079694e-15
p<.05 ges
1 * 0.69139046
2 * 0.03412947
3 * 0.59137633
4 * 0.03399198
$`Levene's Test for Homogeneity of Variance`
DFn DFd SSn SSd F p p<.05
1 5 1993 2.505882e+13 2.749028e+13 363.3447 3.103997e-277 *
$aov
Call:
aov(formula = formula(aov_formula), data = data)
Terms:
gender grade gender:grade Residuals
Sum of Squares 1.051539e+11 1.007397e+14 2.492903e+12 7.084507e+13
Deg. of Freedom 1 2 2 1993
Residual standard error: 188539
Estimated effects may be unbalanced
TukeyHSD(gender_grade$aov)
Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = formula(aov_formula), data = data)
$gender
diff lwr upr p adj
M-F -14515.3 -31066.39 2035.781 0.0855998
$grade
diff lwr upr p adj
GOLD-BRONZE 1397929.8 1330422.1 1465437.4 0
SILVER-BRONZE 326022.1 294622.1 357422.1 0
SILVER-GOLD -1071907.7 -1144827.5 -998987.9 0
$`gender:grade`
diff lwr upr p adj
M:BRONZE-F:BRONZE 3634.792 -22238.48 29508.07 0.9986737
F:GOLD-F:BRONZE 1649632.847 1527937.52 1771328.17 0.0000000
M:GOLD-F:BRONZE 1190962.681 1079609.78 1302315.59 0.0000000
F:SILVER-F:BRONZE 365244.258 311110.15 419378.36 0.0000000
M:SILVER-F:BRONZE 291158.186 237024.08 345292.29 0.0000000
F:GOLD-M:BRONZE 1645998.056 1524412.41 1767583.70 0.0000000
M:GOLD-M:BRONZE 1187327.889 1076094.87 1298560.91 0.0000000
F:SILVER-M:BRONZE 361609.466 307722.39 415496.54 0.0000000
M:SILVER-M:BRONZE 287523.395 233636.32 341410.47 0.0000000
M:GOLD-F:GOLD -458670.167 -621498.64 -295841.69 0.0000000
F:SILVER-F:GOLD -1284388.589 -1414941.81 -1153835.37 0.0000000
M:SILVER-F:GOLD -1358474.661 -1489027.88 -1227921.44 0.0000000
F:SILVER-M:GOLD -825718.423 -946688.92 -704747.93 0.0000000
M:SILVER-M:GOLD -899804.494 -1020774.99 -778834.00 0.0000000
M:SILVER-F:SILVER -74086.071 -145953.25 -2218.89 0.0388543
gender_agerange<-ezANOVA(data=adimem, dv=sales, wid=id, between=.(gender,agerange), detailed = T, return_aov = T, type=3)
print(gender_agerange)
$ANOVA
Effect DFn DFd SSn SSd F
1 (Intercept) 1 1987 1.243843e+13 1.707268e+14 144.7644079
2 gender 1 1987 2.031496e+10 1.707268e+14 0.2364352
3 agerange 5 1987 3.087306e+12 1.707268e+14 7.1863077
4 gender:agerange 5 1987 2.147804e+11 1.707268e+14 0.4999433
p p<.05 ges
1 3.097826e-32 * 0.0679082582
2 6.268464e-01 0.0001189769
3 1.122396e-06 * 0.0177621130
4 7.764905e-01 0.0012564548
$`Levene's Test for Homogeneity of Variance`
DFn DFd SSn SSd F p p<.05
1 11 1987 3.013053e+12 1.523333e+14 3.572869 5.285201e-05 *
$aov
Call:
aov(formula = formula(aov_formula), data = data)
Terms:
gender agerange gender:agerange Residuals
Sum of Squares 1.051539e+11 3.136075e+12 2.147804e+11 1.707268e+14
Deg. of Freedom 1 5 5 1987
Residual standard error: 293124.4
Estimated effects may be unbalanced
TukeyHSD(gender_agerange$aov)
Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = formula(aov_formula), data = data)
$gender
diff lwr upr p adj
M-F -14515.3 -40247.57 11216.96 0.2687439
$agerange
diff lwr upr p adj
20th-10th less 47874.0568 -45834.530 141582.64 0.6916123
30th-10th less 120972.3592 26891.489 215053.23 0.0034197
40th-10th less 120796.6467 21506.539 220086.75 0.0070204
50th-10th less 119119.5710 -6940.732 245179.87 0.0765504
60th over-10th less 65720.0506 -155594.573 287034.67 0.9585622
30th-20th 73098.3024 29258.924 116937.68 0.0000311
40th-20th 72922.5899 18800.446 127044.73 0.0017413
50th-20th 71245.5143 -23421.698 165912.73 0.2637287
60th over-20th 17845.9939 -187217.030 222909.02 0.9998722
40th-30th -175.7125 -54939.910 54588.49 1.0000000
50th-30th -1852.7882 -96888.528 93182.95 0.9999999
60th over-30th -55252.3086 -260485.723 149981.11 0.9728381
50th-40th -1677.0756 -101872.421 98518.27 1.0000000
60th over-40th -55076.5960 -262749.584 152596.39 0.9745652
60th over-50th -53399.5204 -275121.744 168322.70 0.9834226
$`gender:agerange`
diff lwr upr p adj
M:10th less-F:10th less 23386.578 -185846.881 232620.04 0.9999999
F:20th-F:10th less 58209.614 -80823.522 197242.75 0.9690742
M:20th-F:10th less 51476.845 -86409.310 189363.00 0.9873213
F:30th-F:10th less 145678.107 5071.338 286284.87 0.0344791
M:30th-F:10th less 113215.511 -24712.125 251143.15 0.2340034
F:40th-F:10th less 127416.717 -18768.432 273601.87 0.1594661
M:40th-F:10th less 131066.285 -19983.713 282116.28 0.1645053
F:50th-F:10th less 161747.922 -26657.857 350153.70 0.1768062
M:50th-F:10th less 82786.268 -119527.419 285099.96 0.9739612
F:60th over-F:10th less 68300.303 -344048.637 480649.24 0.9999944
M:60th over-F:10th less 72174.545 -244600.685 388949.78 0.9998579
F:20th-M:10th less 34823.036 -137397.765 207043.84 0.9999568
M:20th-M:10th less 28090.268 -143205.919 199386.45 0.9999950
F:30th-M:10th less 122291.529 -51202.145 295785.20 0.4723027
M:30th-M:10th less 89828.934 -81500.644 261158.51 0.8613007
F:40th-M:10th less 104030.140 -74014.488 282074.77 0.7519901
M:40th-M:10th less 107679.708 -74380.430 289739.85 0.7369419
F:50th-M:10th less 138361.345 -75709.973 352432.66 0.6121770
M:50th-M:10th less 59399.690 -167008.392 285807.77 0.9994436
F:60th over-M:10th less 44913.725 -379776.090 469603.54 1.0000000
M:60th over-M:10th less 48787.968 -283892.566 381468.50 0.9999984
M:20th-F:20th -6732.768 -76689.584 63224.05 1.0000000
F:30th-F:20th 87468.493 12291.187 162645.80 0.0080028
M:30th-F:20th 55005.898 -15032.641 125044.44 0.2977522
F:40th-F:20th 69207.103 -15948.413 154362.62 0.2477623
M:40th-F:20th 72856.672 -20403.536 166116.88 0.3058061
F:50th-F:20th 103538.308 -42674.214 249750.83 0.4646494
M:50th-F:20th 24576.654 -139167.635 188320.94 0.9999980
F:60th over-F:20th 10090.689 -384767.528 404948.91 1.0000000
M:60th over-F:20th 13964.932 -279680.961 307610.82 1.0000000
F:30th-M:20th 94201.261 21166.979 167235.54 0.0015248
M:30th-M:20th 61738.666 -5994.456 129471.79 0.1144201
F:40th-M:20th 75939.872 -7329.816 159209.56 0.1139496
M:40th-M:20th 79589.440 -11952.055 171130.93 0.1622563
F:50th-M:20th 110271.077 -34851.219 255393.37 0.3491523
M:50th-M:20th 31309.423 -131462.108 194080.95 0.9999739
F:60th over-M:20th 16823.458 -377632.359 411279.27 1.0000000
M:60th over-M:20th 20697.700 -272406.871 313802.27 1.0000000
M:30th-F:30th -32462.595 -105575.161 40649.97 0.9526366
F:40th-F:30th -18261.389 -105962.657 69439.88 0.9999419
M:40th-F:30th -14611.821 -110202.180 80978.54 0.9999976
F:50th-F:30th 16069.816 -131639.873 163779.50 0.9999999
M:50th-F:30th -62891.839 -227974.371 102190.69 0.9850769
F:60th over-F:30th -77377.804 -472792.854 318037.25 0.9999690
M:60th over-F:30th -73503.561 -367897.788 220890.67 0.9996535
F:40th-M:30th 14201.206 -69137.151 97539.56 0.9999925
M:40th-M:30th 17850.774 -73753.189 109454.74 0.9999703
F:50th-M:30th 48532.411 -96629.297 193694.12 0.9949629
M:50th-M:30th -30429.243 -193235.914 132377.43 0.9999806
F:60th over-M:30th -44915.208 -439385.526 349555.11 0.9999999
M:60th over-M:30th -41040.966 -334165.053 252083.12 0.9999990
M:40th-F:40th 3649.568 -99971.623 107270.76 1.0000000
F:50th-F:40th 34331.205 -118698.160 187360.57 0.9998780
M:50th-F:40th -44630.449 -214489.441 125228.54 0.9994356
F:60th over-F:40th -59116.414 -456549.298 338316.47 0.9999982
M:60th over-F:40th -55242.172 -352341.137 241856.79 0.9999816
F:50th-M:40th 30681.637 -127001.561 188364.83 0.9999707
M:50th-M:40th -48280.017 -222343.458 125783.42 0.9990607
F:60th over-M:40th -62765.982 -462013.902 336481.94 0.9999967
M:60th over-M:40th -58891.740 -358414.360 240630.88 0.9999674
M:50th-F:50th -78961.654 -286274.743 128351.43 0.9851053
F:60th over-F:50th -93447.619 -508272.325 321377.09 0.9998729
M:60th over-F:50th -89573.377 -409564.681 230417.93 0.9989771
F:60th over-M:50th -14485.965 -435809.626 406837.70 1.0000000
M:60th over-M:50th -10611.722 -338984.263 317760.82 1.0000000
M:60th over-F:60th over 3874.242 -482879.644 490628.13 1.0000000