New names:
• `Relax3` -> `Relax3...40`
• `Relax3` -> `Relax3...41`
• `Education` -> `Education...50`
• `` -> `...51`
• `Income` -> `Income...52`
• `` -> `...71`
• `Education` -> `Education...72`
• `` -> `...73`
• `` -> `...74`
• `` -> `...75`
• `Income` -> `Income...76`
• `` -> `...77`
• `` -> `...79`
• `` -> `...80`
• `` -> `...81`
• `` -> `...82`
30 31 32 33 34 35 36 37 38 40 41 42 43 45 46 47 48 49 50 51 52 53 54 55 56 57
1 2 2 1 1 2 3 5 4 3 3 9 7 3 5 8 4 8 5 7 5 2 5 2 7 9
58 59 60
7 5 20
Attaching package: 'dplyr'The following objects are masked from 'package:stats':
filter, lagThe following objects are masked from 'package:base':
intersect, setdiff, setequal, union── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
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Attaching package: 'rstatix'
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filter
Colege graduate College graduate College level
1 21 16
Elementary graduate Elementary level Ementary level
17 21 1
High chool graduate High schoo graduate High school graduate
1 1 22
High School graduate High school level High scool level
4 37 1
High sschool graduate Highschool level
1 1
15000 17000 18000 20000
132 1 2 10 [1] 15400[1] 1314.45
Extremely severe mild Mild Moderate
2 1 41 24
Normal Severe
75 2
Extremely severe mild Mild Moderate
10 1 25 52
Normal Severe
37 20
Call:
lm(formula = StTotal ~ ReappraisalMean + SocialSupportMean +
ProbSolvingMean + RelMean + TolMean + Emomean + OveracMean +
RelaxMean + Subsmean, data = Durias1)
Residuals:
Min 1Q Median 3Q Max
-12.2452 -4.1688 0.1868 3.0768 20.7605
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 7.6781 4.8332 1.589 0.1145
ReappraisalMean 0.5264 1.1958 0.440 0.6605
SocialSupportMean 1.1563 1.0585 1.092 0.2766
ProbSolvingMean -2.5310 1.3180 -1.920 0.0569 .
RelMean 0.8649 1.2815 0.675 0.5009
TolMean -0.3901 0.9907 -0.394 0.6943
Emomean 1.9311 1.3611 1.419 0.1583
OveracMean 0.8203 1.3734 0.597 0.5513
RelaxMean -1.2134 1.2422 -0.977 0.3304
Subsmean 3.9883 1.6741 2.382 0.0186 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5.868 on 135 degrees of freedom
Multiple R-squared: 0.1216, Adjusted R-squared: 0.063
F-statistic: 2.076 on 9 and 135 DF, p-value: 0.03584As shown in the above results, it shows that the model is better than a model with only the intercept because at least one coefficient β is significantly different from 0 with a p -value = 0.03584. It also shows that substance-use significantly predict stress with a p-value results of 0.0186. The coefficient of substance-use is 3.9883, this means that higher substance-use score indicates higher stress level. On, the average, a one unit increase in substance-use increases its stress level by 3.9883.
Call:
lm(formula = AnTotal ~ ReappraisalMean + SocialSupportMean +
ProbSolvingMean + RelMean + TolMean + Emomean + OveracMean +
RelaxMean + Subsmean, data = Durias1)
Residuals:
Min 1Q Median 3Q Max
-8.640 -3.572 -1.267 2.766 20.594
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.79897 4.46615 -0.179 0.85829
ReappraisalMean 1.60382 1.10498 1.451 0.14897
SocialSupportMean 1.31082 0.97808 1.340 0.18243
ProbSolvingMean -1.97803 1.21791 -1.624 0.10668
RelMean -0.32183 1.18417 -0.272 0.78621
TolMean 0.24674 0.91544 0.270 0.78793
Emomean 0.77602 1.25779 0.617 0.53829
OveracMean 1.75879 1.26915 1.386 0.16809
RelaxMean -0.05083 1.14784 -0.044 0.96475
Subsmean 4.47935 1.54695 2.896 0.00442 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5.423 on 135 degrees of freedom
Multiple R-squared: 0.1414, Adjusted R-squared: 0.08411
F-statistic: 2.469 on 9 and 135 DF, p-value: 0.01223As shown in the above results, it shows that the model is better than a model with only the intercept because at least one coefficient β is significantly different from 0 with a p -value = 0.006703. It also shows that substance-use significantly predict anxiety with a p-value result of 0.00387. The coefficient of substance-use is 4.4680, this means that higher substance-use score indicates higher anxiety level. On, the average, a one unit increase in substance-use increases its anxiety level by 4.680.
Pearson's product-moment correlation
data: Durias1$StTotal and Durias$AnTotal
t = 9.743, df = 143, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
0.5224234 0.7204693
sample estimates:
cor
0.6316421 Based on the results above, it shows that there is a positive correlation between anxiety and anxiety with a correlation value of 0.6316421. It further shows that there is a signification relationship between anxiety and stress with a p-value result of 2.2e-16, that is, 0.00000000000000022.
[1] 11.05517[1] 5.666396[1] 14.04828[1] 6.062557