What is the minimum age?

Answer: 30

In the variable “age”, group the “age” variable into two groups, with atmost 50 years and more than 50 years old.

How many of them with at least 50 years old?

Answer: 69

Socio-Demographic Profile

Gender

Education


      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

Income

1. What is the respondent’s level of stress and anxiety as measured by Depression, Anxiety, and Stress Scale (DASS-21)?


Extremely severe             mild             Mild         Moderate 
               2                1               41               24 
          Normal           Severe 
              75                2

3.1 Is there a significant relationship between respondent’s level of stress and coping mechanisms?


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: 0.03584

As 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 = 0.0186 and 0.0569. 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.

3.2 Is there a significant relationship between respondent’s level of stress and coping mechanisms?


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: 0.01223

As 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 = 0.00442. It also shows that substance-use significantly predict anxiety with a p-value result of 0.00442. The coefficient of substance-use is 4.47935 , 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 4.47935 .

Checking of Assumptions

Explain each assumptions in using multiple regression.

Answer: Posterior Predictive Check is the comparison between what the fitted model predicts and the actual observed data. The aim is to detect if the model is inadequate to describe the data. Linearity/Scatter plot checks if there is a linear relationship between the dependent variable and each of the independent variables. Homogeneity of Variance means that the level of variance for a particular variable is constant across the sample. Collinearity assumes that the independent variables are not highly correlated with each other. Normality of Residuals assumes that the residuals are normally distributed.

3. Is there a significant relationship between stress and anxiety?


    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 stress and anxiety with a correlation value of 0.6316421. It further shows that there is a significant relationship between anxiety and stress with a p-value result of 2.2e-16, that is, 0.00000000000000022.