## Question 1: Perceived Value of Statistical Science and Study Time Analysis

**Problem Description:
**

The SPSS assignment aims to confirm a hypothesis regarding the relationship between students' perceived value of statistical science and their study time, with an expectation that higher perceived value correlates with increased study time and, consequently, higher test scores.

**Solution:
**

Upon analysis using the PROCESS module in SPSS, the direct effect between the perceived value of statistical science and test scores was found to be significant (P-value = 0.000). Additionally, both perceived value and study time had significant effects on test scores. The indirect effect of perceived value on test scores through study time was also significant, accounting for 22% of the total effect.

**Selected Output:
**

- Perceived value → Test scores: b = 0.43, SE = 0.09, t = 4.97, p-value = 0.00
- Indirect effect: b = 0.32, SE = 0.08, 95% CI [0.17, 0.48], 22% of total effect.

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## Question 2: Association between Eye Colors of Men and Women

**Problem Description:
**

This assignment investigates whether there's a significant association between the eye colours of men and their female partners, utilizing the chi-squared test of independence.

**Solution:
**

The chi-square test revealed a statistically significant relationship between the eye colours of men and women (X^2(4, N = 204) = 33.702, p-value = 0.000), indicating a correlation between the eye colours of men and their female partners.

**Selected Output:
**

- Chi-Square: X^2(4, N = 204) = 33.702, p-value = 0.000.

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## Question 3: Predictors of Burnout among University Professors

**Problem Description:
**

The assignment involves conducting hierarchical logistic regression to identify predictors of burnout among university professors, considering factors like perceived control, coping style, stress from teaching, and stress from research.

**Solution:
**

The overall model was statistically significant, and individual predictors showed varied relationships with burnout. Perceived control and coping ability positively predicted burnout, while stress from teaching negatively predicted burnout. Stress from research did not significantly predict burnout.

**Selected Output:
**

- Perceived Control: OR = 1.100, 95% CI = [1.071, 1.130]
- Coping Ability: OR = 1.146, 95% CI = [1.112, 1.181]
- Stress from Teaching: OR = 0.920, 95% CI = [0.890, 0.951]
- Stress from Research: Not a significant predictor (p-value > 0.05).

**Question 3: **Predictors of Burnout among University Professors (Output Analysis)

**Problem Description:
**

The task involves hierarchical logistic regression to identify predictors of burnout among university professors. The analysis considers perceived control, coping ability, stress from teaching, and stress from research.

**Solution:
**

**Block 0: **Beginning Block

- Model Fit:
- Total Cases: 467
- Burnout Prediction Accuracy: 74.5%
- Variables in the Equation:
- Constant: Exp(B) = 0.342
- Variables not in the Equation:
- Perceived Control, Coping Ability
- Overall Statistics: Chi-square = 162.861, df = 2, Sig. = .000

**Block 1:** Method = Enter

- Model Fit:
- Chi-square for Model Coefficients: 165.928, df = 2, Sig. = .000
- Overall Model Chi-square: 165.928, df = 2, Sig. = .000
- Model Summary: -2 Log likelihood = 364.179, Cox & Snell R Square = 0.299, Nagelkerke R Square = 0.441
- Burnout Prediction Accuracy: 80.5%
- Variables in the Equation:
- Perceived Control: Exp(B) = 1.063
- Coping Ability: Exp(B) = 1.086
- Constant: Exp(B) = 0.011
- Variables not in the Equation:
- None

**Block 2: **Method = Enter

- Model Fit:
- Chi-square for Model Coefficients: 30.468, df = 2, Sig. = .000
- Overall Model Chi-square: 196.396, df = 4, Sig. = .000
- Model Summary: -2 Log likelihood = 333.711, Cox & Snell R Square = 0.343, Nagelkerke R Square = 0.506
- Burnout Prediction Accuracy: 83.3%
- Variables in the Equation:
- Perceived Control: Exp(B) = 1.100
- Coping Ability: Exp(B) = 1.146
- Stress from Teaching: Exp(B) = 0.920
- Stress from Research: Exp(B) = 1.018
- Constant: Exp(B) = 0.052
- Variables not in the Equation:
- None

## Summary:

The hierarchical logistic regression analysis indicates a significant prediction of burnout among university professors. Perceived control and coping ability play essential roles, while stress from teaching and research also contribute. The model shows improvement with the inclusion of stress factors.