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***2a***. Interpretation of *correlation matrix* in your own words (1 point):

The correlation matrix in Table 3 shows the relationships between different variables in a study. Each cell in the matrix contains a correlation coefficient, which quantifies the strength and direction of the relationship between two variables. Here’s a summary of the key points:

1. **Correlation Coefficients**: These range from -1 to 1.
   - A value close to 1 indicates a strong positive correlation.
   - A value close to -1 indicates a strong negative correlation.
   - A value around 0 indicates no correlation.

2. **Variables**: The matrix includes 10 variables:
   1. Age
   2. Gender
   3. Education
   4. Geographic location
   5. Number of barriers
   6. Health Beliefs about Mental Illness (HBMI)
   7. Generalised Anxiety Disorder (GAD-7)
   8. Attitudes Toward Seeking Professional Psychological Help (ATSPPHS)
   9. General Self Efficacy Scale (GSES)
   10. Help-seeking intention questionnaire

3. **Significance Levels**: Some coefficients are marked with asterisks:
   - *p < .05 (indicated by one asterisk *)
   - **p < .01 (indicated by two asterisks **)
   
   These marks denote the statistical significance of the correlations.

4. **Notable Correlations**:
   - The number of barriers (Variable 5) is negatively correlated with many other variables, such as HBMI (Variable 6, r = -0.25*), GAD-7 (Variable 7, r = -0.19**), and GSES (Variable 9, r = -0.25**).
   - HBMI (Variable 6) shows positive correlations with GAD-7 (Variable 7, r = 0.28**) and Help-seeking intention questionnaire (Variable 10, r = 0.27**).
   - GAD-7 (Variable 7) is strongly positively correlated with HBMI (Variable 6, r = 0.28**) and shows a very strong correlation with the ATSPPHS (Variable 8, r = 0.63**).
   - GSES (Variable 9) is negatively correlated with many variables, such as GAD-7 (Variable 7, r = -0.44**) and HBMI (Variable 6, r = -0.25**), but positively correlated with Help-seeking intention questionnaire (Variable 10, r = 0.70**).

5. **General Observations**:
   - Age (Variable 1) has weak correlations with all other variables.
   - Gender (Variable 2) has some weak to moderate correlations, notably a negative correlation with ATSPPHS (Variable 8, r = -0.19**).
   - The education level (Variable 3) shows weak correlations overall, with a slight negative correlation with GSES (Variable 9, r = -0.12*).

This matrix helps to understand how these variables interact with each other in the context of the study, highlighting both significant and non-significant relationships.

Do you want more details on any specific correlation or variable? Here are some related questions that might help deepen your understanding:

1. How can the negative correlation between the number of barriers and GSES be interpreted?
2. Why is the correlation between GAD-7 and ATSPPHS particularly strong?
3. What implications do the significant correlations of HBMI have on mental health interventions?
4. How can we explain the weak correlations involving age?
5. What does the positive correlation between GSES and Help-seeking intention questionnaire indicate?
6. How might the negative correlations of the number of barriers affect overall mental health outcomes?
7. What are the practical implications of the positive correlation between HBMI and help-seeking intentions?
8. How does gender influence attitudes toward seeking psychological help, according to this matrix?

**Tip:** When interpreting correlation matrices, always consider the context of the study and the potential for underlying variables that might influence the relationships.

Understand the correlation matrix in statistical analysis with detailed insights on key variables like age, gender, education, and health beliefs about mental illness (HBMI). Explore how correlation coefficients indicate relationships between variables and their statistical significance. Learn about implications for mental health interventions and attitudes toward seeking psychological help.

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