Humphrey-EDR8202-3 (4)

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Analyzing Data Using Bivariate Correlation, Regression, and T-Tests Null and Alternative Hypotheses: The null and alternative hypotheses for the bivariate correlation analysis are as follows: H0: ρ = 0 (correlation coefficient is 0; no association) H1: ρ ≠ 0 (correlation coefficient is not 0; nonzero correlation could exist) These hypotheses are used to test the strength and direction of the relationship between variables. Scatterplot Relationship: The scatterplot visually depicts a positive relationship between the variables, indicating that as one variable increases, the other tends to increase as well.
Correlation Analysis: The correlation analysis shows that the correlation coefficient between Beck depression and emotional control is 0.304 (p < .001 for a two-tailed test), based on 421 complete observations. This positive correlation suggests a moderately strong relationship between the variables. Shared Variance: The shared variance by Beck depression and emotional control is calculated as (0.304)^2 = 0.0924, which corresponds to 9.24% of the variance. Model Significance: The model, represented by the Pearson correlation coefficient, is significant (p < .001 for a two-tailed test) based on 421 complete observations. The significant result leads to the rejection of the null hypothesis.
2. In SPSS, develop a regression model between the variables emcontot and beckdep. a. The dependent (predicted) variable is beckdep. Predictors: (Constant), emotional control: full scale cecs Dependent Variable: Beck depression: bdi b. Predictors: (Constant), emotional control: full scale cecs Dependent Variable: Beck depression: bdi c.
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