According to the data represented, what is the strength of the effects? is there

Question

According to the data represented, what is the strength of the effects? is there significance found in the model (.694) for income in constant dollars and .412 (number of hours worked a week? Does (.000) represent the dependent variable and therefore the null hypothesis can be rejected? Does the overall model have statistical significance found in both the independent variables and the control variable? What would be a social change implication?

Model Summary Adjusted R Square Std. Error of the Estimate R Square 083 Model 289a 022 13.093 a. Predictors: (Constant), NUMBER OF HOURS USUALLY WORKAWEEK, RESPONDENTINCOME IN CONSTANT DOLLARS ANOVAa Sum of Squares df Mean Square 233.874 171.433 Model Sig 1.364 271 467.747 5142.980 5610.727 a. Dependent Variable: Rs occupational prestige score (2010) Regression Residual Total 30 32 b. Predictors: (Constant), NUMBER OF HOURS USUALLY WORKAWEEK, RESPONDENT INCOME IN CONSTANT DOLLARS Coefficients Standardized Unstandardized Coefficients Coefficients Model Std. Error Beta Sig (Constant) RESPONDENT INCOME IN CONSTANT DOLLARS NUMBER OF HOURS USUALLY WORKA WEEK 39.610 8.097 4.892 397 4.316E-5 100 694 209 251 209 832 412 a. Dependent Variable: Rs occupational prestige score (2010)

Explanation / Answer

The strength of effect is used to determine whether the difference between two groups are meaningly large regardless of whether the difference is statistically significant. Strength of the effect is calculated with mean, std deviation and sample sizes of both groups. However, the values are not present with the given data, thus unable to give you the value.

Since the values 0.694 and 0.412 are above the p value 0f 0.05, there is no significance difference between the two groups

The null hypothesis stating that there is no sognificant difference between the two variables is accepted

The only factor that shows a statistical significant is the factor (constant). However, there is no statistical significance found in both the independent variables

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