Question

# ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 109,780 3 36,593 617,763...

 ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 109,780 3 36,593 617,763 ,030a Residual 10,722 181 ,059 Total 120,501 184 a. Predictors: (Constant), F4, F2, F3 b. Dependent Variable: F1
 Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) ,356 ,105 3,373 ,001 F2 -,269 ,026 -,699 -2,997 ,030 F3 ,030 ,028 ,570 2,103 ,021 F4 ,859 ,024 ,989 1,112 ,141 a. Dependent Variable: F1

a- Write down the hypothesis, p- value and your conclusion.

b- Can you predict satisfaction score by using any of the independent variables? If yes, what are these variables write down the hypothesis for each of the variable and give your conclusion.

c- What is the most important variable?

(a) The hypothesis being tested is:

H0: β1 = β2 = β3 = 0

H1: At least one βi ≠ 0

The p-value is 0.030.

Since the p-value (0.030) is less than the significance level (0.05), we can reject the null hypothesis.

Therefore, we can conclude that the model is significant.

(b) The hypothesis being tested is:

H0: β1 = 0

H1: β1 ≠ 0

The p-value is 0.030.

Since the p-value (0.030) is less than the significance level (0.05), we can reject the null hypothesis.

Therefore, we can conclude that the slope, F2, is significant.

The hypothesis being tested is:

H0: β2 = 0

H1: β2 ≠ 0

The p-value is 0.021.

Since the p-value (0.021) is less than the significance level (0.05), we can reject the null hypothesis.

Therefore, we can conclude that the slope, F3, is significant.

(c) F3

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