Simple linear regression results: Dependent Variable: % obese Independent Variable: % less 1 vegetable/day % obese = -2.890451 + 0.4002508 % less 1 vegetable/day Sample size: 32 R (correlation coefficient) = 0.66457159 R-sq = 0.4416554 Estimate of error standard deviation: 2.0064392 Parameter estimates: Parameter Estimate Std. Err. Intercept Slope Alternativ DF T-Stat P-value e -2.890451 3.2385091 0 30 -0.89252521 0.3792 0.4002508 0.082163886 0 30 4.8713714 <0.0001 Analysis of variance table for regression model: SourceDF SS MS F-stat P-value Model 1 95.533238 95.533238 23.730259<0.0001 Error 30 120.77395 4.0257983 Total 31 216.30719 a. b. c. d. e. f. g. Write 5 descriptive, detailed sentences discussing the results. Discuss the strength and direction of the correlation Are the results expected? What do these results tell you about the relationship of the two variables? If strong correlation, is it due to causation, and underlying cause or coincidence? State the slope of the regression line and a give a sentence to explain what it means. Choose a value of the explanatory variable and use the equation of the regression line to predict the average response variable. h. Show set-ups to calculations. i. Write a descriptive sentence explaining what the prediction tells