Consider the simple linear regression model based on normal theory. If we are interested in two different testing H0 : B1 = 0 vs H1:  B1 does not = 0 and H0 :  p= 0 vs  H1: p does not = 0, then show that test statistic value in both the tests are equivalent (values are always same).

A researcher is interested in examining the relationship between spousal abuse and child abuse.  Specifically, they are interested in determining whether there is a predictive relationship between spousal abuse and child abuse in 5 county social services offices.  Calculate the linear regression line for the following data.  Note you have already calculated the first step to this analysis (Pearson's Correlation)

Select all statements that are true of the least-squares regression line. ) It assumes a linear relationship between the explanatory and the response variable. R-squared is the portion of sample variance in the explanatory variable that can be explained by variation in the response variable. ) It can be used to predict the mean response of the explanatory variable. | R-squared is the portion of sample variance in the y variable that can be explained by variation in the x variable.

For a given set of x and y data values, assume that the regression model assumptions are valid and that a 90% confidence interval for ₁ is given by (-2.2, -0.1). Which of the following statements are true? i) At a = 0.10, there is a significant linear relationship between x and y. ii) In the scatterplot of x and y, the values of y tend to decrease as the values of x increase. iii) Based on this confidence interval, we would reject the null hypothesis of no linear relationship at any significance level a ≤ 0.1. Select one: a. i) O b. i) and ii) O c. ii) d. i), ii), and iii)