Answer all questions please in response to the picture attached : a) Confirm that the work provided is correct OR provide guidance on corrections that are needed. b) Calculate the hypothesis test (alpha of .05), showing your work, and explain if the results is statistically significant. **Note: If you are responding to someone and sample size is not listed, you can create your own sample size to identify the critical value. c) Calculate r-squared and explain this value in terms of the example.

A researcher wants to predict the amount of anxiety attacks that will be experienced monthly by an individual with GAD who consumes 200 mg of caffeine a day. She gathers the following Information from a sample of 15 patients: Caffeine consumption (X): Mean = 134mg/day; SD = 48 Anxiety Attacks (Y): Mean = 4.52 /month; SD = 2.1 r = 0.64 A linear regression is appropriate for this example because it allows for the prediction of one variable based on the other: In this case, it allows the researcher to predict the level of monthly anxiety attacks based on an Individual's caffeine consumption. Work for the raw score linear regression equation is shown below. Y = a + bx when X = 0 ... Ex = 10 - 134 ) / 48 . 0.64 = - 1.79 .. a = ( - 1.79 . 2. 1) + 4.52 = 0.768 when X : 1 ... Ex : [ (1- 134) / 48] . 0.64 = - 1.77 Y = ( - 1. 77 . 2.1) + 4.52: 0. 796 . 6 = 0.796 - 0-768 = 0. 028 raw score linear regression equation: * = 0.768 + 0.028X Reply