Chapter 2.4, Problem 46E

The slope, b represents * O predicted value of Y when X = 0. O the estimated average change in Y per unit change in X. O variation around the line of regression. O the predicted value of Y.

Statistics professor wants to use the number of hours (x) a student studies for a statistics final exam to predict the final exam score (y). A regression model was fit based on data collected from a class during the previous semester, with the following results: (y hat): y = 35.0 + 3X What is the slope? a. Yb. 35.0c. 3d. X

A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y) The results of the regression were: учах+b a-1.25 b-35.644 r2 .541696 r=-0.736 Use this to predict the number of situps a person who watches 10 hours of TV can do (to one decimal place)

Input 'X' Family Median Percentiles OutPut 'Y' Percent Of Children Attending College 100 94 1 25 Find The Linear equation using the above data.

I need correct solution only handwritten

The table shows a regression of average hourly earnings (wage) on education (educ), age (age) and the gender dummy (woman). Discuss briefly the results. How do you interpret the intercept and the slope coefficients on these three variables?

MY NOTES ASK YOUR TEAC Does it pay to study for an exam? The number of hours studied, x, is compared to the exam grade received, y. 2 3. 80 85 70 90 95 (a) Find the equation for the line of best fit. (Round your intercept to two decimal places and your slope to three decimal places.) (b) Draw the ine of best fit on the scatter diagram of these data. (Do this on paper. Your inotructor may ask you to turn in this work.) (c) Based on what you see in your answers to parts (a) and (b), does it pay to study for an exam? O Yes, there is a strong relationship in the data. INo, there is not a strong relationship in the data.

Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. j = 12 +1.8x n=17 SSR = 225 SSE = 75 Sb1 = .2683 The t statistic for testing the significance of the slope is A B 1.80. D 1.96. C 6.71. .56.

A medical researcher wants to determine howa new medication affects blood pressure. 150 140 130 120 110 100 50 100 150 200 250 300 350 Amount of medication (in mg) The regression equation for the plot above is Y Ex: 40 :+ Ex: 0.43 X. Patient systolic blood pressure (in mm Hg)