on the first statistics exam, the coefficient of determination between the hours studied and the grade earned was 80%. the standard error of the estimate was 15. there were 20 students in the class. develop ANOVA table for the regression analysis of hours studied as a predictor of the grade earned on the first statistics exam.

The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the number of bids an item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Price in Dollars 2020 3030 3535 4242 4949 Number of Bids 33 44 55 66 99 Table Copy Data Step 1 of 6 :   Find the estimated slope. Round your answer to three decimal places.

A colleague of yours is completing a final report on the causes of the frequency of cyberbullying.  In this report, she is asked to identify the causes that most strongly impacted the frequency of cyberbullying.  She conducts an OLS regression.  What statistic do you advise her to use in her discussion?  Why?

On the first statistics exam, the coefficient of determination between the hours studied and the grade earned was 80%. The standard error of estimate was 10. There were 15 students in the class. Develop an ANOVA table for the regression analysis of hours studied as a predictor of the grade earned on the first statistics exam. (Round your DF answers to nearest whole number and other answers to 2 places.) Source DF SS MS Regression 1 Error Total 13 14

what is a confidence coefficinent for a simple linear regression line whoes alpha =0.05 and line is y(hat)=-7.45-10x

Acrylamide is a chemical that is sometimes found in cooked starchy foods and which is thought to increase the risk of certain kinds of cancer. The paper "A Statistical Regression Model for the Estimation of Acrylamide Concentrations in French Fries for Excess Lifetime Cancer Risk Assessment"+ describes a study to investigate the effect of frying time (in seconds) and acrylamide concentration (in micrograms per kilogram) in french fries. The data in the accompanying table are approximate values read from a graph that appeared in the paper. Frying Acrylamide Time Concentration 150 240 240 270 300 300 150 125 + 195 185 135 275 USE SALT (a) Find the equation of the least-squares line for predicting acrylamide concentration using frying time. (Round your answers to four decimal places.) ŷ = (b) Does the equation of the least-squares line support the conclusion that longer frying times tend to be paired with higher acrylamide concentrations? Explain. O No, the least squares regression line…

The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Find the estimated y intercept . Round your answer to three decimal places. age 35 41 52 56 66  bone density 358 350 348 332 321

The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the number of bids an item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Price in Dollars 2323 3434 4040 4646 4747 Number of Bids 11 33 44 55 77 Table Copy Data Step 2 of 6:  Find the estimated y-intercept. Round your answer to three decimal places.

The following table shows the starting salary and profile of a sample of 10 employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance.What is the equation of the resulting multiple linear regression?   starting_salary = 3008.61 + 48.65*GPA + 94.79*years_of_experience + 27.36*civil_service_ratings       starting_salary = 15000.00 + 48.65*GPA + 94.79*years_of_experience + 27.36*civil_service_ratings       starting_salary = 15001.00 + 41.43*GPA + 84.71*years_of_experience + 37.32*civil_service_ratings       starting_salary = 2366.77 + 130.25*GPA + 396.39*years_of_experience + 21.67*civil_service_ratings

Suppose the entering freshmen at a certain college have a mean combined SAT score of 1231 with a standard deviation of 122 In the first​ semester, these students attained a mean GPA of 2.64​, with a standard deviation of 0.53. A scatterplot showed the association to be reasonably​ linear, and the correlation between SAT score and GPA was 0.47 How do i find the regression line using the equation