10 -10 -20 100 200 300 400 Predicted Residuals

What are the assumptions of multiple linear regressions only?

Last years Data Management class decided to see if there was a relationship between the score (out of 10) a student got on the two-variable stats quiz, and their score (out of 30) on the unit test. Use the given data to Quiz Score Test Score 6 8 10 9 10 20 26 29 26 30 a) Calculate the correlation coefficient. b) Perform a linear regression.

Suppose the estimaited OLS regression is: Happiness = a + b*dailychocolates Now use chocolate consumprion per week instead of days. What is the relationship between the old and new units? How would this affect b (i.e. what is bnew in terms of b)?

Write a short note on regression analysis

Below is some of the regression output from a regression of the amount various customers paid for a new car (expressed in dollars) versus the age of the customer (expressed in years), the number of previous cars the customer had purchased from the dealership in the past, a dummy variable indicating the gender of the customer (=1 for a Man and = 0 for a woman), and an interactive term the multiplies the age of the customer with the gender dummy variable.  Regression Statistics           Multiple R 0.963           R Square             Adjusted R Square             Standard Error             Observations 20                         ANOVA               df SS MS F Significance F Regression   24686354.49 6171589 47.8 2.3289E-08   Residual     129243       Total   26625000…

Would I use the regression line to predict Y from X ?  And what is the pattern of the scatterplot?

We wants to assess the relationship between overall GPA (4.0 scale) and amount of time spent weekly on school work of 50 college students. Simple linear regression model is used and some results for the model is given: a) Is it plausible that the true intercept for the model is 2.0? Why or why not? (hint: using interval for intercept) b) If 2.0 is the real intercept for the model, does it make contextual sense? Explain why it is or why it is not. c) Using the model, calculate the number of hours needed to achieve a GPA of 4.0. Then explain why this estimate number of hours is biased. (hint: think about Y).

A study of king penguins looked for a relationship between how deep the penguins dive to seek food and how long they stay underwater. For all but the shallowest dives, there is a linear relationship that is different for different penguins. The study report gives a scatterplot for one penguin titled, “The relation of dive duration (DD) to depth (D).” Duration DD is measured in minutes, and depth D is in meters. The report then says, “The regression equation for this bird is DD=2.69+0.0138D. (a) What is the slope of the regression line? (Enter your answer rounded to four decimal places.) slope =     (b) On average, if the depth of the dive increases by one meter, what is the increase in the diving duration? (Enter your answer rounded to four decimal places.) increase in duration =   minutes (c) According to the regression line, how long does a typical dive to a depth of 168 meters last? (Enter your answer rounded to three decimal places.) length…

Let price denote a price index for the goods sold by a restaurant, advert the amount spent on advertising, sales the sales for the restaurant, and consider the following two regressions First regression: sales = B1 + B2price + B3price? + B4advert + ßsadvert? + e, Second regression: sales = B1 + B2price + B3price? + e We estimate both regressions using a sample of 105 observations. The sum of square residuals (E ê) from the first regression equals 50, while the sum of square Li=1 residuals from the second regression equals 70. Suppose we are interested in testing the null hypothesis that expected sales do not depend on advertising. What is the F- statistic for this null hypothesis? Recall the F-statistic is given by ((SSER - SSEU)/J)/(SSEy/(n – K)). O a. -15 O b. 42 Oc. 21 O d. 20 O e. All other options are incorrect.