Exam 9: Inference for Regression

In a random sample of 41 students, the correlation between Verbal SAT score and college GPA is 0.574. Is there evidence of a positive correlation between Verbal SAT score and college GPA? Use a 5% significance level. Include all details of the test. Round the test statistic to two decimal places.

Compute the standard deviation of the error term. Use two decimal places in your answer.

Use the following Data were collected on GPA and number of Facebook friends for students in a small statistics class. Some summary statistics, partial output from the regression analysis, and a scatterplot of the data (with regression line) are provided. Assume that students in this class are typical of all students at the university. Use three decimal places when reporting the results from any calculations, unless otherwise specified. The regression equation is GPA = 3.830 - 0.000919 FacebookFriends -Use the provided output to construct and interpret a 90% prediction interval for the GPA of a student with 800 Facebook friends.

Use the following In recent years, fast food restaurants have been required to publish nutrition information about the foods they serve. Nutrition information about a random sample of McDonald's lunch/dinner menu items (excluding sides and drinks) was obtained from their website. We wish to use the sodium content (in milligrams) to better understand the number of calories in the lunch/dinner menu items at McDonald's. Some summary statistics, partial computer output from a regression analysis, and a scatterplot (with regression line) of the data are provided. Use two decimal places when reporting the results from any calculations, unless otherwise specified. The regression equation is Calories = 99.69 + 0.3698 Sodium (mg) -Use the information in the ANOVA table to determine the number of menu items in the sample.

Use the following A quantitatively savvy, young couple is interested in purchasing a home in northern New York. They collected data on houses that had recently sold in the area. They want to predict the selling price of homes (in thousands of dollars) based on the age of the home (in years). Some summary statistics, partial regression output, and a scatterplot of the relationship (with regression line) are provided. Use two decimal places when reporting the results from any calculations, unless otherwise specified. The regression equation is Price (in thousands) = 193 - 0.665 Age Analysis of Variance -Use the provided computer output to compute the standard deviation of the error term.

Use the following Data were collected on the mileage (in thousands of miles) and price (in thousands of dollars) of a random sample of used Hyundai Elantras. A scatterplot of the data (with regression line), some summary statistics, and partial computer output from a regression analysis are provided. Use three decimal places when reporting the results from any calculations, unless otherwise specified. The regression equation is Price = 13.8 - 0.0912 Mileage -Use the provided output to compute and interpret R².

Use the following Students in a small statistics course wanted to investigate if forearm length (in cm) was useful for predicting foot length (in cm). The data they collected are displayed in the provided scatterplot (with regression), and the computer output from the analysis is provided. Use three decimal places when reporting the results from any calculations, unless otherwise specified. The regression equation is Foot (cm) = 9.22 + 0.574 Forearm (cm) Predicted Values for New Observations -Construct a 90% confidence interval for the population slope.

Use the following Data were collected on GPA and number of Facebook friends for students in a small statistics class. Some summary statistics, partial output from the regression analysis, and a scatterplot of the data (with regression line) are provided. Assume that students in this class are typical of all students at the university. Use three decimal places when reporting the results from any calculations, unless otherwise specified. The regression equation is GPA = 3.830 - 0.000919 FacebookFriends -Use the following output to identify and interpret a 95% interval for the mean GPA for all students with 500 Facebook friends. ‪

Use the following to answer questions : Computer output from a regression analysis is provided. -What is the sample slope for this model?

Use the following Computer output from a regression analysis is provided. ‪ -The sample size in this situation is n = 157. Construct a 95% confidence interval for the population slope. Round the margin of error to four decimal places.

Use the following A quantitatively savvy, young couple is interested in purchasing a home in northern New York. They collected data on houses that had recently sold in the area. They want to predict the selling price of homes (in thousands of dollars) based on the age of the home (in years). Some summary statistics, partial regression output, and a scatterplot of the relationship (with regression line) are provided. Use two decimal places when reporting the results from any calculations, unless otherwise specified. The regression equation is Price (in thousands) = 193 - 0.665 Age Analysis of Variance -Construct and interpret a 95% interval for the mean selling price of all 92-year-old homes.

Use the following Data were collected on GPA and number of Facebook friends for students in a small statistics class. Some summary statistics, partial output from the regression analysis, and a scatterplot of the data (with regression line) are provided. Assume that students in this class are typical of all students at the university. Use three decimal places when reporting the results from any calculations, unless otherwise specified. The regression equation is GPA = 3.830 - 0.000919 FacebookFriends -Is the linear model effective at predicting GPA? Use the information from the computer output and = 0.05. Include all details of the test.

Use the following A quantitatively savvy, young couple is interested in purchasing a home in northern New York. They collected data on houses that had recently sold in the area. They want to predict the selling price of homes (in thousands of dollars) based on the age of the home (in years). Some summary statistics, partial regression output, and a scatterplot of the relationship (with regression line) are provided. Use two decimal places when reporting the results from any calculations, unless otherwise specified. The regression equation is Price (in thousands) = 193 - 0.665 Age Analysis of Variance -Use the following output to identify and interpret a 95% interval for the mean selling price of all 50-year-old homes in this portion of northern New York. Predicted Values for New Observations

Use the following Data were collected on the age (in years) and price (in thousands of dollars) of a random sample of 25 used Hyundai Elantras. A scatterplot of the data (with regression line) and computer output from a regression analysis are provided. Use three decimal places when reporting the results from any calculations, unless otherwise specified. The regression equation is Price = 15.3 - 1.71 Age S = 1.37179 R-Sq = 88.9% R-Sq(adj) = 88.4% Predicted Values for New Observations -What is the R² for this model? Interpret it in context.

Use the following A quantitatively savvy, young couple is interested in purchasing a home in northern New York. They collected data on houses that had recently sold in the area. They want to predict the selling price of homes (in thousands of dollars) based on the age of the home (in years). Some summary statistics, partial regression output, and a scatterplot of the relationship (with regression line) are provided. Use two decimal places when reporting the results from any calculations, unless otherwise specified. The regression equation is Price (in thousands) = 193 - 0.665 Age Analysis of Variance -Construct and interpret a 95% interval for the selling price of a single 92-year-old home.

Use the following In recent years, fast food restaurants have been required to publish nutrition information about the foods they serve. Nutrition information about a random sample of 15 McDonald's lunch/dinner menu items (excluding sides and drinks) was obtained from their website. We wish to use the total fat content (in grams) to better understand the number of calories in the lunch/dinner menu items at McDonald's. Computer output from a regression analysis and a scatterplot (with regression line) of the data are provided. Use two decimal places when reporting the results from any calculations, unless otherwise specified. -Based on the available information, what is the correlation between total fat content (g) and number of calories for McDonald's lunch/dinner menu items in this sample?

Use the following Data were collected on the mileage (in thousands of miles) and price (in thousands of dollars) of a random sample of used Hyundai Elantras. A scatterplot of the data (with regression line), some summary statistics, and partial computer output from a regression analysis are provided. Use three decimal places when reporting the results from any calculations, unless otherwise specified. The regression equation is Price = 13.8 - 0.0912 Mileage -Compute the t test statistic for the slope.

Use the following In recent years, fast food restaurants have been required to publish nutrition information about the foods they serve. Nutrition information about a random sample of 15 McDonald's lunch/dinner menu items (excluding sides and drinks) was obtained from their website. We wish to use the total fat content (in grams) to better understand the number of calories in the lunch/dinner menu items at McDonald's. Computer output from a regression analysis and a scatterplot (with regression line) of the data are provided. Use two decimal places when reporting the results from any calculations, unless otherwise specified. -What is the R² for this model? Interpret it in context.

Use the following A quantitatively savvy, young couple is interested in purchasing a home in northern New York. They collected data on houses that had recently sold in the area. They want to predict the selling price of homes (in thousands of dollars) based on the age of the home (in years). Some summary statistics, partial regression output, and a scatterplot of the relationship (with regression line) are provided. Use two decimal places when reporting the results from any calculations, unless otherwise specified. The regression equation is Price (in thousands) = 193 - 0.665 Age Analysis of Variance -Use the following output to identify and interpret a 95% interval for the selling price of a 50-year-old house in this portion of northern New York. Predicted Values for New Observations

Use the following A quantitatively savvy, young couple is interested in purchasing a home in northern New York. They collected data on houses that had recently sold in the area. They want to predict the selling price of homes (in thousands of dollars) based on the age of the home (in years). Some summary statistics, partial regression output, and a scatterplot of the relationship (with regression line) are provided. Use two decimal places when reporting the results from any calculations, unless otherwise specified. The regression equation is Price (in thousands) = 193 - 0.665 Age Analysis of Variance -Is the linear model effective at predicting the selling price of homes in this portion of northern New York? Use the provided computer output (and = 0.05) for this test. Include all details of the test.