Exam 9: Inference for Regression

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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. 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        -Write down the equation of the least squares line and use it to predict the selling price of a 92-year-old home. The regression equation is Price (in thousands) = 193 - 0.665 Age Analysis of Variance 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        -Write down the equation of the least squares line and use it to predict the selling price of a 92-year-old home. 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        -Write down the equation of the least squares line and use it to predict the selling price of a 92-year-old home. -Write down the equation of the least squares line and use it to predict the selling price of a 92-year-old home.

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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 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        -Use the computer output to test the slope to determine whether age is an effective predictor of price. Use   = 0.05. Include all details of the test. S = 1.37179 R-Sq = 88.9% R-Sq(adj) = 88.4% 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        -Use the computer output to test the slope to determine whether age is an effective predictor of price. Use   = 0.05. Include all details of the test. 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        -Use the computer output to test the slope to determine whether age is an effective predictor of price. Use   = 0.05. Include all details of the test. -Use the computer output to test the slope to determine whether age is an effective predictor of price. Use 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        -Use the computer output to test the slope to determine whether age is an effective predictor of price. Use   = 0.05. Include all details of the test. = 0.05. Include all details of the test.

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Use the following Computer output from a regression analysis is provided. ‪ Use the following  Computer output from a regression analysis is provided. ‪   -What is the p-value for testing if the slope in the population is different from zero? -What is the p-value for testing if the slope in the population is different from zero?

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Two intervals are given for the same value of the explanatory variable. Which interval is the confidence interval for the mean response at this value of the explanatory variable?

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Use the following to answer questions : Computer output from a regression analysis is provided. Use the following to answer questions : Computer output from a regression analysis is provided.    -Use the p-value for testing if the slope in the population is different from zero (and a 5% significance level) to make a clear conclusion about the effectiveness of the model. -Use the p-value for testing if the slope in the population is different from zero (and a 5% significance level) to make a clear conclusion about the effectiveness of the model.

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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. 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 information in the computer output to compute the standard deviation of the error term. The regression equation is GPA = 3.830 - 0.000919 FacebookFriends 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 information in the computer output to compute the standard deviation of the error term. 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 information in the computer output to compute the standard deviation of the error term. -Use the information in the computer output to compute the standard deviation of the error term.

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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 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        -Use the computer output to provide and interpret a 95% interval for the price of a 3-year-old used Hyundai Elantra. S = 1.37179 R-Sq = 88.9% R-Sq(adj) = 88.4% 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        -Use the computer output to provide and interpret a 95% interval for the price of a 3-year-old used Hyundai Elantra. 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        -Use the computer output to provide and interpret a 95% interval for the price of a 3-year-old used Hyundai Elantra. -Use the computer output to provide and interpret a 95% interval for the price of a 3-year-old used Hyundai Elantra.

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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) 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        -Use the scatterplot to determine whether we should have any significant concerns about the conditions being met for using a linear model with these data. Explain briefly. 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        -Use the scatterplot to determine whether we should have any significant concerns about the conditions being met for using a linear model with these data. Explain briefly. Predicted Values for New Observations 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        -Use the scatterplot to determine whether we should have any significant concerns about the conditions being met for using a linear model with these data. Explain briefly. 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        -Use the scatterplot to determine whether we should have any significant concerns about the conditions being met for using a linear model with these data. Explain briefly. -Use the scatterplot to determine whether we should have any significant concerns about the conditions being met for using a linear model with these data. Explain briefly.

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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. 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.    -Construct and interpret a 99% confidence interval for the population slope. -Construct and interpret a 99% confidence interval for the population slope.

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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. 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 construct and interpret a 95% interval for the mean price of all used Hyundai Elantras with 50,000 miles. The regression equation is Price = 13.8 - 0.0912 Mileage 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 construct and interpret a 95% interval for the mean price of all used Hyundai Elantras with 50,000 miles. 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 construct and interpret a 95% interval for the mean price of all used Hyundai Elantras with 50,000 miles. -Use the provided output to construct and interpret a 95% interval for the mean price of all used Hyundai Elantras with 50,000 miles.

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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. 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 scatterplot to determine whether we should have any strong concerns about the conditions being met for using a linear model with these data. Explain briefly. The regression equation is GPA = 3.830 - 0.000919 FacebookFriends 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 scatterplot to determine whether we should have any strong concerns about the conditions being met for using a linear model with these data. Explain briefly. 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 scatterplot to determine whether we should have any strong concerns about the conditions being met for using a linear model with these data. Explain briefly. -Use the scatterplot to determine whether we should have any strong concerns about the conditions being met for using a linear model with these data. Explain briefly.

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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. 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        -Write down the equation of the least squares line and use it to predict the GPA for someone with 800 Facebook friends. The regression equation is GPA = 3.830 - 0.000919 FacebookFriends 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        -Write down the equation of the least squares line and use it to predict the GPA for someone with 800 Facebook friends. 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        -Write down the equation of the least squares line and use it to predict the GPA for someone with 800 Facebook friends. -Write down the equation of the least squares line and use it to predict the GPA for someone with 800 Facebook friends.

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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 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        -Use the computer output to provide and interpret a 95% interval for the mean price of all 3 year old used Hyundai Elantras. S = 1.37179 R-Sq = 88.9% R-Sq(adj) = 88.4% 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        -Use the computer output to provide and interpret a 95% interval for the mean price of all 3 year old used Hyundai Elantras. 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        -Use the computer output to provide and interpret a 95% interval for the mean price of all 3 year old used Hyundai Elantras. -Use the computer output to provide and interpret a 95% interval for the mean price of all 3 year old used Hyundai Elantras.

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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 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        -Write down the equation of the least squares line and use it to predict the price of a used Hyundai Elantra that is 6 years old. S = 1.37179 R-Sq = 88.9% R-Sq(adj) = 88.4% 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        -Write down the equation of the least squares line and use it to predict the price of a used Hyundai Elantra that is 6 years old. 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        -Write down the equation of the least squares line and use it to predict the price of a used Hyundai Elantra that is 6 years old. -Write down the equation of the least squares line and use it to predict the price of a used Hyundai Elantra that is 6 years old.

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Use the following A quantitatively savvy, young couple is interested in purchasing a home in northern New York. They collected data on 48 houses that had recently sold in the area. They want to predict the selling price of homes (in thousands of dollars) based on the size of the home (in square feet). The regression equation is Price (in thousands) = 17.1 + 0.0643 Size (sq. ft.) Use the following  A quantitatively savvy, young couple is interested in purchasing a home in northern New York. They collected data on 48 houses that had recently sold in the area. They want to predict the selling price of homes (in thousands of dollars) based on the size of the home (in square feet). The regression equation is Price (in thousands) = 17.1 + 0.0643 Size (sq. ft.)     S = 48.5733 R-Sq = 37.5% R-Sq(adj) = 36.1% Predicted Values for New Observations        -Use the scatterplot to determine whether we should have any serious concerns about the conditions being met for using a linear model with these data. Explain briefly. S = 48.5733 R-Sq = 37.5% R-Sq(adj) = 36.1% 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 48 houses that had recently sold in the area. They want to predict the selling price of homes (in thousands of dollars) based on the size of the home (in square feet). The regression equation is Price (in thousands) = 17.1 + 0.0643 Size (sq. ft.)     S = 48.5733 R-Sq = 37.5% R-Sq(adj) = 36.1% Predicted Values for New Observations        -Use the scatterplot to determine whether we should have any serious concerns about the conditions being met for using a linear model with these data. Explain briefly. Use the following  A quantitatively savvy, young couple is interested in purchasing a home in northern New York. They collected data on 48 houses that had recently sold in the area. They want to predict the selling price of homes (in thousands of dollars) based on the size of the home (in square feet). The regression equation is Price (in thousands) = 17.1 + 0.0643 Size (sq. ft.)     S = 48.5733 R-Sq = 37.5% R-Sq(adj) = 36.1% Predicted Values for New Observations        -Use the scatterplot to determine whether we should have any serious concerns about the conditions being met for using a linear model with these data. Explain briefly. -Use the scatterplot to determine whether we should have any serious concerns about the conditions being met for using a linear model with these data. Explain briefly.

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In a random sample of 41 college students, the correlation between number of hours of television watched in a typical week and college GPA is -0.125. Is there evidence of a negative correlation between the amount of television watched and college GPA? Use a 5% significance level. Include all details of the test. Round the test statistic to three decimal places.

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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. 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 provided output to construct and interpret a 95% interval for the number of calories in a single McDonald's lunch/dinner menu item with 1,000 mg of sodium. The regression equation is Calories = 99.69 + 0.3698 Sodium (mg) 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 provided output to construct and interpret a 95% interval for the number of calories in a single McDonald's lunch/dinner menu item with 1,000 mg of sodium. 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 provided output to construct and interpret a 95% interval for the number of calories in a single McDonald's lunch/dinner menu item with 1,000 mg of sodium. -Use the provided output to construct and interpret a 95% interval for the number of calories in a single McDonald's lunch/dinner menu item with 1,000 mg of sodium.

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Use the following to answer questions : Computer output from a regression analysis is provided. Use the following to answer questions : Computer output from a regression analysis is provided.    -The sample size in this situation is n = 20. What are the degrees of freedom for constructing a confidence interval, or performing a test about, the population slope? -The sample size in this situation is n = 20. What are the degrees of freedom for constructing a confidence interval, or performing a test about, the population slope?

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Use the following In a regression analysis with n = 25, SSE = 1,800 and SSTotal = 2,000. -Use this information to fill in all values in an analysis of variance table as shown. Round decimal answers to three decimal places. Use the following  In a regression analysis with n = 25, SSE = 1,800 and SSTotal = 2,000. -Use this information to fill in all values in an analysis of variance table as shown. Round decimal answers to three decimal places.

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Use this information to fill in all values in an analysis of variance table as shown. Use this information to fill in all values in an analysis of variance table as shown.

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