One of the key tasks in metropolitan area transportation planning is to estimate the total number...
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One of the key tasks in metropolitan area transportation planning is to estimate the total number of trips made by households during a typical day. It is hypothesized that one of the most important determinants of household trips is household income. 12 households are randomly selected to collect their trips per day and household income, and the data are provided in the following table. Trips per day 3 5 5 4 6 7 9 7 8 8 6 5 Household Income ($1,000) 25 36 33 27 42 48 63 54 66 72 51 45 Question 1. (1 point). Use software R to plot a scatter gram of trips and household income. Attach the scatter gram to this question. Do you think a linear regression will explain the relationship between the two variables? Question 2. (1.5 points). Do a regression analysis "by hand to determine the cause-effect relation between trips and household income. You only need to determine the dependent and independent variables, and calculate the least square regression line (slope and intercept) and r. Question 3. (1.5 points). Use software R to plot a scatter gram of the independent variable and corresponding residual. Attach the scatter gram to this question. Based on the scatter gram and other information, discuss the residual pattern in terms of the four aspects illustrated in the lecture. Question 4. (2 points). Do a hypothesis test to confirm whether household income is a determinant of household trips. You need to discuss the requirements, state the hypotheses, calculate the p-value and make conclusion. One of the key tasks in metropolitan area transportation planning is to estimate the total number of trips made by households during a typical day. It is hypothesized that one of the most important determinants of household trips is household income. 12 households are randomly selected to collect their trips per day and household income, and the data are provided in the following table. Trips per day 3 5 5 4 6 7 9 7 8 8 6 5 Household Income ($1,000) 25 36 33 27 42 48 63 54 66 72 51 45 Question 1. (1 point). Use software R to plot a scatter gram of trips and household income. Attach the scatter gram to this question. Do you think a linear regression will explain the relationship between the two variables? Question 2. (1.5 points). Do a regression analysis "by hand to determine the cause-effect relation between trips and household income. You only need to determine the dependent and independent variables, and calculate the least square regression line (slope and intercept) and r. Question 3. (1.5 points). Use software R to plot a scatter gram of the independent variable and corresponding residual. Attach the scatter gram to this question. Based on the scatter gram and other information, discuss the residual pattern in terms of the four aspects illustrated in the lecture. Question 4. (2 points). Do a hypothesis test to confirm whether household income is a determinant of household trips. You need to discuss the requirements, state the hypotheses, calculate the p-value and make conclusion.
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Related Book For
International Marketing And Export Management
ISBN: 9781292016924
8th Edition
Authors: Gerald Albaum , Alexander Josiassen , Edwin Duerr
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