Pearson eText Business Statistics: First Course -- Instant Access (Pearson+)
8th Edition
ISBN: 9780136880974
Author: David Levine, David Stephan
Publisher: PEARSON+
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Draw a scatter diagram with square feet of living space as the independent variable and selling price as the dependent variable and describe variable and describe the relationship between the size of a house and the selling price.
The data represent the cost, return on investment, and graduation rate for a random sample of fifty colleges or universities in the United States. The data is from payscale.com. The variable "Cost" represents the four-year cost including tuition, supplies, room and board of attending the school. The variable "Annual ROI" represents the return on investment for graduates of the school. It essentially represents how much you would earn on the
investment of attending the school. The variable "Grad Rate" represents the graduation rate of the school. Complete parts (a) and (b) below.
Click here to view the school data.
Click here to view the table of critical values of the correlation coefficient.
(a) Describe the association between Cost and Graduation Rate graphically by drawing a scatter diagram, treating Cost as the explanatory variable. Describe the association between Cost and Graduation Rate by finding the linear correlation between the two variables. Is there a linear association…
A nonprofit analyst seeks to determine which variables should be used to predict nonprofit charitable commitment, a nonprofit organization commitment
to its charitable purpose. Two independent variables under consideration are Revenue, a measurement of total revenue, in billions of dollars, as a
measure of nonprofit size X, and Efficiency, a measurement of the percent of private donations remaining after fundraising expenses as a measure of
nonprofit fundraising efficiency X2. The dependent variable Y is Commitment, a measurement of the percent of total expenses that are allocated directly
to charitable services. Both variables X, and Y are encoded as percents. Data are collected from a random sample of 98 nonprofit organizations, with
the results provided in the accompanying table. Complete parts (a) through (c) below.
E Click the icon to view the table of results.
a. State the multiple regression equation.
(Round to two decimal places as needed.)
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- If you graph a revenue and cost function, explain how to determine in what regions there is profit.arrow_forwardIf you are performing a break-even analysis for a business and their cost and revenue equations are dependent, explain what this means for the company's profit margins.arrow_forwardFor the revenue model in Exercise 10.206 and Exercise 10.210, explain what the x-intercepts mean to the backpack retailer.arrow_forward
- If you travel 100 miles in two hours, then your average speed for the trip is Average speed=_________=________arrow_forwardcan a cause and effect relationship be determined?arrow_forwardA nonprofit analyst seeks to determine which variables should be used to predict nonprofit charitable commitment, a nonprofit organization commitment to its charitable purpose. Two independent variables under consideration are Revenue, a measurement of total revenue, in billions of dollars, as a measure of nonprofit size X₁ and Efficiency, a measurement of the percent of private donations remaining after fundraising expenses as a measure of nonprofit fundraising efficiency X₂. The dependent variable Y is Commitment, a measurement of the percent of total expenses that are allocated directly to charitable services. Both variables X₂ and Y are encoded as percents. Data are collected from a random sample of 99 nonprofit organizations, with the results provided in the accompanying table. Complete parts (a) through (c) below. Click the icon to view the table of results. a. State the multiple regression equation. Ŷ₁ = + X₁₁ + x2i (Round to two decimal places as needed.) Table of results…arrow_forward
- Table of results Variable Intercept Revenue Efficiency Coefficients 11.680464 0.6999226 0.8029396 Print Standard Error 7.132097 0.321328 0.077201 T Statistic 1.64 2.18 10.40 Done p-Value 0.1048 0.0319 <0.0001 X ons of dollars, as a measure of nonp sure of nonprofit fundraising efficienc haritable services. Both variables X₂ d in the accompanying table. Complearrow_forwardTable of results Variable Intercept Revenue Efficiency Coefficients 11.680464 0.6999226 0.8029396 Print Standard Error 7.132097 0.321328 0.077201 T Statistic 1.64 2.18 10.40 Done p-Value 0.1048 0.0319 <0.0001 X ons of dollars, as a measure of nonp sure of nonprofit fundraising efficienc haritable services. Both variables X₂ d in the accompanying table. Complearrow_forwardTable of results Variable Intercept Revenue Efficiency Coefficients 11.680464 0.6999226 0.8029396 Print Standard Error 7.132097 0.321328 0.077201 T Statistic 1.64 2.18 10.40 Done p-Value 0.1048 0.0319 <0.0001 X ons of dollars, as a measure of nonp sure of nonprofit fundraising efficienc haritable services. Both variables X₂ d in the accompanying table. Complearrow_forward
- A real estate agent has developed a linear model for the price of a house, P, in dollars in terms of the area, A, in square feet for the homes in a certain neighborhood. The data set had areas ranging from 1,000 square feet to 4,500 square feet. Would predicting the prices of a home that is 4,900 square feet be interpolation or extrapolation? Explain. Using the model to predict the price of a 4,900 square foot home is extrapolation because 4,900 square feet is outside the range of the areas in the data. Using the model to predict the price of a 4,900 square foot home is interpolation because 4,900 square feet is inside the range of the areas in the data. Using the model to predict the price of a 4,900 square foot home is extrapolation because 4,900 square feet is inside the range of the areas in the data. Using the model to predict the price of a 4,900 square foot home is interpolation because 4,900 square feet is outside the range of the areas in the data.arrow_forwardDefine the terms dependent and independent variable and explain their relationship.arrow_forwardWhich are the graphs for quantitative data?arrow_forward
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