Introductory Statistics (10th Edition)
10th Edition
ISBN: 9780321989178
Author: Neil A. Weiss
Publisher: PEARSON
expand_more
expand_more
format_list_bulleted
Textbook Question
Chapter A.3, Problem 66E
Graduation Rates. Refer to Exercise A.45 on page A-15 regarding the relationship between college graduation rate and the predictor variables of student-to-faculty ratio, the percentage of freshmen in the top 10% of their high school class, and the percentage of applicants accepted. Use Output A.9 on page A-19 to help answer the following questions.
- a. Explain what it would mean for the assumptions for multiple linear regression inferences to be satisfied with student-to-faculty ratio, percentage of freshmen in the top 10% of their high school class, and percentage of applicants accepted as predictor variables for graduation rate.
- b. Use the computer output to obtain the coefficient of determination, R2. Interpret your result.
- c. How useful do the variables student-to-faculty ratio, percentage of freshmen in the top 10% of their high school class, and percentage of applicants accepted appear to be for predicting graduation rates at colleges and universities?
- d. Determine and interpret the standard error of the estimate, se.
- e. At the 5% significance level, do the data provide sufficient evidence to conclude that, taken together, student-to-faculty ratio, percentage of freshmen in the top 10% of their high school class, and percentage of applicants accepted are useful for predicting graduation rate?
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solutionStudents have asked these similar questions
The operations manager of a musical instrument distributor feels that the demand for Bass Drums may be related to the number of
television appearances by the popular rick group Green Shades during the previous month. The manager has collected the data shown
in the following table.
Demand for Bass Drums
3 6 7 5 10 8
Green Shades TV appearances
3 4 7 6 8 5
Develop the linear regression equation to forecast.
Forecast demand for Bass Drums when Green Shades’ TV appearances are 10.
Compute MSE and standard deviation for Problem 8.
QUESTION 2
XXX Electric Illuminating Company is doing a survey on the relationship between electricity
used in kilowatt-hours (thousand) and the number of rooms in a private single-family residence.
A random sample of 10 homes was selected and the electricity consumption recorded as below.
ii. Find a suitable linear regression equation ? = ? + ??.
iii. Determine the number of kilowatt-hours (thousand) for an eleven-room residence.
Do students with higher college grade point averages (GPAs) earn more than those graduates with lower GPAs?† Consider the following hypothetical college GPA and salary data (10 years after graduation).
GPA
Salary ($)
2.22
72,000
2.27
48,000
2.57
72,000
2.59
62,000
2.77
86,000
2.85
96,000
3.12
133,000
3.35
130,000
3.66
157,000
3.68
162,000
#1) Use these data to develop an estimated regression equation that can be used to predict annual salary 10 years after graduation given college GPA. (Let x = GPA, and let y = salary (in $). Round your numerical values to the nearest integer.) ŷ =
#2) Find the value of the test statistic. (Round your answer to two decimal places.)
#3)Find the p-value. (Round your answer to three decimal places.)
p-value =
Chapter A Solutions
Introductory Statistics (10th Edition)
Ch. A.1 - A. 1 Regarding linear equations in two or more...Ch. A.1 - Fill in the blanks. a. The graph of a linear...Ch. A.1 - Consider a linear equation y = b0 + b1x1 + b2x2. ...Ch. A.1 - Prob. 4ECh. A.1 - Prob. 5ECh. A.1 - Prob. 6ECh. A.1 - Banquet Room Rental. The banquet room at the...Ch. A.1 - Prob. 8ECh. A.1 - In each of Exercises A.9A.12, a. determine the...Ch. A.1 - In each of Exercises A.9A.12, a. determine the...
Ch. A.1 - In each of Exercises A.9A.12, a. determine the...Ch. A.1 - In each of Exercises A.9A.12, a. determine the...Ch. A.1 - Prob. 13ECh. A.1 - Prob. 14ECh. A.1 - Prob. 15ECh. A.1 - In each of Exercises A.13A.22, you are given the...Ch. A.1 - Prob. 17ECh. A.1 - Prob. 18ECh. A.1 - In each of Exercises A.13A.22, you are given the...Ch. A.1 - Prob. 20ECh. A.1 - Prob. 21ECh. A.1 - In each of Exercises A.13A.22, you are given the...Ch. A.1 - In each of Exercises A.23A.30, we have identified...Ch. A.1 - Prob. 24ECh. A.1 - Prob. 25ECh. A.1 - Prob. 26ECh. A.1 - In each of Exercises A.23A.30, we have identified...Ch. A.1 - Prob. 28ECh. A.1 - Prob. 29ECh. A.1 - Prob. 30ECh. A.1 - Why is it often preferable to use more than one...Ch. A.1 - Grade Prediction. The Statistics Department at a...Ch. A.1 - Prob. 33ECh. A.1 - Blood Pressure Medication. A medical researcher...Ch. A.1 - Infant Mortality Rate. A social scientist wants to...Ch. A.2 - Regarding a scatterplot matrix: a. Identify two of...Ch. A.2 - Regarding the criterion used to decide tits a set...Ch. A.2 - Prob. 38ECh. A.2 - Regarding the variables in a multiple linear...Ch. A.2 - Answer true or false to the following statements...Ch. A.2 - In each of Exercises A.41 and A.42, a. construct...Ch. A.2 - In each of Exercises A.41 and A.42, a. construct...Ch. A.2 - Advertising and Sales. A household-appliance...Ch. A.2 - Corvette Prices. The data on age and price for 10...Ch. A.2 - Graduation Kales. Graduation rates and what...Ch. A.2 - Custom Home Resales. Hanna Properties specializes...Ch. A.2 - Advertising and Sales. Refer to Exercise A.43. Use...Ch. A.2 - Prob. 48ECh. A.2 - Graduation Rates. Refer to Exercise A.45. Use the...Ch. A.2 - Custom Home Resales. Refer to Exercise A.46. Use...Ch. A.3 - Fill in the blanks. a. A measure of total...Ch. A.3 - In this section we introduced a descriptive...Ch. A.3 - Suppose x1, x2, and x3 are predictor variables and...Ch. A.3 - State the four conditions required for making...Ch. A.3 - In each of Exercises A.55A.59, assume the...Ch. A.3 - In each of Exercises A.55A.59, assume the...Ch. A.3 - In each of Exercises A.55A.59, assume the...Ch. A.3 - Prob. 58ECh. A.3 - In each of Exercises A.55A.59, assume the...Ch. A.3 - Fill in the blanks. a. When a sum of squares is...Ch. A.3 - Answer true or false to the following statements...Ch. A.3 - For a particular multiple linear regression...Ch. A.3 - For a particular multiple linear regression...Ch. A.3 - Advertising and Sales. Refer to Exercise A.43 on...Ch. A.3 - Corvette Prices. Refer to Exercise A.44 on page...Ch. A.3 - Graduation Rates. Refer to Exercise A.45 on page...Ch. A.3 - Custom Home Resales. Refer to Exercise A.46 on...Ch. A.3 - Advertising and Sales. Refer to Exercise A.43 on...Ch. A.3 - Corvette Prices. Refer to Exercise A.44 on page...Ch. A.3 - Graduation Rates. Refer to Exercise A.45 on page...Ch. A.3 - Custom Home Resales. Refer to Exercise A.46 on...Ch. A.3 - Suppose that R2 = 1 for a data set. What can you...Ch. A.3 - Suppose that R2 = 0 for a data set. What can you...Ch. A.3 - Use the regression identity for multiple linear...Ch. A.4 - Explain why the predictor variables are useless as...Ch. A.4 - Prob. 76ECh. A.4 - What test statistic is used for a hypothesis test...Ch. A.4 - Answer line or false to the following statements...Ch. A.4 - Advertising and Sales. Refer to Exercise A.43 oil...Ch. A.4 - Prob. 80ECh. A.4 - Graduation Rates. Refer to Exercise A.45 on page...Ch. A.4 - Custom-Home Resales. Refer to Exercise A.46 on...Ch. A.4 - Advertising and Sales. Referring to Exercise A.79,...Ch. A.4 - Prob. 84ECh. A.4 - Graduation Rates. Referring to Exercise A.81, use...Ch. A.4 - Prob. 86ECh. A.5 - What two regression inferences did we discuss in...Ch. A.5 - Prob. 88ECh. A.5 - A sample multiple linear regression equation...Ch. A.5 - Answer true or false to the following statements...Ch. A.5 - Advertising and Sales. Refer to Exercise A.43 on...Ch. A.5 - Corvette Prices. Refer to Exercise A.44 on page...Ch. A.5 - Graduation Rates. Refer to Exercise A.45 on page...Ch. A.5 - Custom-Home Resales. Refer to Exercise A.46 on...Ch. A.5 - Advertising and Sales. Referring to Exercise A.91,...Ch. A.5 - Corvette Sales. Referring to Exercise A.92, use...Ch. A.5 - Graduation Rates. Referring to Exercise A.93, use...Ch. A.5 - Custom-Home Resales. Referring to Exercise A.94,...Ch. A.6 - Fill in the blanks. a. In multiple linear...Ch. A.6 - Describe the difference between a residual and a...Ch. A.6 - Fill in the blanks. a. In multiple linear...Ch. A.6 - Answer true or false to the following statements...Ch. A.6 - Prob. 103ECh. A.6 - Corvette Prices. Refer to Exercise A.44 on page...Ch. A.6 - Advertising and Sales. Refer to Exercise A.43 on...Ch. A.6 - Corvette Prices. Refer to Exercise A.44 on page...Ch. A.6 - Graduation Rates. Refer to Exercise A.45 on page...Ch. A.6 - Custom-Homes Resales. Refer to Exercise A.46 on...Ch. A - For a linear equation y = b0 + b1x1 + b2x2 + b3x3,...Ch. A - Consider the linear equation y = 5 + 4x1 3x2. a....Ch. A - Answer true or false to each of the following...Ch. A - What kind of plot is useful for deciding whether...Ch. A - Prob. 5RPCh. A - Prob. 6RPCh. A - Regarding multiple linear regression analysis: a....Ch. A - Prob. 8RPCh. A - For each of the following sums of squares in...Ch. A - Prob. 10RPCh. A - Prob. 11RPCh. A - Suppose x1 and x2 are predictor variables for a...Ch. A - Fill in the blanks. a. The F-statistic for a test...Ch. A - Answer true or false to each of the following...Ch. A - Which interval is wider: (a) the 95% confidence...Ch. A - What plots did we use in this module to decide...Ch. A - Regarding analysis of residuals, decide in each...Ch. A - Annual Income. The Census Bureau collects data on...Ch. A - Annual Income. Refer to Problem 18 and the...Ch. A - Annual Income. Refer to Problem 18, Outputs...Ch. A - Recall from Chapter 1 (page 34 of your text) that...Ch. A - At the beginning of this module on page A-0, we...
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.Similar questions
- Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?arrow_forwardThe following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.arrow_forwardA researcher notes that, in a certain region, a disproportionate number of software millionaires were born around the year 1955. Is this a coincidence, or does birth year matter when gauging whether a software founder will besuccessful? The researcher investigated this question by analyzing the data shown in the accompanying table. Complete parts a through c below. a. Find the coefficient of determination for the simple linear regression model relating number (y) of software millionaire birthdays in a decade to total number (x) of births in the region. Interpret the result. The coefficient of determination is 1.___? (Round to three decimal places as needed.) This value indicates that 2.____ of the sample variation in the number of software millionaire birthdays is explained by the linear relationship with the total number of births in the region. (Round to one decimal place as needed.) b. Find the coefficient of determination for the simple linear regression model…arrow_forward
- Do students with higher college grade point averages (GPAs) earn more than those graduates with lower GPAs?† Consider the following hypothetical college GPA and salary data (10 years after graduation). GPA Salary ($) 2.22 72,000 2.29 48,000 2.57 72,000 2.59 64,000 2.77 88,000 2.85 98,000 3.12 133,000 3.35 130,000 3.66 157,000 3.68 162,000 Use these data to develop an estimated regression equation that can be used to predict annual salary 10 years after graduation given college GPA. (Let x = GPA, and let y = salary (in $). Round your numerical values to the nearest integer.) ŷ = Find the value of the test statistic. (Round your answer to two decimal places.) = Find the p-value. (Round your answer to three decimal places.) p-value =arrow_forwardCh 13. 7: Refer to the Lincolnville School District bus data. First, add a variable to change the type of engine (diesel or gasoline) to a qualitative variable. If the engine type is diesel, then set the qualitative variable to 0. If the engine type is gasoline, then set the qualitative variable to 1. Develop a regression equation using statistical software with maintenance cost as the dependent variable and age, odometer miles, miles since last maintenance, and engine type as the independent variables.arrow_forwardQuestion b. Movieflix, an online movie streaming service that offers a wide variety of award-winning TV shows, movies, animes, and documentaries, would like to determine the mathematical trend of memberships in order to project future needs. Year 2013 2014 2015 2016 2017 2018 2019 2020 2021 Membership (000s) 17 16 16 21 20 20 23 25 24 (i) Use the following time series data, to develop a regression equation relating memberships to time. (ii) Forecast 2023 membership. (iii) Assuming the COVID-19 pandemic comes to an end in 2021, in your opinion, how will this affect membership? Why? How will this affect your prediction?arrow_forward
- Suppose a study wants to predict the market price of a certain species of turtle (Y) based on the following independent variables indicated in the table. Based from the table, what is the equation of the multiple linear regression? (Round off up to two decimal places. Market Price = 0.07 - 0.40*weight + 1.51*length + 1.41*width + 0.80*age Market Price = - 0.40*weight + 1.51*length + 1.41*width + 0.80*age Market Price = 0.07 + 0.40*weight + 1.51*length + 1.41*width + 0.80*age Market Price = 0.07 - 0.40 + weight + 1.51 + length + 1.41 + width + 0.80 + agearrow_forward2(a).SSR in linear regression is equal to? SST-SSE SST+SSE SSE-SST SST x SSE SST/SSE correct option? (b).SSE or Sum of square erros show variations in between the populations variations within the populatios Type 1 error Family wise wrror Type 2 error variations within the samples correct option?arrow_forwardThe grades of a class of 9 students on a midterm report (x) and on the final examination (y) are as follows: Give the following: a. linear regression line and equation b. computation of the coefficient of determination ?^2 c. Computation of the coefficient of correlation ? d. Estimate the final examination grade of a student who received a grade of 85 on the midterm report.arrow_forward
- Consider the following linear regression model that relates income per capita in thousand dollars of a country i (GDP P Ci), with its percentage of the population in the agricultural sector (P Ai): Model : GDP P Ci = β0 + β1P Ai + ui (a) Explain in words how to interpret parameters β0 and β1. What sign do you think these parameters might have? Explain. (b) Draw the (population) regression line associated with this model assuming that parameters β0 and β1 have the sign you have indicated in answering question (2a). Explain the meaning of this regression line.arrow_forwardFinally, the researcher is interested in examining the regression model for knowledge, attitude and practices towards the COFLU-20. The following model was developed to forecast individual practices towards COFLU-20 using knowledge and attitude scores. P = α + β K + δ A where P = Practice towards COFLU-20 score K = Knowledge towards COFLU-20 score A = Attitude towards COFLU-20 score The data are processed using MINITAB and the output in Exhibit 1 below was obtained: Exhibit 1 The regression equation is ************* Predictor Coef SE t-ratio P Constant 4.755 0.462 10.282 0 Knowledge 0.8 0.039 2.055 0.041 Attitude 0.024 0.6 0.393 0.695 R-sq = 81.5% Analysis of Variance SOURCE DF SS…arrow_forward
arrow_back_ios
arrow_forward_ios
Recommended textbooks for you
- College AlgebraAlgebraISBN:9781305115545Author:James Stewart, Lothar Redlin, Saleem WatsonPublisher:Cengage LearningLinear Algebra: A Modern IntroductionAlgebraISBN:9781285463247Author:David PoolePublisher:Cengage LearningFunctions and Change: A Modeling Approach to Coll...AlgebraISBN:9781337111348Author:Bruce Crauder, Benny Evans, Alan NoellPublisher:Cengage Learning
College Algebra
Algebra
ISBN:9781305115545
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:Cengage Learning
Linear Algebra: A Modern Introduction
Algebra
ISBN:9781285463247
Author:David Poole
Publisher:Cengage Learning
Functions and Change: A Modeling Approach to Coll...
Algebra
ISBN:9781337111348
Author:Bruce Crauder, Benny Evans, Alan Noell
Publisher:Cengage Learning
Time Series Analysis Theory & Uni-variate Forecasting Techniques; Author: Analytics University;https://www.youtube.com/watch?v=_X5q9FYLGxM;License: Standard YouTube License, CC-BY
Operations management 101: Time-series, forecasting introduction; Author: Brandoz Foltz;https://www.youtube.com/watch?v=EaqZP36ool8;License: Standard YouTube License, CC-BY