STAT.F/BUS.+ECO.PKG.:LOOSELEAF+MYLABSPL
13th Edition
ISBN: 9780135412428
Author: MCCLAVE
Publisher: PEARSON C
expand_more
expand_more
format_list_bulleted
Concept explainers
Videos
Question
Chapter 11.6, Problem 11.87ACB
a.
To determine
To locate: The 95% confidence interval for
To interpret: The results.
b.
To determine
To Locate: The 95% prediction interval for y.
To Interpret: The results.
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solution
Students have asked these similar questions
A 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…
The authors of a paper were interested in how the distance a deer mouse will travel for food is related to the distance from the food to the nearest pile of debris. Distances were measured in meters. The data and computer output are given below.
Distance from Debris
Distance Traveled
6.94
0.00
5.23
6.13
5.21
11.29
7.10
14.35
8.16
12.03
5.50
22.72
9.19
20.11
9.05
26.16
9.36
30.65
Simple Linear Regression Results:
Dependent Variable: Traveled
Independent Variable: Debris
Sample size: 9
R (correlation coefficient) = 0.5657
R-sq = 0.32002088
Estimate of error standard deviation 8.670711
Parameter estimates:
Parameter
Estimate
Std. Err.
Alternative
DF
T-Stat
P-Value
Intercept
-7.6854587
13.332196
≠ 0
7
-0.5764586
0.5824
Slope
3.2340908
1.7818117
≠ 0
7
1.8150575
0.1124
a)What is the least squares regression line for the output given above?
b) what is the predicted traveled distance given the distance from debris is 6.5 meters?
A sixth-grade teacher believes that there is a relationship between his students’ IQscores (y) and the numbers of hours (x) they spend watching television each week. Thefollowing table shows a random sample of 7 sixth-grade students.y 125 116 97 114 85 107 105x 5 10 30 16 41 28 21
Does the data provide sufficient evidence to indicate that the simple linear regressionmodel is appropriate to describe the relationship between x and y? Perform a model utilitytest at α = 0.05. (Give H0, Ha, rejection region, observed test statistic, P-value, decisionand conclusion.)Find the Pearson sample correlation coefficient between x and y. Then interpretthe result.
Chapter 11 Solutions
STAT.F/BUS.+ECO.PKG.:LOOSELEAF+MYLABSPL
Ch. 11.1 - In each case, graph the line that passes through...Ch. 11.1 - Give the slope and y-intercept for each of the...Ch. 11.1 - The equation for a straight line (deterministic...Ch. 11.1 - Refer to Exercise 11.3. Find the equations of the...Ch. 11.1 - Plot the following lines: a. y 4 + x b. y = 5 2x...Ch. 11.1 - Give the slope and y-intercept for each of the...Ch. 11.1 - Prob. 11.7LMCh. 11.1 - Prob. 11.8LMCh. 11.1 - If a straight-line probabilistic relationship...Ch. 11.1 - Congress voting on women's issues. The American...
Ch. 11.1 - Best-paid CEOs. Refer to Glassdoor Economic...Ch. 11.1 - Estimating repair and replacement costs of water...Ch. 11.1 - Forecasting movie revenues with Twitter. A study...Ch. 11.2 - The following table is similar to Table 11.2.It is...Ch. 11.2 - Refer to Exercise 11.14. After the least squares...Ch. 11.2 - Construct a scatterplot for the data in the...Ch. 11.2 - Consider the following pairs of measurements: a....Ch. 11.2 - Use the applet Regression by Eye to explore the...Ch. 11.2 - In business, do nice guys finish first or last?...Ch. 11.2 - State Math SAT scores. Refer to the data on...Ch. 11.2 - Lobster fishing study. Refer to the Bulletin of...Ch. 11.2 - Repair and replacement costs of water pipes. Refer...Ch. 11.2 - Joint Strike Fighter program. The Joint Strike...Ch. 11.2 - Software millionaires and birthdays. In Outliers:...Ch. 11.2 - Prob. 11.24ACICh. 11.2 - Ranking driving performance of professional...Ch. 11.2 - Sweetness of orange juice. The quality of the...Ch. 11.2 - Forecasting movie revenues with Twitter. Marketers...Ch. 11.2 - Charisma of top-level leaders. According to a...Ch. 11.2 - Ran kings of research universities. Refer to the...Ch. 11.2 - Prob. 11.30ACACh. 11.3 - Visually compare the scatterplots shown below. If...Ch. 11.3 - Calculate SSE and s2 for each of the following...Ch. 11.3 - Suppose you fit a least squares line to 26 data...Ch. 11.3 - Refer to Exercise 11.14 (p. 629). Calculate SSE,...Ch. 11.3 - Do nice guys really finish last in business? Refer...Ch. 11.3 - State Math SAT scores. Refer to the simple linear...Ch. 11.3 - Prob. 11.37ACBCh. 11.3 - Prob. 11.38ACBCh. 11.3 - Prob. 11.39ACBCh. 11.3 - Prob. 11.40ACICh. 11.3 - Prob. 11.41ACICh. 11.3 - Sweetness of orange juice. Refer to the study of...Ch. 11.3 - Rankings of research universities. Refer to the...Ch. 11.3 - Life tests of cutting tools. To Improve the...Ch. 11.4 - Construct both a 95% and a 90% confidence interval...Ch. 11.4 - Consider the following pairs of observations: a....Ch. 11.4 - Refer to Exercise 11.46. Construct an 80% and a...Ch. 11.4 - Do the accompanying data provide sufficient...Ch. 11.4 - State Math SAT Scores. Refer to the SPSS simple...Ch. 11.4 - Lobster fishing study. Refer to the Bulletin of...Ch. 11.4 - Prob. 11.51ACBCh. 11.4 - Prob. 11.52ACBCh. 11.4 - Estimating repair and replacement costs of water...Ch. 11.4 - Prob. 11.54ACBCh. 11.4 - Prob. 11.55ACICh. 11.4 - Beauty and electoral success. Are good looks an...Ch. 11.4 - Prob. 11.57ACICh. 11.4 - Prob. 11.58ACICh. 11.4 - Prob. 11.59ACICh. 11.4 - Prob. 11.60ACICh. 11.4 - Rankings of research universities. Refer to the...Ch. 11.4 - Prob. 11.62ACACh. 11.4 - Does elevation impact hitting performance in...Ch. 11.5 - Explain what each of the following sample...Ch. 11.5 - Describe the slope of the least squares line if a....Ch. 11.5 - Construct a scatterplot for each data set. Then...Ch. 11.5 - Calculate r2 for the least squares line in each of...Ch. 11.5 - Use the applet Correlation by Eye to explore the...Ch. 11.5 - In business, do nice guys finish first or last?...Ch. 11.5 - Going for it on fourth-down in the NFL Each week...Ch. 11.5 - Lobster fishing study. Refer to the Bulletin of...Ch. 11.5 - RateMyProfessors.com. A popular Web site among...Ch. 11.5 - Last name and acquisition timing. Refer to the...Ch. 11.5 - Women in top management. An empirical analysis of...Ch. 11.5 - Prob. 11.74ACICh. 11.5 - Prob. 11.75ACICh. 11.5 - Prob. 11.76ACICh. 11.5 - Prob. 11.77ACICh. 11.5 - Prob. 11.78ACICh. 11.5 - Evaluation of an imputation method for missing...Ch. 11.5 - Prob. 11.80ACICh. 11.5 - Prob. 11.81ACACh. 11.6 - Consider the followings of measurements: a...Ch. 11.6 - Consider the pairs of measurements shown in the...Ch. 11.6 - In fitting a least squares line to n = 10 data...Ch. 11.6 - Prob. 11.86ACBCh. 11.6 - Prob. 11.87ACBCh. 11.6 - Prob. 11.88ACBCh. 11.6 - Prob. 11.89ACBCh. 11.6 - Prob. 11.90ACBCh. 11.6 - Prob. 11.91ACICh. 11.6 - Ranking driving performance of professional...Ch. 11.6 - Spreading rate of spilled liquid Refer to the...Ch. 11.6 - Removing nitrogen from toxic wastewater. Highly...Ch. 11.6 - Predicting quit rates In manufacturing The reasons...Ch. 11.6 - Life tests of cutting tools Refer to the data...Ch. 11.7 - Prices of recycled materials. Prices of recycled...Ch. 11.7 - Thickness of dust on solar cells. The performance...Ch. 11.7 - Management research In Africa. The editors of the...Ch. 11.7 - An MBAs work-life balance. The importance of...Ch. 11 - In fitting a least squares line ton= 15 data...Ch. 11 - Consider the following sample data. a. Construct a...Ch. 11 - Consider the following 10 data points. a. Plot the...Ch. 11 - Drug controlled-release rate study. The effect of...Ch. 11 - Metaskills and career management. Effective...Ch. 11 - Burnout of human services professionals. Emotional...Ch. 11 - Retaliation against company whistle-blowers....Ch. 11 - Extending the life of an aluminum smelter pot. An...Ch. 11 - Diamonds sold at retail. Refer to the Journal of...Ch. 11 - Sports news on local TV broadcasts. The Sports...Ch. 11 - Evaluating managerial success. An observational...Ch. 11 - Doctors and ethics. Refer to the Journal of...Ch. 11 - FCAT scores and poverty. In the state of Florida,...Ch. 11 - Monetary values of NFL teams. Refer to the Forbes...Ch. 11 - Evaluating a truck weigh-in-motion program. The...Ch. 11 - Energy efficiency of buildings. Firms conscious of...Ch. 11 - Forecasting managerial needs. Managers are an...Ch. 11 - Prob. 11.118ACACh. 11 - Prob. 11.119CTCCh. 11 - Prob. 11.120CTC
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_forwardThe Update to the Task Force Report on Blood Pressure Control in Children [12] reported the observed 90th per-centile of SBP in single years of age from age 1 to 17 based on prior studies. The data for boys of average height are given in Table 11.18. Suppose we seek a more efficient way to display the data and choose linear regression to accomplish this task. age sbp 1 99 2 102 3 105 4 107 5 108 6 110 7 111 8 112 9 114 10 115 11 117 12 120 13 122 14 125 15 127 16 130 17 132 Do you think the linear regression provides a good fit to the data? Why or why not? Use residual analysis to justify your answer. Am I supposed to run a residual plot and QQ-plot for this question?arrow_forward
- A group of Maternal and Child Health public health practitioners are interested in the relationship between bacterial vaginosis (BV) and a number of negative health outcomes. Suppose the research team gathers information on a group of participants, and constructs a multiple linear regression model looking at the relationship between BV and depression, controlling for maternal age. The following is a computerized output displaying the results of their analysis.Parameter Intercept Maternal Age DepressionEstimate StandardError tValue Pr>|t|0.2186206635 -.0046496845 0.19124124150.06635040 0.00221338 0.031518843.29 0.0010 -2.10 0.0360 6.07 <.0001 A) What are the dependent and independent variables in this investigation?B) Based on the information above, was the research team justified in controlling for maternal age in this population? Why or why not?C) Write out the model in symbols. Round to 3 decimal places.D) Is there a significant association between BV and depression?arrow_forwardThe owner of Showtime Movie Theaters, Inc., would like to predict weekly gross revenueas a function of advertising expenditures. Historical data for a sample of eight weeks follow. Weekly GrossRevenue($1000s) Television Advertising($1000s) Newspaper Advertising($1000s) 96 5.0 1.5 90 2.0 2.0 95 4.0 1.5 92 2.5 2.5 95 3.0 3.3 94 3.5 2.3 94 2.5 4.2 94 3.0 2.5 a. Develop an estimated regression equation with the amount of televisionadvertising as the independent variable.b. Develop an estimated regression equation with both television advertising and newspaper advertising as the independent variables. c. Is the estimated regression equation coefficient for television advertisingexpenditures the same in part (a) and in part (b)? Interpret the coefficient in each case. d. Predict weekly gross revenue for a week when $3500 is spent on television advertising and $1800 is spent on newspaper advertising.arrow_forwardA mail-order business selling personal computer supplies, software and hardware maintains a centralized warehouse. Management is currently examining the process of distribution from the warehouse and wants to study the factors that affect the warehouse distribution costs. Data collected over 24 random months contain the warehouse’s distribution cost (in thousands of Rands), the sales (in thousands of Rands) and the number of orders received. A multiple linear regression model was fitted to the data by using Stat1.2. Use the output to answer the questions that follow by typing only the letter of the correct option in the answer boxes. Variablesy: Warehouse Distribution Costx1: Salesx2: Number of Orders Model Fitting StatisticsR2 = 0.8504Adj R2: ? Regression Coefficients Beta Parameter Standard b Parameter Standard Estimates…arrow_forward
- The monthly premium quoted by an insurance company for a critical illness policy was collected from a sample of 6 adult male smokers at different age. The data for the sample are shown: Age 28 25 50 39 47 31 Premium ($) 75 40 175 125 250 105 Using Age to predict premium, the Linear Regression equation is given by: ŷ =6.556X−112 and r2=0.813y^=6.556X−112 and r2=0.813 a. Identify the independent and Dependent variables. Dependent: Age Premium Independent: Age Premium b. Determine the slope. Slope = Slope = Round to 3 decimal places c. Determine |r||r| . |r|=|r|= Round to 3 decimal places d. Interpret rr : and e. Determine critical r value at 5% significance level and determine if there is a significant linear correlation exists. |r| critical=|r| critical= Round to 3 decimal places Linear Correlation:Linear Correlation: Significant Not Significant f. Predict the monthly premium for a 40 years old adult male smoker.…arrow_forwardA company trains its employees with instructional videos and claims that the amount of time, in hours, spent training is linearly related to an increase in productivity. The company selected a random sample of five employees to test its claim. The data were used to create the computer output for a least-squares linear regression, shown in the table. Variable DF Estimate SE Intercept 1 3.6 1.1489 Hours 1 0.8 0.3464 Which of the following is the correct test statistic and number of degrees of freedom? t=2.31 with 4 degrees of freedom A t=2.31 with 3 degrees of freedom B t=2.31 with 5 degrees of freedom C t=3.13 with 1 degree of freedom D t=3.13 with 3 degrees of freedom Earrow_forwardthe following table lists democrats spending thousands of dollars by statewide office and the percentage of the popular vote they received in their districts Spending:11.5 | 51.1 | 17.9 | 4.9 | 12.9 | 20.5 | 76.4 Percent:33.4 | 12.8 | 61.2 | 50.2 | 78.1 | 14.1 |49.9 does a sting linear correlation exist between democratic spending and a % of voters received, if so how and answer a. Find a regression model ax+b for percentage of votes received as a function of democratic spending b. If a democratic politician spent $60,000 on a campaign, what % of the vote should be expected to receive? Is it interpolation or extrapolation, why? c. If a democrat received a quarter of the votes, what would you expect the democrat to have spent?arrow_forward
- The following table gives information on the amount of sugar (in grams) and the calorie count in one serving of a sample of varieties of Kellogg's cereal. Find the predictive regression equation of the number of calories on the amount of sugar. Sugar (grams) 6 15 12 11 8 6 7 4 9 14 20 13 3 Calories 120 200 150 110 120 80 190 120 120 190 190 120 120arrow_forwardThe U.S. Postal Service is attempting to reduce the number of complaints made by the public against its workers. To facilitate this task, a staff analyst for the service regresses the number of complaints lodged against an employee last year on the hourly wage of the employee for the year. The analyst ran a simple linear regression in SPSS. The results are shown below. Table 7: Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .854a .730 .695 6.6235 a. Predictors: (Constant), Hourly Wage Table 8: ANOVA ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 1918.458 1 1918.458 129.783 .000a Residual 709.567 48 14.782 Total 2628.025 49 a. Predictors: (Constant), Hourly Wage b. Dependent Variable: Number of Complaints Table 9: Coefficients Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t…arrow_forwardThe U.S. Postal Service is attempting to reduce the number of complaints made by the public against its workers. To facilitate this task, a staff analyst for the service regresses the number of complaints lodged against an employee last year on the hourly wage of the employee for the year. The analyst ran a simple linear regression in SPSS. The results are shown below. Table 7: Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .854a .730 .695 6.6235 a. Predictors: (Constant), Hourly Wage Table 8: ANOVA ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 1918.458 1 1918.458 129.783 .000a Residual 709.567 48 14.782 Total 2628.025 49 a. Predictors: (Constant), Hourly Wage b. Dependent Variable: Number of Complaints Table 9: Coefficients Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t…arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
College AlgebraAlgebraISBN:9781305115545Author:James Stewart, Lothar Redlin, Saleem WatsonPublisher:Cengage Learning
Linear Algebra: A Modern IntroductionAlgebraISBN:9781285463247Author:David PoolePublisher:Cengage Learning
Functions and Change: A Modeling Approach to Coll...AlgebraISBN:9781337111348Author:Bruce Crauder, Benny Evans, Alan NoellPublisher:Cengage Learning
Glencoe Algebra 1, Student Edition, 9780079039897...AlgebraISBN:9780079039897Author:CarterPublisher:McGraw Hill
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
Glencoe Algebra 1, Student Edition, 9780079039897...
Algebra
ISBN:9780079039897
Author:Carter
Publisher:McGraw Hill
Correlation Vs Regression: Difference Between them with definition & Comparison Chart; Author: Key Differences;https://www.youtube.com/watch?v=Ou2QGSJVd0U;License: Standard YouTube License, CC-BY
Correlation and Regression: Concepts with Illustrative examples; Author: LEARN & APPLY : Lean and Six Sigma;https://www.youtube.com/watch?v=xTpHD5WLuoA;License: Standard YouTube License, CC-BY