Statistics: The Art and Science of Learning from Data (4th Edition)
4th Edition
ISBN: 9780321997838
Author: Alan Agresti, Christine A. Franklin, Bernhard Klingenberg
Publisher: PEARSON
expand_more
expand_more
format_list_bulleted
Concept explainers
Question
Chapter 12, Problem 101CP
a.
To determine
Explain why it is sensible to set
b.
To determine
Explain why the distance is quadrupled when the velocity of the swing for the model
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solutionStudents have asked these similar questions
What does this plot show about the model being analysed?
Starfish coildots is a disease affecting approximately 40 different species of sea stars and several other echinoderms. A sample of 240 ochre starfish and 155 sunflower starfish found that 97 ochre starfish and 54 sunflower starfish showed signs of infection.
Is there evidence to suggest that the difference in the proportion of infected ochre starfish is greater than the proportion of infected sunflower starfish?
(a) Define the parameter(s) of interest using the correct notation. Then, state the null and alternative hypotheses for this study.
(b) Calculate the observed test statistic and state the distribution it follows (including degrees of freedom, if needed).
(c) Give the p-value, or a range of appropriate values for the p-value.
(d) Using the significance level α = 0.10, state your conclusions regarding the proportion of infected starfish in a plain English sentence.
(e) Determine the 90% confidence interval for the difference in the proportions of infected ochre starfish and…
a) explain on he strenght and variation of the model (multiple regression)
b) At a-value =0.01. test whether there is a significiant relationship between the dependent variable (y) and the independant variables x1, x2 and x3
Chapter 12 Solutions
Statistics: The Art and Science of Learning from Data (4th Edition)
Ch. 12.1 - Car mileage and weight The Car Weight and Mileage...Ch. 12.1 - Prob. 2PBCh. 12.1 - Predicting maximum bench strength in males For the...Ch. 12.1 - Prob. 4PBCh. 12.1 - Mu, not y For a population regression equation,...Ch. 12.1 - Prob. 6PBCh. 12.1 - Study time and college GPA Exercise 3.39 in...Ch. 12.1 - Prob. 8PBCh. 12.1 - Cell phone specs Refer to the cell phone data set...Ch. 12.1 - Prob. 10PB
Ch. 12.2 - t-score? A regression analysis is conducted with...Ch. 12.2 - Prob. 12PBCh. 12.2 - Confidence interval for slope Refer to the...Ch. 12.2 - Prob. 14PBCh. 12.2 - Strength through leg press The high school female...Ch. 12.2 - Prob. 16PBCh. 12.2 - More girls are good? Repeat the previous exercise...Ch. 12.2 - CI and two-sided tests correspond Refer to the...Ch. 12.2 - Advertising and sales Each month, the owner of Caf...Ch. 12.2 - Prob. 20PBCh. 12.2 - GPA and skipping classrevisited Refer to the...Ch. 12.2 - Prob. 22PBCh. 12.3 - Dollars and thousands of dollars If a slope is...Ch. 12.3 - Prob. 24PBCh. 12.3 - Sketch scatterplot Sketch a scatterplot,...Ch. 12.3 - Prob. 26PBCh. 12.3 - Body fat For the Male Athlete Strength data file...Ch. 12.3 - Prob. 28PBCh. 12.3 - SAT regression toward mean Refer to the previous...Ch. 12.3 - Prob. 30PBCh. 12.3 - GPA and study time Refer to the association you...Ch. 12.3 - Prob. 32PBCh. 12.3 - Does tutoring help? For a class of 100 students,...Ch. 12.3 - Prob. 34PBCh. 12.3 - Golf regression In the first round of a golf...Ch. 12.3 - Prob. 36PBCh. 12.3 - Food and drink sales The owner of Berthas...Ch. 12.3 - Prob. 38PBCh. 12.3 - Violent crime and single-parent families Use...Ch. 12.4 - Poor predicted strengths The MINITAB output shows...Ch. 12.4 - Prob. 42PBCh. 12.4 - Bench press residuals The figure is a histogram of...Ch. 12.4 - Predicting house prices The House Selling Prices...Ch. 12.4 - Predicting clothes purchases For a random sample...Ch. 12.4 - Prob. 46PBCh. 12.4 - ANOVA table for leg press Exercise 12.15 referred...Ch. 12.4 - Prob. 48PBCh. 12.4 - Variability and F Refer to the previous two...Ch. 12.4 - Understanding an ANOVA table For a random sample...Ch. 12.4 - Predicting cell phone weight Refer to the cell...Ch. 12.4 - Cell phone ANOVA Report the ANOVA table for the...Ch. 12.5 - Savings grow exponentially You invest 100 in a...Ch. 12.5 - Prob. 55PBCh. 12.5 - Prob. 56PBCh. 12.5 - Prob. 57PBCh. 12.5 - Prob. 58PBCh. 12.5 - Prob. 59PBCh. 12.5 - Prob. 60PBCh. 12.5 - Prob. 61PBCh. 12 - Prob. 62CPCh. 12 - Prob. 63CPCh. 12 - Prob. 64CPCh. 12 - Prob. 65CPCh. 12 - Prob. 66CPCh. 12 - Prob. 67CPCh. 12 - Prob. 68CPCh. 12 - Prob. 69CPCh. 12 - Prob. 70CPCh. 12 - Prob. 71CPCh. 12 - Prob. 72CPCh. 12 - Prob. 73CPCh. 12 - Prob. 74CPCh. 12 - World population growth The table shows the world...Ch. 12 - Prob. 76CPCh. 12 - Prob. 77CPCh. 12 - Prob. 78CPCh. 12 - Prob. 79CPCh. 12 - Prob. 81CPCh. 12 - Prob. 82CPCh. 12 - Prob. 83CPCh. 12 - Prob. 84CPCh. 12 - Prob. 85CPCh. 12 - Prob. 86CPCh. 12 - Prob. 87CPCh. 12 - Prob. 88CPCh. 12 - Prob. 89CPCh. 12 - Assumptions What assumptions are needed to use the...Ch. 12 - Assumptions fail? Refer to the previous exercise....Ch. 12 - Lots of standard deviations Explain carefully the...Ch. 12 - Decrease in home values A Freddie Mac quarterly...Ch. 12 - Population growth Exercise 12.57 about U.S....Ch. 12 - Multiple choice: Interpret r One can interpret r =...Ch. 12 - Multiple choice: Correlation invalid The...Ch. 12 - Multiple choice: Slope and correlation The slope...Ch. 12 - Multiple choice: Regress x on y The regression of...Ch. 12 - Multiple choice: Income and height University of...Ch. 12 - True or false The variables y = annual income...Ch. 12 - Prob. 101CPCh. 12 - Why is there regression toward the mean? Refer to...Ch. 12 - Prob. 103CPCh. 12 - Prob. 104CPCh. 12 - Prob. 105CPCh. 12 - Prob. 106CP
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
- Sports scientists want to use nuclear magnetic resonance spectroscopy, NMR, to predict the muscle fibre composition in the thighs of athletes. They obtained the data in the screenshot, which contains three variables: FTF – the percentage of fast twitch fibres in the muscle. T1 – the T1 relaxation time measured in ms. T2 – the T2 relaxation time measured in ms. Perform a multiple linear regression using the model FTF = b0 + b1T1 + b2T2. i) What are the values of the three coefficients in the equation? ii) What is the F statistic and P value for the regression? Do these indicate that the regression is significant? iii) Does adding the other NMR relaxation time, T2, to the predictive equation significantly improve the ability of NMR spectroscopy to predict muscle fibre type? Explain your conclusions.arrow_forward1. Obtain the regression of Y on X a' ´from the following table and estimate the blood pressure when age is 50. Age X Blood pressure Y 56 147 42 125 72 160 36 118 63 149 47 128 55 150 49 145 38 115 42 140 68 152 60 155 CS Scanned with CamScannerarrow_forward3. Regression analysis breaks scores on the DV into... (explain and give equations)arrow_forward
- The estimated least-squares regression equation for profit (in $100,000) is: y' = 2.5 + 0.054t Sales for time period 32 (t = 32) are 5% below the average of yearly sales. Forecast sales, including the seasonal component, for t = 32.arrow_forward'1) Interpret the following regression line y = 10.50 – 0.18x 2) Interpret the following coefficient of determination r? = 0.69 3) Interpret the following coefficient of correlation r =-0.83arrow_forwardWrinkle recovery angle and tensile strength are the two most important characteristics for evaluating the performance of crosslinked cotton fabric. An increase in the degree of crosslinking, as determined by ester carboxyl band absorbance, improves the wrinkle resistance of the fabric (at the expense of reducing mechanical strength). The accompanying data on x = absorbance and y = wrinkle resistance angle was read from a graph in the paper "Predicting the Performance of Durable Press Finished Cotton Fabric with Infrared Spectroscopy".† x 0.115 0.126 0.183 0.246 0.282 0.344 0.355 0.452 0.491 0.554 0.651 y 334 342 355 363 365 372 381 392 400 412 420 Here is regression output from Minitab: Predictor Constant absorb S = 3.60498 Coef 321.878 156.711 SOURCE Regression Residual Error Total SE Coef 2.483 6.464 R-Sq = 98.5% DF 1 9 10 SS 7639.0 117.0 7756.0 T 129.64 24.24 0.000 0.000 R-Sq (adj) = 98.3% MS 7639.0 13.0 F P 587.81 (a) Does the simple linear regression model appear to be…arrow_forward
- Wrinkle recovery angle and tensile strength are the two most important characteristics for evaluating the performance of crosslinked cotton fabric. An increase in the degree of crosslinking, as determined by ester carboxyl band absorbance, improves the wrinkle resistance of the fabric (at the expense of reducing mechanical strength). The accompanying data on x = absorbance and y = wrinkle resistance angle was read from a graph in the paper "Predicting the Performance of Durable Press Finished Cotton Fabric with Infrared Spectroscopy".t 半 0.115 0.126 0.183 0.246 0.282 0.344 0.355 0.452 0.491 0.554 0.651 334 342 355 363 365 372 381 392 400 412 420 Here is regression output from Minitab: Predictor Coef SE Coef P Constant 321.878 2.483 129.64 0.000 absorb 156.711 6.464 24.24 0.000 S = 3.60498 R-Sq = 98.5% R-Są (adj) - 98.3% SOURCE DF MS F P Regression 1 7639.0 7639.0 587.81 0.000 Residual Error 9 117.0 13.0 Total 10 7756.0 (a) Does the simple linear regression model appear to be…arrow_forwardWrinkle recovery angle and tensile strength are the two most important characteristics for evaluating the performance of crosslinked cotton fabric. An increase in the degree of crosslinking, as determined by ester carboxyl band absorbance, improves the wrinkle resistance of the fabric (at the expense of reducing mechanical strength). The accompanying data on x = absorbance and y = wrinkle resistance angle was read from a graph in the paper "Predicting the Performance of Durable Press Finished Cotton Fabric with Infrared Spectroscopy".t x 0.115 0.126 0.183 0.246 0.282 0.344 0.355 0.452 0.491 0.554 0.651 y 334 342 355 363 365 372 381 400 392 412 420 Here is regression output from Minitab: Predictor Constant absorb S = 3.60498 Coef 321.878 156.711 SOURCE Regression Residual Error Total R-Sq= 98.5% DF SE Coef 2.483 6.464 1 9 10 SS 7639.0 117.0 7756..0 T 129.64 24.24 P 0.000 0.000. R-Sq (adj) 98.3% MS 7639.0 13.0 F 587.81 (a) Does the simple linear regression model appear to be appropriate?…arrow_forwardThe least-squares regression equation is y = 689.9x + 14,803 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7256. Complete parts (a) through (d). (a) Predict the median income of a region in which 20% of adults 25 years and older have at least a bachelor's degree. (Round to the nearest dollar as needed.) . TOLED dian Income Media 55000- 20000- 15 20 25 30 35 40 45 50 55 60 Bachelor's 96 Qarrow_forward
- a) We conduct a regression of size on hhinc, owner, hhsize, hhsize2,and hhsize3. We do not include the constant. The regression output is reported in Table 3. Would you conclude that the home size increases with the household size? Interpret the sign and magnitude of the estimated coefficients of hhsize1, hhsize2, and hhsize3.arrow_forwardThe article "Earthmoving Productivity Estimation Using Linear Regression Techniques" (S. Smith, Journal of Construction Engineering and Management, 1999:133–141) presents the following linear model to predict earth-moving productivity (in m3 moved per hour): Productivity = - 297.877 + 84.787x, + 36.806x, + 151.680x, – 0.081x, – 110.517x5 - 0.267.x, – 0.016x,x, +0.107.x,x5 + 0.0009448x,x, – 0.244x;x, where X1 = number of trucks X2 = number of buckets per load X3 = bucket volume, in m³ X4 = haul length, in m X5 = match factor (ratio of hauling capacity to loading capacity) X6 = truck travel time, in s If the bucket volume increases by 1 m², while other independent variables are unchanged, can you determine the change in the predicted productivity? If so, determine it. If not, state what other information you would need to determine it. b. If the haul length increases by 1 m, can you determine the change in the predicted productivity? If so, determine it. If not, state what other…arrow_forwardConsider the simple regression model y = B, + B*t + u t = 1,2,.. ,T where u, = pu,-1 + & with Ipl < 1 and E (&) = 0, E (ɛ?) = a?, E(ɛɛs) = 0,t # s %3D %3D What are the consequences of having first order autoregressive autocorrelation? b. Derive the mean of autocorrelated u, 's. Derive the variance of autocorrelated u, 's. d. Derive the covariance of autocorrelated u, 's. Derive the correlation coefficient between u, and u,-1. a. с. е.arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
- MATLAB: An Introduction with ApplicationsStatisticsISBN:9781119256830Author:Amos GilatPublisher:John Wiley & Sons IncProbability and Statistics for Engineering and th...StatisticsISBN:9781305251809Author:Jay L. DevorePublisher:Cengage LearningStatistics for The Behavioral Sciences (MindTap C...StatisticsISBN:9781305504912Author:Frederick J Gravetter, Larry B. WallnauPublisher:Cengage Learning
- Elementary Statistics: Picturing the World (7th E...StatisticsISBN:9780134683416Author:Ron Larson, Betsy FarberPublisher:PEARSONThe Basic Practice of StatisticsStatisticsISBN:9781319042578Author:David S. Moore, William I. Notz, Michael A. FlignerPublisher:W. H. FreemanIntroduction to the Practice of StatisticsStatisticsISBN:9781319013387Author:David S. Moore, George P. McCabe, Bruce A. CraigPublisher:W. H. Freeman
MATLAB: An Introduction with Applications
Statistics
ISBN:9781119256830
Author:Amos Gilat
Publisher:John Wiley & Sons Inc
Probability and Statistics for Engineering and th...
Statistics
ISBN:9781305251809
Author:Jay L. Devore
Publisher:Cengage Learning
Statistics for The Behavioral Sciences (MindTap C...
Statistics
ISBN:9781305504912
Author:Frederick J Gravetter, Larry B. Wallnau
Publisher:Cengage Learning
Elementary Statistics: Picturing the World (7th E...
Statistics
ISBN:9780134683416
Author:Ron Larson, Betsy Farber
Publisher:PEARSON
The Basic Practice of Statistics
Statistics
ISBN:9781319042578
Author:David S. Moore, William I. Notz, Michael A. Fligner
Publisher:W. H. Freeman
Introduction to the Practice of Statistics
Statistics
ISBN:9781319013387
Author:David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:W. H. Freeman
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