
MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
expand_more
expand_more
format_list_bulleted
Question
![### Regression Analysis on Desired Weight
In a study involving a statistics class, the heights and responses to the question, "How much would you like to weigh?" were collected from 126 women (\(n = 126\)). A regression analysis was performed using the variables:
- \(y\): Desired weight (in pounds)
- \(x\): Height (in inches)
The regression equation derived from the data is:
\[ \text{Estimated mean desired weight} = -65.4 + 2.90 \times (\text{Height}) \]
### Key Questions
**b. Notation for the Slope:**
- Is the proper notation for the slope of this equation \(b_1\) or \(\beta_1\)?
Respond with: \(b_1\) or \(B_1\)
**Why?**
- Respond with: Sample or Population
This exercise helps to understand the appropriate notation based on whether the results relate to a sample or a population.](https://content.bartleby.com/qna-images/question/235449c2-9daa-42cc-8a69-02bbb9cd6e17/16127c75-44c1-4a4f-936c-8e2595f9d431/hnjv6j_thumbnail.jpeg)
Transcribed Image Text:### Regression Analysis on Desired Weight
In a study involving a statistics class, the heights and responses to the question, "How much would you like to weigh?" were collected from 126 women (\(n = 126\)). A regression analysis was performed using the variables:
- \(y\): Desired weight (in pounds)
- \(x\): Height (in inches)
The regression equation derived from the data is:
\[ \text{Estimated mean desired weight} = -65.4 + 2.90 \times (\text{Height}) \]
### Key Questions
**b. Notation for the Slope:**
- Is the proper notation for the slope of this equation \(b_1\) or \(\beta_1\)?
Respond with: \(b_1\) or \(B_1\)
**Why?**
- Respond with: Sample or Population
This exercise helps to understand the appropriate notation based on whether the results relate to a sample or a population.
Expert Solution
This question has been solved!
Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.
Step by stepSolved in 2 steps

Knowledge Booster
Similar questions
- The accompanying table shows a portion of data consisting of the selling price, the age, and the mileage for 20 used sedans. Selling Price 13,532 13,740 Age Miles 8. 61,456 54,394 11,954 9 42,428 Click here for the Excel Data File a. Determine the sample regression equation that enables us to predict the price of a sedan on the basis of its age and mileage. (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.) [If you are using R to obtain the tput, then first enter the following command at the prompt: optic scientific notation.] ipen=D10). This will ensure that the output is not in Pr ice + Age + Miles. b. Interpret the slope coefficient of Age. The slope coefficient of Age is -359.04, which suggests that for every additional year of age, the predicted price of car decreases by $359.04. O The slope coefficient of Age is -0.09, which suggests that for every additional year of age, the predicted price of car decreases by $0.09. The slope…arrow_forwardYou need to determine the slope of the regression line for a data set. The sums of the variables are given below. n = 14 Ex = 146.5 Ey = 993 Exy = 10,427 Ex2 = 1552 Ey? : = 70,510.5 Find the slope, only. Round the answer to the thousandths place.arrow_forwardUsing your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported as y = 42.52x + 86.52 and the r = 0.67. What percentage of the variation in y can be explained by the variation in the values of x? pi = % (Report exact answer, and do not enter the % sign)arrow_forward
- Find the regression equation, letting the diameter be the predictor (x) variable. Find the best predicted circumference of a marble with a diameter of 1.8 cm. How does the result compare to the actual circumference of 5.7 cm? Use a significance level of 0.05. Baseball Basketball Golf Soccer Tennis Ping-Pong Volleyball 7.5 21.4 4.0 Diameter Circumference 23.6 23.9 75.1 4.3 22.1 13.5 69.4 7.1 22.3 12.6 67.2 Click the icon to view the critical values of the Pearson correlation coefficient r. The regression equation is y= 0 (Round to five decimal places as needed.) + X.arrow_forwardYou are studying how a penguin's flipper length (in mm) explains its body mass (in grams) using linear regression. You choose a non-directional alternative to be safe. You calculate an R2=0.7621. What is the interpretation of this value? O76.21% of the variability in body mass is explained by the flipper length. O 76.21% of the variability in flipper length is explained by the body mass. 0 Flipper length and body mass have a positive relationship becase R² is positive O76.21% of the body mass values will be inside the confidence intervalarrow_forwardThe ages (in years) and weights (in pounds) of all wide receivers for a football team are listed. Find the coefficient of variation for each of the two data sets. Then compare the results. Click the icon to view the data sets. CV. weights = ☐ % (Round to one decimal place as needed.) CV = ages ☐ % (Round to one decimal place as needed.) Compare the results. What can you conclude? A. Ages are more variable than weights for all wide receivers on this team. B. Ages and weights for all wide receivers on this team have about the same amount of variability. C. Weights are more variable than ages for all wide receivers on this team.arrow_forward
- Lillian conducted a small survey of her friends and family. She asked them how many hours per week they spend reading digital documents (newspapers, blogs, books, etc.), and their age. She created the scatter plot below with the results she obtained. Draw the regression line that best represents this scatter plot and determine its equation.arrow_forwardUsing your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported asˆy=−29.73x+47.69 and the r=−0.588What proportion of the variation in y can be explained by the variation in the values of x?Report answer as a percentage accurate to one decimal place.arrow_forwardA professor at the University of Alabama was interested in evaluating the relationship between family support and delinquency. Using data collected on 4545 families, the researcher used regression to analyze the relationship. The results are presented below. Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 Family supportb . Enter a. Dependent Variable: Delinquency b. All requested variables entered. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .249a .062 .062 1.59168 a. Predictors: (Constant), Family support ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 759.204 1 759.204 299.671 <.001b Residual 11479.107 4531 2.533 Total 12238.311 4532 a. Dependent Variable: Delinquency b. Predictors: (Constant), Family support…arrow_forward
- Heights and answers to the question, "How much would you like to weigh?" were recorded for n=126 women in a statistics class. A regression equation for y=desired weight (in pounds) and x=height (in inches) is Estimated mean desired weight= - 65.4 + 2.90 (Height) D = bo + bịx a. What is the value of the slope of this regression equation?arrow_forwardUsing your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported as . 72.45х + 93.26 y = - 0.23. and the r = What percentage of the variation in y can be explained by the variation in the values of x? r2 = % (Report exact answer, and do not enter the % sign)arrow_forwardI need the right answer to this problem.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 Inc
Probability and Statistics for Engineering and th...StatisticsISBN:9781305251809Author:Jay L. DevorePublisher:Cengage Learning
Statistics 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:PEARSON
The Basic Practice of StatisticsStatisticsISBN:9781319042578Author:David S. Moore, William I. Notz, Michael A. FlignerPublisher:W. H. Freeman
Introduction 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