5) Please answer the question and show your work in the space provided.Medhavi suspects that there is a relationship between the number of text messages high school studentssend and their academic achievement. To explore this, she asks a random sample of 52 students at herschool how many text messages they sent yesterday and what their grade point average (GPA) was duringthe most recent marking period. Her data are summarized in the scatter plot below. The least squaresregression line is also shown.The equation of the least squares regression line isGPA=3.8-0.005(TextsSent). Interpret thequantities -0.005 and 3.8 in the context of the data.4.254.00 -3.753.503.253.00 -2.752.50 -20406080100120140160Texts Sent

The question is based on a regression model Given reg. eq. : GPA = 3.8 - 0.005 ( Text sent )

Answered: 5) Please answer the question and show…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Researchers measured the percent body fat and the preferred amount of salt (percent weight/volume) for several children. Here are data for seven children salt: Preferred amount of salt x 0.2 0.3 0.4 0.5 0.6 0.8 1.1 Percent body fat y 20 30 22 30 38 23 30 Using your calculator or software, what is the equation of the least-squares regression line for predicting percent body fat from preferred amount of salt? (a) yˆ = 24.2 + 6.0 x (b) yˆ = 0.1 5 + 0.0 1x (c) yˆ = 6.0 + 24.2 x
The data in the table represent the number of licensed drivers in various age groups and the number of fatal accidents within the age group by gender. Complete parts (a) through (c) below. Click the icon to view the data table. ..... (a) Find the least-squares regression line for males treating the number of licensed drivers as the explanatory variable, x, and the number of fatal crashes, y, as the response variable. Repeat this procedure for females. Find the least-squares regression line for males. y =x+O %D/ (Round the x coefficient to three decimal places as needed. Round the constant to the nearest integer as needed.) Find the least-squares regression line for females. y = ý =x+O %3D (Round the x coefficient to three decimal places as needed. Round the constant to the nearest integer as needed.) (b) Interpret the slope of the least-squares regression line for each gender, if appropriate. How might an insurance company use this information? What is the correct interpretation of the…
The management at a company that sells and services exercise equipment would like to determine if there is a relationship between the number of minutes required to complete a routine service call and the number of machines serviced. A random sample of 12 records revealed the information available below concerning the number of machines serviced and the time (in minutes) to complete the routine service call. Complete parts a and b below. E Click the icon to view the data. .... a. Estimate the least squares regression equation. The regression equation is y=() x. (Round to two decimal places as needed.) b. If a gymnasium had nine machiìnes, how many minutes should the company expect a routine service call to require. A routine service call should require about minutes if there are nine machines. (Round to the nearest minute as needed.) - X Cost of Small Projects Data Number of Machines Service Time (minutes) 12 115 65 80 10 9 85 50 60 65 40 7 9. 3 11 95 4 45 5 11 35 105 Print Done
The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, y = b0 + b1x, for predicting the number of bids an item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Price in Dollars 23 26 31 40 48 Number of Bids 3 4 6 7 9 Table Step 5 of 6: Find the error prediction when x = 31. Round your answer to three decimal places.
Answer the 2 questions from the page with the question starting with "Give a practical interpretation..."
. A 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…
In a statistics class, a teacher had the students complete an activity in which they grabbed as many bite-sized pretzels as they could with their dominant hand, without crushing them. The teacher then measured their handspan in centimeters. The scatterplot displays the data the teacher collected along with the least-squares regression line. One student with a handspan of 23 cm grabbed 38 pretzels. This point is circled on the graph. What effect will the circled point have on the y-intercept? The y-intercept will not change with the addition of this point. The y-intercept will decrease because the point pulls the least-squares regression line toward it. The y-intercept will increase because the point pulls the least-squares regression line toward it. The y-intercept will increase because this point represents an extremely high number of pretzels grabbed with the dominant hand.
The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, y = bo + bjx, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age 38 43. 53 59 63 Bone Density 357 351 326 317 313 Table Copy Data Step 3 of 6: Find the estimated value of y when x = 59. Round your answer to three decimal places. I Tables E Keypad Answer How to enter your answer Keyboard Shortcuts Previous step answers Submit Answer O 2020 Hawkes Learning MacBook Air DD F1 F3 FS F11 F12 & + 1 2 3 4 5 6 7 8 9 %3D Q W E { [ Y } F J K L C V ? ption command command option .. .. リ V -
A corporation owns several companies. The planner for the corporation believes the amount spent on advertising can predict the total sales of the company. She gathers the following sales and advertising information from several of the companies for 2015 (in millions). Advertising 12.5 3.5 21.4 10.5 12.2 8.9 7.6 12.4 18.7 Sales 148 26 120 100 157 58 67 123 196 What is the simple regression line that can best predict the sales from the advertising expenditures using these data? Oŷ 84.15x 45.81 Oŷ = 7.52x + 20.57 ỹ = 3.45x – 45.12 Oŷ = 7.31x + 19.86
Suppose a doctor measures the height, x, and head circumference, y, of 11 children and obtains the data below. The correlation coefficient is 0.899 and the least squares regression line is y=0.185x+12.276. Complete parts (a) and (b) below. Height, x 27.75 25.75 26.75 25.75 28 26.5 25.75 26.75 27 27.25 27.25 Head Circumference, y 17.4 17.1 17.2 16.9 17.4 17.1 17.1 17.3 17.3 17.3 17.4 (a) Compute the coefficient of determination, R2. R2=nothing% (Round to one decimal place as needed.) (b) Interpret the coefficient of determination. Approximately nothing% of the variation in ▼ height head circumference is explained by the least-squares regression model. (Round to one decimal place as needed.)
Suppose a doctor measures the height, x, and head circumference, y, of 8 children and obtains the data below. The correlation coefficient is 0.941 and the least squares regression line is y = 0.244x + 10.794. Complete parts a and b below. Height, x Head Circumference, y 27.00 25.75 26.25 17.3 25.75 27.50 17.5 26.25 17.1 26.00 27.00 17.4 17.4 17.1 17.1 17.1 (a) Compute the coefficient of determination, R?. R2 =% (Round to one decimal place as needed.) (b) Interpret the coefficient of determination. % of the variation in height is explained by the least-squares regression model. (Round to one decimal place as needed.)
A study was conducted to investigate the effect of vehicle weight on gas mileage. The following random sample was collected where x is the weight of a vehicle in pounds and y is the miles per gallon. a. Write a sentence interpreting the value of the slope of the regression line. b. If a vehicle weighs 4000 pounds, what does the least-squares line predict for the miles per gallon? (Show your calculations.) Is this interpolation or extrapolation? Explain. c. What does the correlation coefficient tell us about the relationship between weight and gas mileage? d. Give a brief explanation of the meaning of the coefficient of determination in the context of this problem.

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