You are interesting in how rats' weights influence their running speed. For a group of 6 rats,you weigh them (in kg) and then time them in a race (in s). The data are given in the followingtable.SubjectABСOEDEWeight(kg)Time (s)1.10.80.90.71.21.1FFind the regression line that represents the relationship between your predictor variable(Weight) and your criterion variable (Time).SP or SSXY = [Select]SSX or SSXX= [Select]110907080100SSY or SSYY = [Select]85The slope of the line (b) = [Select]The intercept of the line (a) = [Select]Find the standard error of the estimate for the regression above:[Select]

Answered: you weigh them (in kg) and then time…

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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Bookstore sales revisited Recall the data we saw inChapter 6, Exercise 3 for a bookstore. The manager wantsto predict Sales from Number of Sales People Working. Number of SalesPeople Working Sales (in $1000)2 103 117 139 1410 1810 2012 2015 2216 2220 26 Dependent variable is SalesR-squared = 93.2,s = 1.477 Variable CoefficientIntercept 8.1006Num_Workers 0.9134 a) Write the regression equation. Define the variablesused in your equation.b) What does the slope mean in this context?c) What does the y-intercept mean in this context? Is itmeaningful?d) If 18 people are working, what Sales do you predict?e) If sales for the 18 people are actually $25,000, what isthe value of the residual?f) Have we overestimated or underestimated the sales?
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x 150 180 130 120 90 190 (a) x=160 calories (b) x=100 calories Sodium, y 430 480 320 360 290 550 (c) x=140 calories (d) x=50 calories Find the regression equation. y=nothingx+(nothing) (Round to three decimal places as needed.) Choose the correct graph below. A. 02000560CaloriesSodium (mg) A scatterplot has a horizontal axis labeled "Calories" from 0 to 200 in increments of 20 and a vertical axis labeled "Sodium (in milligrams)" from 0 to 560 in increments of…
Prehistoric pottery vessels are usually found as sherds (broken pieces) and are carefully reconstructed if enough sherds can be found. Information taken from a study provides data relating x = body diameter in centimeters and y = height in centimeters of prehistoric vessels reconstructed from sherds found at a prehistoric site. The following Minitab printout provides an analysis of the data. Predictor Coef SE Coef T P Constant -0.233 2.429 -0.09 0.929 Diameter 0.7948 0.1671 5.33 0.001 S = 4.10980 R-Sq = 80.3% (a) The standard error Se of the linear regression model is given in the printout as "S." What is the value of Se? (b) The standard error of the coefficient of the predictor variable is found under "SE Coef." Recall that the standard error for b is Se Σx2 − 1 n (Σx)2 . From the Minitab display, what is the value of the standard error for the slope b?
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Post secondary education information was examined for a random selection of states. The data below show the number of community colleges in the number of universities for each particular state. Community: 12, 17, 13, 10, 8 University: 4, 6, 5, 4, 3 A. Create a scatterplot of the given data sets B. Find the correlation coefficient of the sets of data. C. Create the equation of the regression line for the data and evaluate it when X=300.
Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $105 million. Use a significance level of a = 0.05. Budget ($)in Millions Gross ($) in Millions 41 23 114 75 78 47 120 64 10 59 127 22 12 150 2 0 127 18 111 65 113 112 102 94 64 98 211 41 22 288 57 Click the icon to view the critical values of the Pearson correlation coefficient r. ..... x. (Round to one decimal place as needed.) The regression equation is = + The best predicted gross for a movie with a $105 million budget is $ million. (Round to one decimal place as needed.)
Life expectancy in the United States has been rising since the nineteenth century. The table shows the U.S. life expectancy in selected years. Year 1950 1960 1970 1980 1990 2000 Life expectancy at birth 68.2 69.7 70.8 73.7 75.4 77 a. Let t represent the number of years after 1950, and plot the data. Draw a line a best fit for the data points. 80+ 76- 5 10 15 20 25 30 35 40 45 50 Draw: 72+ 64- 60+ 56 52 48- 44 Clear All

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you weigh them (in kg) and then time them in a race (in s). The data are given in the following table. Subject Weight (kg) Time (s) A B C D E F Find the regression line that represents the relationship between your predictor variable 1.1 0.8 0.9 0.7 1.2 1.1 110 90 70 80 100 85