Ten rats were randomly assigned a solid diet and 10 in a liquid diet. At the end of thefeeding period, the total protein intake x (in grams) and the weight gain y (in grams)were recorded for each of the rats. A straight line was fit to the 10 (x, y) data pointsfor each diet by the method of least squares. The least square prediction equationsfollows:Liquid: y = 110 - 0.75xSolid: y = 84 +3.66xInterpret the estimated y-intercept and slope for each diet.For each diet, find the predicted weight gain of a rat with a protein instake of 10grams.

Given regression line For liquid Y^=110-0.75X For Solid Y^=84+3.66X .

Answered: Ten rats were randomly assigned a solid…

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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The following regression model was estimated. Q is the number of meals served, P is the average price per meal (customer ticket amount, in dollars), Rxis the average price charged by competitors (in dollars), Ad is the local advertising budget for each outlet (in dollars), and I is the average income per household in each outlet's immediate service area. Least squares estimation of the regression equation on the basis of the 25 data observations resulted in the estimated regression coefficients and other statistics given in Table below. Variable Coefficient Standard Error of Coefficient Intercept 128832.240 69974.818 Price (P) Competitor Price (Px) | Advertising (Ad) Income () -19875.954 4100.856 15467.936 459.280 0.261 0.094 8.780 1.017 Coefficient of determination R =83.3% (a) Interpret the coefficients of independent variables. (b) Test the significance of independent variables at 5% level of Significance. (c) Interpret R? with the help of adjusted R2. (d) Test for the overall…
Consider the following data set: (x, y) : (1.0, 5.1), (1.25, 5.79), (1.5, 6.53), (1.75, 7.45), (2.0, 8.46) If the least squares approximation of the form beax is y=(3.07) e0.5056)x then the total error is: Select one: O a. 0.150 O b. 0.0015 O c. 1.150 O d. 0.015
The difference between a regression weight and a beta weight is: A regression weight assumes linearity. A beta weight is for the population while a regression weight is for the sample. A regression weight is less biased. A beta weight is a standardized regression weight.
If N = 150, (A) = 93, (B) = 112, (C) = 80, (BC) = 20 and (Ay) = 43, find the greatest and the least possible values of (AB) so that the data may be consistent.
Use the following information to answer questions 6 and 7. In a study, nine tires of a particular brand were driven on a track under identical conditions. Each tire was driven a particular controlled distance (measured in thousands of miles) and the tread depth was measured after the drive. Tread depth is measured in "mils." Here, 1 mil is 0.001 inch. The least-squares regression line was computed and added to a scatterplot of these data. On the plot, one data point is marked with an "X." The equation of the least-squares regression line is: Tread depth = 360.64 - 11.39 Miles The data value marked with "X" in the provided scatterplot has Tread Depth (Mils) 60 80 150 0 5 O a negative value for the residual. O a positive value for the residual. O a zero value for the residual. O a zero value for the correlation. 10 15 Miles (x 1000) 20 25 30
Consider the following data values for variables x and y: Ť 8 10 5 2 3 1 X 5 4 3 6 9 8 10 The regression coefficients were calculated as bo = 13.223 and b₁ = -1.257. Select the correct statement. Select one: O a. If x = 2, the estimated value of y from the regression line is -25.189. b. The least--squares regression line is y = 13.223-1.257x. c. An x-value of 11 resulted in an estimated y value of -1.861 d. The least--squares regression line is y = 1.257-13.223x. e. The relationship between x and y appears to be linear and positive.
Consider the following pairs of measurements: a. Use Stata to chart a scattergram for the data. Show the graph below. X 5 8 3 4 9 Y 6.2 3.4 7.5 8.1 3.2 b. Use Stata to estimate the least squares model between X and Y. Copy the output below and specify the least squares equation. c. What are SSE, s2, and s?
The U.S. online grocery market is estimating sales worth approximately $29.7 billion by 2021. One of the biggest situational factors that influence the amount spent by a customer is the distance that that customer lives from its closest grocery store. Using the OLS method, the simple regression equation was estimated as: y = 40 + 3.5x. Find 1) the predicted amount a customer spends if they live 10 miles from the closest grocery store, as well as 2) the error amount. Note: the observed amount spent by a customer that lives 10 miles away is $85.50. a) $75.00, $10.50 Ob) $75.00, -$10.50 c) $73.00, $12.50 d) $73.00, -$12.50
A math professor selects 8 students at random from her calculus class and asks them to record their study times. After two weeks, she gives an exam. the number of hours, x, of study time and the test score, y, yield the following sample data summary: Ex = 117 Ey = 660 8 %3| n 3= Ea2 = 1869 54638 9519 The professor is a bit surprised. a) Find the equation of the regression line. b) Use the regression line to predict the score of a student who studies for 20 hours over the two weeks.
A data set is given below. (a) Draw a scatter diagram. Comment on the type of relation that appears to exist between x and y. (b) Given that x=3.8333, sx=2.4014, y=3.6500, sy=1.7942, and r=−0.9539, determine the least-squares regression line. (c) Graph the least-squares regression line on the scatter diagram drawn in part (a).
For the model: Y= Bo + B1X1 + B2X2 + B3X3 + B4X4 + ɛ If sample size is n=30, what is the degree of freedom for Error? 4 5 29 25
This data table contians the listed prices and weights of the diamonds in 48 rings offered for sale in The Singapore Times. The prices are in Singapore dollars, with the weights in crats. Estimate the linear regression using weight as the explanatory variable and price as the response variable using the following two methods: a) Create a scatterplot with trendline (be sure to show the equation and R-square on the chart.) b) Use the Data Analysis Toolpak to do the work for you.

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