Based on a sample of n = 26, the least-squares method was used to develop the prediction line Y, = 4 + 5X,. In addition, Syx = 1.8, X= 9, and E (X, -X)2 = 26, Complete parts (a) and (b) below.i=1Click here for page 1 of critical values of t. Click here for page 2 of critical values of t.a. Construct a 95% confidence interval estimate of the population mean response for X = 5.26.0036 sHyx = 5s 31.9964(Round to four decimal places as needed.)

Answered: Based on a sample of n = 26, the…

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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Suppose that a researcher, using data on 150 randomly selected bicycles, estimates the OLS regression: Price=672.65-2.12x Weight, (185.8) (0.42) where Price measures the price of the th bike in dollars and Weight measures the weight of the th bike in kilograms. The 99% confidence interval for the intercept, ßo, will be (, ). (Round your answers to two decimal places.)
Cardiorespiratory fitness is widely recognized as a major component of overall physical well-being. Direct measurement of maximal oxygen uptake (VO2max) is the single best measure of such fitness, but direct measurement is time-consuming and expensive. It is therefore desirable to have a prediction equation for VO2max in terms of easily obtained quantities. A sample is taken and variables measured are age (years), time necessary to walk 1 mile (mins), and heart rate at the end of the walk (bpm) in addition to the VO2 max uptake. The following output is from a multiple regression. Based on the F-test alone, what is the correct conclusion about the regression slopes? We did not find significant evidence to conclude that at least one slope differs from zero. 2) We do not have the dataset, therefore, we are unable to make a conclusion about the slopes. 3) All the regression slopes do not equal zero.…
Suppose that you have estimated coefficients for the regression model Y = B₁ + B₁X₁ + ß2X2 + ß3X3. Test the hypothesis that all three of the predictor variables are equal to 0, given the analysis of variance shown on the right. Use α = 0.05. Click here to view page 1 of a table of critical values of F. Click here to view page 2 of a table of critical values of F. Choose the correct null and alternartive hypotheses below. A. Ho: B₁ B₂ =B3 = 0 H₁: at least one ß; #0 C. Ho: B₁ B₂ = 3 = 0 H₁: B₁0, B₂0, B3 > 0 Find the critical value. The critical value is (Round to two decimal places as needed.) Source Regression Residual Error DF SS 3 9,654 23 2,400 B. Hō: at least one ß; ‡0 H₁: B₁ =B₂ =B3 = 0 D. H₁: B₁ = P₂ = ³3 = 0 H₁: B₁ B₂ B3 0 MS
Suppose a least-squares regression line is given by ModifyingAbove y with caret equals 4.302 x minus 3.293y=4.302x−3.293. What is the mean value of the response variable if xequals=2020? mu Subscript ModifyingAbove y with caret vertical line 20μy20equals=nothing (Round to one decimal place as needed.) Enter your answer in the answer box.
5
Based on a sample of n=15, the least-squares method was used to develop the prediction line Yi=6+2Xi. In addition, SYX=1.5, X=3 and ∑i=1nXi−X2=15. Complete parts (a) and (b) below. Click here to view page 1 of the table of the critical values of t. LOADING... Click here to view page 2 of the table of the critical values of t. LOADING... a. Construct a 90% confidence interval estimate of the population mean response for X=2. enter your response here≤μY|X=2≤enter your response here (Round to two decimal places as needed.) b. Construct a 90% prediction interval of an individual response for X=2. enter your response here≤YX=2≤enter your response here (Round to two decimal places as needed.)
The data from exercise 3 follow. xi 2 6 9 13 20 yi 7 18 9 26 23 The estimated regression equation is = 7.6 + .9x. What is the value of the standard error of the estimate (to 4 decimals)? What is the value of the t test statistic (to 2 decimals)? What is the p-value? Use Table 1 of Appendix B.Selectless than .01between .01 and .02between .02 and .05between .05 and .10between .10 and .20between .20 and .40greater than .40Item 3 What is your conclusion ( = .05)?SelectConclude a significant relationship exists between x and yCannot conclude a significant relationship exists between x and yItem 4 Use the F test to test for a significant relationship. Use = .05.Compute the value of the F test statistic (to 2 decimals). What is the p-value?Selectless than .01between .01 and .025between .025 and .05between .05 and .10greater than .10Item 6 What is your conclusion?SelectConclude a significant relationship exists between x and yCannot conclude a significant relationship exists…
A repeated measures experiment investigates if people can tickle themselves. A mean difference of 3.04 milliseconds is found between the Tickled By Self (485.17ms) and Tickled By Experimenter (482.13ms) means for 9 participants (NB: conditions were counterbalanced). The sum of squares value was 110.40. What is the appropriate test statistic and what it its critical value (applying α = 0.05)? t ; 2.365 r; 1.96 z; 2.307 t; 2.307
Suppose we run the following OLS regression JobStr B1 + B2 M + B3 Exp+ B4 Edu + u %3D to explain an individual's job stress level by their gender (M for male dummy), work experience (Exp) and education (Edu), using a sample of 300 observations. Suppose that the F statistic for the joint significance of the model is 30 and the RSS of the fitted model is 250. What is the TSS of the model?
9) We have a sample of 6 observations on exam scores and hours of study and would like to estimate the following relationship using the least-squares method: Score Bo+ B hours +e, We expect the score to increase with hours of study. Score Hours 80 90 85 65 50 80 12 14 11 10 8 11 Escore = 450, hours = 66,E hours. score = 5085, score= 34850, hours=746 Estimate the unknown parameters using the method of OLS and find the least-squares prediction equation. b. Calculate SSE, R', standard error of the residuals (s), and standard error of slope coefficient (s) Construct and interpret a 90% confidence interval for B. Predict the score of a student who studies 9 hours for the exam, and construct and interpret a 90% confidence interval using the predicted value (prediction interval). a. C.
A year-long fitness center study sought to determine if there is a relationship between the amount of muscle mass gained y(kilograms) and the weekly time spent working out under the guidance of a trainer x(minutes). The resulting least-squares regression line for the study is y=2.04 + 0.12x A) predictions using this equation will be fairly good since about 95% of the variation in muscle mass can be explained by the linear relationship with time spent working out. B)Predictions using this equation will be faily good since about 90.25% of the variation in muscle mass can be explained by the linear relationship with time spent working out C)Predictions using this equation will be fairly poor since only about 95% of the variation in muscle mass can be explained by the linear relationship with time spent working out D) Predictions using this equation will be fairly poor since only about 90.25% of the variation in muscle mass can be explained by the linear relationship with time spent…
A regional distributor of NIKE shoes is in the process of analyzing the factors that influence thedemand for the NIKE brand. The distributor hired an economist to conduct a study on the demand for this product. The economist collected quarterly time series data from 1986Q1 to 1991Q4 on the following variables:SALES Sales of NIKE shoesRPDI Real personal disposal incomeCONF Consumer confidence indexD2 Dummy variable for quarter 2D3 Dummy variable for quarter 3D4 Dummy variable for quarter 4Ordinary Least Squares was applied using sales as the dependent variable and real personal disposal income, consumer confidence index, dummy variable for quarter 2, dummy variable for quarter 3, and dummy variable for quarter 4 as independent variables. The table below shows the OLS output.Model 1: OLS, using observations 1986:1-1991:4 (T = 24)Dependent variable: SALESCoefficient Std. Error t-ratio p-valueconst −139.452 61.8421 −2.255 0.0368 **RPDI 1.56286 0.438492 3.564 0.0022 ***CONF 0.256247…

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