Answer Question 4 (a) - (e) based on information given belowX2tХ212448.6.6.10831410-11612-52014-72216-8a. Estimate the three multiple regreesion coefficientsb. Estimate their variances and standard errorsc. Obtain R2 and R¯2|d. Test the statistical significance of each estimated regressions coefficient usinga = 5% (two - tail)e. Test at a = 5% that all partial slope coefficients are equal to zero.

y x1 x2 2 2 12 4 4 9 8 6 6 10 8 3 14 10 -1 16 12 -5 20 14 -7 22 16 -8

Answered: Answer Question 4 (a) - (e) based on…

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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2. (35 Points) Consider the following dataset obtained from a sample. 80 3 97 4 92 4 102 103 8 111 10 119 10 123 11 117 13 136 (a) Compute the estimated linear regression coefficients to predict y using x values. (b) Using the estimated regression line found in the previous part, predict the value of y if æ equals to 7. (c) Compute SSE, SST, and SSR. Then, also compute the resulting coefficient of determination and comment on the goodness of fit. (d) Conduct t-test to test the significance of the regression relationship with a = 0.05. (e) Conduct F-test to test the significance of the regression relationship with a = 0.05.
4. The following regression is fitted using variables identified that could be related to tuition charges ($) of a university. TUITION = a+ B ACCEPT + y MSAT + 1 VSAT Where ACCEPT = the percentage of applicants that was accepted by the university, MSAT = Median Math SAT score for the freshman class and VSAT = Median English SAT score for the freshman class. The data was processed using MNITAB and the following is an extract of the output obtained: Predictor Coef StDev T P Constant -26780 6115 -4.38 0.000 ACCEPT 116.00 37.17 * 0.003 MSAT -4.21 14.12 VSAT 70.85 15.77 -0.30 4.49 0.767 ** S = 2685 R-Sq = 69.6% Analysis of Variance R-Sq (adj) = 67.7% Source DF SS MS F P Regression 3 808139371 Residual Error 49 353193051 269379790 7208021 37.37 0.000 Total 52 1161332421 a) Write out the regression equation. b) State the dependent and independent variable(s) c) Fill in the blanks identified by ** and ****. d) Is B significant, at the 10% level of significance? e) State one limitation of using…
17. Additional information was obtained from EXCEL. Conduct a test of hypothesis to determine if any of the regression coefficients do not equal 0 Use the 005 significance level. The regression equation is: Salary = 19.2 + 3.10 Years + 0.269 Perform - 0.704 Absent Intercept Years Perform Absent Coefficients Standard Error 19.186 3.096 0.269 -0.704 12.146 0.706 0.120 0.586 -1.202 t Stat 1.580 4.385 P-value 0.143 0.001 0.046 0.255 2.252 а. Но: H: Họ: H1: Họ: H1: b. The decision rules are to reject Ho if What is your decision? Interpret. c. 305 Multiple Regression and Correlation Analysis Chapter 14
Data on 11 randomly selected athletes was obtained concerning their cardiovascular fitness (measured by time to exhaustion running on a treadmill) and performance in a 20-km ski race. Both variables were measured in minutes and a regression analysis was performed. Ski 88 2.5 . Treadmill Coefficients Estimate Std. Error 0.41 (Intercept) Treadmill 1.11 88 -2.5 Is there sufficient evidence to conclude that there is a linear relationship between cardiovascular fitness and ski race performance? (a). The test statistic is (b). The p-value is (use four decimal places) (use four decimal places) (c). At the 2% significance level, we Select an answer the null hypothesis and conclude that there is Select an answer evidence to conclude that there is a linear relationship between cardiovascular fitness and ski race performance.
x 5.7 4.1 6.2 4.4 6.5 5.8 4.9 y 1.9 4.8 0.8 3.9 1.2 1.7 3.0 (a) Computethecoefficientofdetermination. (b) Howmuchofthevariationintheoutcomevariableisexplainedbytheleast-squares regression line?
Suppose x1 ans x2 are predictor variables for a response variable y. a. The distribution of all possible values of the response variable corresponding to particular values of the two predictor variables is called a distribution of the response variable. b. State the four assumptions for multiple linear regression inferences.
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4. A simple linear regression is fit to a dataset. Unfortunately, the corresponding ANOVA table is not complete because some quantities in the table are missing due to unknown digital errors. Calculate the missing values, denoted by "?", in the ANOVA table based on the other available values. Is this regression model significant (α = 0.05)? Source Regression Residual Total df ? ? 21 SS ? ? ? MS = SS/df ? 1.13 F-Ratio 430.65 p-value ?
2. We performed a linear regression using 25 observations. From the regression output we find that bo = 5.7, bị = 12.9, x = 11.4, Sz = 3.2 and MSE = 12.25. a. From the least squares line, what is the predicted response when x* = 10.65? y = b. What is the 95% confidence interval for the mean response when x* = 10.65? c. What is the 95% prediction interval for an individual response when x* = 10.65? d. Which interval is wider? The confidence interval or the prediction interval? O a. Confidence Interval b. Prediction Interval
According to the nutrition research, recommendation on the consumption of fiber for children and teenagers is the following (y is the amount of fiber per day (in grams), x is the age): y 20 22 26 29 31 33 37 40 41 2 4 6 8 10 12 14 16 18 ४ = (a) Test for the significance of regression using the analysis of variance with a useful linear relationship between these two variables? We (b) Estimate ². Round your answer to three decimal places (e.g. 98.765). (c) Estimate the standard error of the slope and intercept in this model. Round your answers to three decimal places (e.g. 98.765). (B₁) se (Bo) se B = = conclude that the model specifies a useful linear relationship at a = 0.05. Mo 0.05. Can you conclude that the model specifies a
8. In an investigation to empirically determine the value of 1, a student measures the circumference and diameter of several circles of varying size and uses Excel to make a linear plot of circumference versus diameter (both in units of meters). A linear regression fit yields the result of: y = 3.1527x - 0.0502, with R2= 0.9967 for the 5 data points plotted. How should this student report the final result? Does the empirical ratio of C/D agree with the accepted value of n?
12. Use a = 0.10. Is the coefficient of the independent variable significantly different from zero? No a. b. Yes с. Cannot conclude 13. In multiple regression analysis, high correlation among the independent variables is termed linearity b. a. multicollinearity homoscedasticity endogeneity с. d.

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