Use the following information from a multiple regression analysis to complete parts (a) through (c) below.n = 20 b₁ = 10b₂ = 35 Sp₁ = 6Choose the correct hypotheses for X₁ below.O A. Ho: B₁ #0H₂₁: B₁ = 0O C. Ho: B₁ = 0H₁: B₁ 0Sp2Find the test statistic.(Round to two decimal places as needed.)Find the p-value.Dandl to thren desimal ula= 8ال دلOB. Ho: B₁ = 1H₁: B₁ 1O D. Ho: B₁ #1H₂₁: B₁ = 1 Use the following information from a multiple regression analysis to complete parts (a) through (c) below.n = 20 b₁ = 10 b₂ = 35 Sp₁ = 6 Sb₂ = 8a. Which variable has the largest slope, in units of a t statistic?X₂b. Construct a 95% confidence interval estimate of the population slope, ß₁.≤B₁ ≤(Round to four decimal places as needed.)c. At the 0.05 level of significance, determine whether each independent variable makes a significant contribution to the regression model. On the basis of theseresults, indicate the independent variables to include in this model.Choose the correct hypotheses for X₁ below.

a) t statistic for X1: t=b1Sb1=106=1.667 t statistic for X2: t=b2Sb2=358=4.375 Here, the t statistic…

Answered: Use the following information from a…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

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Consider the following Stata regression output (some values are deliberately removed). Variable | Obs Mean Std. Dev. Min Маx lwage points | rebounds | assists 269 6.952296 .8813761 5.010635 8.655214 269 10.21041 5.900667 1.2 29.8 269 4.401115 2.892573 2.092986 .5 17.3 269 269 2.408922 1682.193 12.6 3533 minutes | 893.3278 33 Source | SS df MS Number of obs F(, Prob > F Model | Residual | = R-squared Adj R-squared Root MSE %3D 0.4146 Total | lwage | Сoef. Std. Err. P>|t| [95% Conf. Interval .0795364 points rebounds .0277761 .0637763 .0204514 3.12 0.002 0.252 0.227 -.0230647 -.0000747 .087425 .0003133 assists .0321805 .0280576 1.15 minutes .0001193 .0000985 1.21 _cons Answer the following questions. Please round your answers to 2 decimal places. Model SS : ; Residual S : ; Total SS :
Not all choices on the right will necessarily be used. Select a letter from the choices on the right into each of the drop-down boxes on the left. sample linear correlation coefficient a. o² coefficient of determination b. В population variance С. р probability of a Type Il error d. o y – intercept of a regression equation е. а f. R? g. p h. b1 i. r j. p k. bo
MAKE A GRAPH FROM THE GIVEN DATAplease do this typewritten and completely so I will upvote. Thank you and much appreciated for the help.
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
i. Write out the regression equation ii. What is the sample size used in this investigation? iii. Determine the values of *, ** and ***, **** iv. Conduct a hypothesis test, at the 5% level of significance, to determine whether ? issignificant. v. What would be the growth of the plant if 4g of fertilizer and 7g of ater was given to itdaily? vi. Carry out an F -test at the 1% significance level to determine whether the model issignificant
Use the following information from a multiple regression analysis. n=15 b1=4 b2=5 Sb1=1.3 Sb2=0.7 a. Which variable has the largest slope, in units of a t statistic? b. Construct a 95% confidence interval estimate of the population slope, β1. c. At the 0.05 level of significance, determine whether each independent variable makes a significant contribution to the regression model. On the basis of these results, indicate the independent variables to include in this model.
Consider the following computer output from a multiple regression analysis relating the cost of car insurance to the variables: number of car accidents, driver's credit score, and safety rating of the car. Intercept Car Accidents (In last 3 years) Credit Score Safety Rating Coefficients 1186 213.48 Coefficients - 130.46 294.11 Standard Error Does the sign of the coefficient for the variable safety rating make sense? 123.87 21.89 14.26 356.37 t Stat P-value 9.575 0.0000 9.752 0.0000 -9.149 0.0000 0.825 0.4128
Step 1 of 3. State the null and alternative hypotheses for the test. Step 2 of 3. Compute the value of the test statistic. Round your answer to three decimal places Step 3 of 3. Draw a conclusion and interpret the decision.
Suppose a doctor measures the height, x, and head circumference, y, of 8 children and obtains the data below. The correlation coefficient is 0.858 and the least squares regression line is y = 0.228x +11.187. Complete parts (a) and (b) below. Height, x 27.5 25.75 26.5 25.5 27.25 26.25 25.75 27.25 27 27.25 27 Head Circumference, y 17.4 17.2 17.2 16.9 17.6 17.1 17.1 17.4 17.4 17.3 17.3 (a) Compute the coefficient of determination, R². R² =% (Round to one decimal place as needed.) (b) Interpret the coefficient of determination and comment on the adequacy of the linear model. Approximately % of the variation in (Round to one decimal place as needed.) is explained by the least-squares regression model. According to the residual plot, the linear model appears to be
Let's study the relationship between brand, camera resolution, and internal storage capacity on the price of smartphones. Use α = .05 to perform a regression analysis of the Smartphones01CS dataset, and then answer the following questions. When you copy and paste output from MegaStat to answer a question, remember to choose to "Keep Formatting" to paste the text. a. Did you find any evidence of multicollinearity and variance inflation among the predictors. Explain your answer using a VIF analysis. b. Copy and paste the normal probability plot for your analysis. Is there any evidence that the errors are not normally distributed? Explain. c. Copy and paste the Residuals vs. Predicted Y-values. Does the pattern support the null hypothesis of constant variance for the errors? Explain. d. Study the residuals analysis. Which observations, if any, have unusual residuals? e. Study the residuals analysis. Calculate the leverage statistic. Which observations, if any, are high leverage…
Only do D.

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