Consider the following Stata regression output (IDTQ1)SourceSdfMSNumber of obs526%3DF(3, 522)76.87%3DModel2194.11163 731.370532Prob > F0.0000Residual4966.30269522 9.51398984 R-squared0.3064%3DAdj R-squared0.3024%3DTotal7160.41429525 13.6388844Root MSE3.0845wageCoef.Std. Err.tP>|t|[95% Conf. Interval]educ.5989651.051283511.680.000.4982176.6997126exper.0223395.01205681.850.064-.0013464.0460254tenure.1692687.02164467.820.000.1267474.2117899_cons-2.872735.7289643-3.940.000-4.304799-1.440671where wage is hourly wage in US$, exper is years of work experience, and tenure is years of tenure with the current employers.Assume that the classical linear model assumptions hold.Imagine you want to test whether the effect of experience is statistically significant. In contrast to what we typically do in the course, you want to conduct a one-sidedhypothesis test. The null hypothesis is that experience has no effect on wage. The alternative hypothesis is that the effect of experience on wage is positive.For this one-sided hypothesis test, is the estimated effect of experience on wage statistically significant at the 5% level? How do you know?Hint: start your answer with "Yes, because" or "No, because".IIII Consider the following Stata regression output (IDTQ1)SourceSdfMSNumber of obs%3D526F(3, 522)76.87Model2194.11163 731.370532Prob > F0.0000Residual4966.30269522 9.51398984R-squared0.3064Adj R-squared =0.3024Total7160.41429525 13.6388844Root MSE3.0845wageCoef.Std. Err.tP>|t|(95% Conf. Interval]educ.5989651.051283511.680.000.4982176.6997126еxper.0223395.01205681.850.064-.0013464.0460254tenure.1692687.02164467.820.000.1267474.2117899_cons-2.872735.7289643-3.940.000-4.304799-1.440671where wage is hourly wage in US$, exper is years of work experience, and tenure is years of tenure with the current employers.Assume that the classical linear model assumptions hold.Imagine you want to test whether the effect of experience is statistically significant. In contrast to what we typically do in the course, you want to conduct a one-sidedhypothesis test. The null hypothesis is that experience has no effect on wage. The alternative hypothesis is that the effect of experience on wage is positive.For this one-sided hypothesis test, is the estimated effect of experience on wage statistically significant at the 5% level? How do you know?Hint: start your answer with "Yes, because" or "No, because".II

Statistical significance rule: If p value is less than or equal to the level of significance 0.05…

Answered: Consider the following Stata regression…

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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What is the predicted total number of wins in a regular season for a team that is averaging 75 points per game with a relative skill level of 1350?
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A regression model relating x, number of salespersons at a branch office, to y, annual sales at the office (in thousands of dollars) provided the following regression output. Where ntotal = 40. ANOVA df SS MS F Significance F Regression 6,759.5 Residual Total 9,031.4 Coefficients Standard Error t Stat P-value Intercept 75.0 10.408 Number of 40.0 5.323 Salespersons a. Write the estimated regression equation (to whole number). ŷ = + b. Compute the F statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals) F-value p-value is - Select your answer - we - Select your answer - v Ho c. Compute the t statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals) t Stat p-value is - Select your answer - we - Select your answer - v Ho: B, d. Predict the annual sales at the Memphis branch office. This branch employs 10 salespersons. $ thousand (to whole number) %24
Hello, I am working on an assignment in research design. How do I calculate cronbach's alpha for a multiple regression analyis of prayer on a set of 5 different vital signs? (heart rate, blood pressure, temp, O2, and resp)
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Consider the following Stata regression output (IDFB2) Source SS df MS Number of obs 935 %3D F(3, 931) 114.07 Model 1211.30177 3 403.767257 Prob > F 0.0000 %3D Residual 3295.51748 931 3.53976099 R-squared 0.2688 %3D Adj R-squared 0.2664 Total 4506.81925 934 4.82528828 Root MSE 1.8814 educ Coef. Std. Err. P>|t| [95% Conf. Interval] age .0074829 .0198281 urban 2546161 .1367932 IQ 0750274 .0040968 5.439236 .7981253 _cons What is the value of the t-statistic of the constant?
Chapter 9, Section 2, Exercise 032 Use the following ANOVA table for regression to answer the questions. Response: Y Source DF Sum Sq Mean Sq F-value Pr(>F) Regression 1 355.21 355.21 14.76 0.000 Residual Error 359 8641.13 24.07 Total 360 8996.34 Give the F-statistic and p-value.Enter the exact answers.The F-statistic is=The p-value is=
The following output comes from regression using the actual HW9 scores and the Final test scores from intro stats one semester. Sample size: 50R (correlation coefficient) = 0.3658R-sq = 0.1338Estimate of error standard deviation: 10.36256Parameter estimates: Parameter Estimate Std. Err. DF T-Stat P-Value Intercept 43.558118 11.1716 48 3.899 0.0003 Slope 0.360048 0.132225 48 2.723 0.009 Assume no assumptions are violated. Form a 87% Confidence interval for how much your final is supposed to increase for each problem done on homework 9.Use 5 decimal places
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Beachcomber Ltd in a local car dealership that sells used and new vehicles. The manager of the company wants to know how different variables affect the sales of his vehicles. A random sample of yearly data was taken with the view to testing the model: SALES=a+BAGE+YMIL+SENG Where SALES= amount that a vehicle is sold for($000's), AGE = age of the vehicle, MIL= the total mileage of the vehicle at the point of sale and ENG = the size of the engine. The sample of data was processed using MINITAB and the following is an extract of the output obtained:
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Following is a portion of the regression output for an application relating maintenance expense (dollars per month) to usage (hours per week) for a particular brand of computer terminal. Excel File: data14-41.xlsx ANOVA df SS MS F Significance F Regression 1575.76 Residual 8 349.14 Total 1924.90 Coefficients Standard Error t Stat P-value Intercept 6.1092 0.9361 Usage 0.8951 0.149 If your answer is zero, enter "0". a. Write the estimated regression equation (to 4 decimals). ŷ = b. Use a t test to determine whether monthly maintenance expense is related to usage at the 0.05 level of significance (to 2 decimals). Use Table 2 of Appendix В. t = p-value - Select your answer v the null hypothesis. Monthly maintenance expense Select your answer - related to usage. c. Did the estimated regression equation provide a good fit? Explain. Hint: If r is greater than 0.50, the estimated regression equation provides a good fit. - Select your answer - V because the value of r2 is - Select your answer -…

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