(c) The alternate hypothesis isO A. H, :p + 0В. Н : и= 0О С. Н : В # 0O D. H, :p = 0(d) The test statistic isO A. 4.794B. None of the other answersC. 0.362O D. 40.78 Regression. A coach wants to see the relationship between the statistics of practice games and official games of a local soccer team. A sample of24 players was used and the resulting (partial) Excel output is shown below. Assume both x and y form normal distributions.RegressionStatisticsMultiple R***R Square0.70524Adjusted R Square0.668395Standard Error8.703633Observations24Coefficients Standardt StatP-valueLowerUpper95%Error95%Intercept40.634618.5068614.7942660.00136621.167360.40101Midterm0.7182050.1749174.3795870.0023650.3620461.169078(a) The slope of the regression line isA. 0.175В. 4.38C. 40.635D. 0.718(b) The correlation coefficient isA. 0.705B. None of the other answersC. 0.8398D. -0.8398A hypothesis test is done to determine whether the correlation coefficient is significantly different from zero.

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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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Use the following ANOVA table for regression to answer the questions. Analysis of Variance Source DF SS MS F P Regression 1 293.3 293.3 2.01 0.158 Residual Error 174 25386.6 145.9 Total 175 25679.9 The F-statistic is _____________.The p-value is ___________________
I need help with these questions 1. do the covariates and factors interact? 2. can you conclude a homogeneity of regression slopes? 3. can you conclude homogeneity of variance?
Use the following ANOVA table for regression to answer the questions. Analysis of Variance Source DF SS MS F P Regression 1 291.4 291.4 2.01 0.158 Residual Error 174 25230.0 145.0 Total 175 25521.4 Give the F-statistic and p-value.Enter the exact answers.The F-statistic is =The p-value is =
A multiple regression analysis produced the following tables. Predictor Coefficients StandardErrort Statistic p-valueIntercept -139.609 2548.989 -0.05477 0.957154x 24.24619 22.25267 1.089586 0.295682x 32.10171 17.44559 1.840105 0.08869Source df SS MS F p-valueRegression 2 302689 151344.5 1.705942 0.219838Residual 13 1153309 88716.07Total 15 1455998Using = 0.01 to test the null hypothesis H :?1 = ?2 = 0, the critical F value is ____.6.701.964.845.995.70
The __________ __ __ ______ of a random sample is the graph of its theoretical normal percentiles paired with corresponding actual percentiles of the random sample. A. scatterplot B. normal q-q plot C. fitted histogram D. unbiased estimator
A regression analysis was performed and the summary output is shown below. Regression Statistics Multiple R 0.7802268560.780226856 R Square 0.6087539470.608753947 Adjusted R Square 0.5870180550.587018055 Standard Error 6.7217061336.721706133 Observations 20 ANOVA dfdf SSSS MSMS F� Significance F� Regression 11 1265.3871265.387 1265.3871265.387 28.006928.0069 4.9549E-054.9549E-05 Residual 1818 813.264813.264 45.18145.181 Total 1919 2078.6512078.651 Step 2 of 2: Which measure is appropriate for determining the proportion of variation in the dependent variable explained by the set of independent variable(s) in this model?
Choose the appropriate statistical test. When computing, be sure to round each answer as indicated. A dentist wonders if depression affects ratings of tooth pain. In the general population, using a scale of 1-10 with higher values indicating more pain, the average pain rating for patients with toothaches is 6.8. A sample of 30 patients that show high levels of depression have an average pain rating of 7.1 (variance 0.8). What should the dentist determine? 1. Calculate the estimated standard error. (round to 3 decimals). [st.error] 2. What is thet-obtained? (round to 3 decimals). 3. What is the t-cv? (exact value) 4. What is your conclusion? Only type "Reject" or Retain"
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Refer to the ANOVA table for this regression. Source SS d.f. MS Regression 1,164,578 5 232,916 Residual 1,500,689 45 33,349 Total 2,665,267 50 (a) State the degrees of freedom for the F test for overall significance.
3.Which model do you think is the “best” reduced model? Discuss why you choose this model. Analysis of Variance Table (Step back model) Response: rent Df Sum Sq Mean Sq F value Pr(>F) age 1 21000 21000 17.1136 0.0003079 *** sqft 1 35364 35364 28.8196 1.134e-05 *** sd 1 5961 5961 4.8576 0.0362339 * unts 1 8678 8678 7.0722 0.0130049 * gar 1 33364 33364 27.1899 1.713e-05 *** cp 1 7641 7641 6.2269 0.0189934 * Residuals 27 33131 1227 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Step forward model: Response: rent Df Sum Sq Mean Sq F value Pr(>F) age 1 21000 21000 16.6255 0.000406 *** sqft 1 35364 35364 27.9976 1.757e-05 *** sd 1 5961 5961 4.7191 0.039517 * unts 1 8678 8678 6.8705 0.014697 * gar 1 33364 33364 26.4144 2.599e-05 *** cp 1 7641 7641 6.0493 0.021176 *…
Using the following information: Coefficients Intercept -12.8094 Independent variable 2.1794 ANOVA df SS MS F Regression 1 12,323.80 12,323.80 90.0481 Residual 8 1,454.602 136.8550 Total 9 13,778.4 What is the correlation coefficient? Multiple Choice 0.8944 0.9457 −0.9457 0.8878

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