Refer Excel Output and answer the following questions. 1. State multiple regression equation 2. Interpret the meaning of two slopes in this equation 3. Interpret the meaning of adjusted r^2.
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Q: 3) Use the regression equation to predict the price of a 2000 square foot house in South Salinas.
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Refer Excel Output and answer the following questions.
1. State multiple regression equation
2. Interpret the meaning of two slopes in this equation
3. Interpret the meaning of adjusted r^2.
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- Rates of return (annualized) in two investment portfolios are compared over the last 12 quarters. They are considered similar in safety, but portfolio B is advertised as being “less volatile.” (a) At α = .025, does the sample show that portfolio A has significantly greater variance in rates of return than portfolio B? (b) At α = .025, is there a significant difference in the means? Portfolio A Portfolio B 5.23 8.96 10.91 8.60 12.49 7.61 4.17 6.60 5.54 7.77 8.68 7.06 7.89 7.68 9.82 7.62 9.62 8.71 4.93 8.97 11.66 7.71 11.49 9.91 Questions: (a-1) Choose the appropriate hypotheses. Assume σA2 is the variance of the Portfolio A and σB2 is the variance of the Portfolio B. multiple choice 1 H0: σA2/σB2 ≤ 1 versus H1: σA2/σB2 > 1 - Correct Answer H0: σA2/σB2 = 1 versus H1: σA2/σB2 ≠ 1 H0: σA2/σB2 ≥ 1 versus H1: σA2/σB2 < 1 (a-2) Specify the decision rule. (Round your answers to 2 decimal places.) Reject the null hypothesis if Fcalc >…Rates of return (annualized) in two investment portfolios are compared over the last 12 quarters. They are considered similar in safety, but portfolio B is advertised as being “less volatile.” (a) At α = .025, does the sample show that portfolio A has significantly greater variance in rates of return than portfolio B? (b) At α = .025, is there a significant difference in the means? Portfolio A Portfolio B 5.23 8.96 10.91 8.60 12.49 7.61 4.17 6.60 5.54 7.77 8.68 7.06 7.89 7.68 9.82 7.62 9.62 8.71 4.93 8.97 11.66 7.71 11.49 9.91 (b-1) Choose the appropriate hypotheses. Assume d = company assessed value – employee assessed value. multiple choice 3 H0: μ1 – μ2 = 0 vs. H1: μ1 – μ2 ≠ 0 H0: μ1 – μ2 ≥ 0 vs. H1: μ1 – μ2 < 0 H0: μ1 – μ2 ≤ 0 vs. H1: μ1 – μ2 > 0 (b-2) State the decision rule for .01 level of significance. (Round your answers to 3 decimal places. A negative value should be indicated by a minus sign.) Reject the null…Rates of return (annualized) in two investment portfolios are compared over the last 12 quarters. They are considered similar in safety, but portfolio B is advertised as being “less volatile.” (a) At α = .025, does the sample show that portfolio A has significantly greater variance in rates of return than portfolio B? (b) At α = .025, is there a significant difference in the means? Portfolio A Portfolio B 5.23 8.96 10.91 8.60 12.49 7.61 4.17 6.60 5.54 7.77 8.68 7.06 7.89 7.68 9.82 7.62 9.62 8.71 4.93 8.97 11.66 7.71 11.49 9.91 (b-1) Choose the appropriate hypotheses. Assume d = company assessed value – employee assessed value. multiple choice 3 H0: μ1 – μ2 = 0 vs. H1: μ1 – μ2 ≠ 0 H0: μ1 – μ2 ≥ 0 vs. H1: μ1 – μ2 < 0 H0: μ1 – μ2 ≤ 0 vs. H1: μ1 – μ2 > 0 (b-2) State the decision rule for .01 level of significance. (Round your answers to 3 decimal places. A negative value should be indicated by a minus sign.) Reject the null…
- 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 *…Analysis of Variance (ANOVA) Health professionals conducted a research study to examine whether people consumed more calories at a fast-food restaurant when the method of payment for their food differed. They hypothesized that people would order more food when they paid with a credit card or a gift certificate compared to cash. Test the null hypothesis that the number of calories consumed does not differ by method of payment. Write a concluding statement. Cash Credit Gift Certificate 1200 1350 1400 1050 1125 1250 700 1050 1000 1450 1680 1950 1365 1380 1400Characteristics Treatment Control P-value Mean SBP 115.3889± 113.0588±6.805 Mean difference (SBP) -0.66±3.0292 2.117 ±2.471 0.005347 Mean DBP 74.556± 7.366 72.4705±6.374 Mean difference (DBP) -1.888±2.9483 1.411765 ±3.3343 0.002233 Mean Pulse rate 96.222±13.0 88.94±15.43725 Mean difference -9.444± 0.5294118± 0.3529523 write an analysis for the data above and what does the p value mean?
- Data: Rate difference per 1000 PY: ___-2.17__; 95% CI __-4.30___ to _-0.03____ HR: __79___; 95% CI _0.63____ to _0.99____ Which statement is the most correct interpretation of the risk of pooled stroke or systemic emboli in the propensity-matched analysis? Apixaban resulted in a statistically significant decrease in stroke or systemic emboli compared to rivaroxaban Apixaban resulted in a statistically significant increase in stroke or systemic emboli compared to rivaroxaban There was no statistically significant difference in stroke or systemic emboli between apixaban and rivaroxaban.A Cox proportional hazards model is estimated relating time to psychiatric hospitalization in patients with severe mental illness. The risk factors include age, sex, prior hospitalization for mental illness, and an indicator of bipolar disorder. The parameter estimates and significance levels for the model are shown here. Which of the predictors are statistically significantly associated with time to psychiatric hospitalization? Predictor Parameter Estimate p-value Age, years 0.0045 0.5647 Sex (0 = female, 1 = male) –0.4841 0.0341 Prior hospitalization (0 = no, 1 = yes) 0.3726 0.6178 Bipolar disorder (0 = no, 1 = yes) 0.7561 0.0042 .Predicting GPA based upon high school average is an example of. aclassification bvalue estimation ccausal modeling d
- Fuel economy A consumer organization has reported test data for 50 car models. We will examine the asso-ciation between the weight of the car (in thousands of pounds) and the fuel efficiency (in miles per gallon).Here are the scatterplot, summary statistics, andregression analysis:Variable Count Mean StdDevMPG 50 25.0200 4.83394wt/1000 50 2.88780 0.511656Dependent variable is: MPGR-squared = 75.6%s = 2.413 with 50 - 2 = 48 dfVariable Coefficient SE(Coeff) t-ratio P-valueIntercept 48.7393 1.976 24.7 ...0.0001Weight -8.21362 0.6738 -12.2 ...0.0001 a) Is there strong evidence of an association between the weight of a car and its gas mileage? Write an appropri-ate hypothesis. b) Are the assumptions for regression satisfied?c) Test your hypothesis and state your conclusion.Quantitative Research Statistical Data Analysis using Software ( SPSS / PLS - SEM ) 1 ) Study the provided videos on preparing and testing SPSS / PLS - SEM 2 ) Interpret the data which has been presented in the below Table 1 and Table 2Palisades Eco-Park is a small ecological reserve that admits a relatively small number of visitors on any day, but provides both educational and entertaining lectures, exhibitions, and opportunities to observe nature. The company has collected the following data on labor costs and number of visitors to the park over the last 30 months. Month Labor Cost Visitors 1 $ 25,520 1,400 2 $ 35,869 2,135 3 $ 39,504 2,315 4 $ 31,280 1,830 5 $ 34,405 1,954 6 $ 32,293 1,796 7 $ 31,651 1,816 8 $ 37,889 2,204 9 $ 38,120 2,273 10 $ 46,387 2,941 11 $ 41,667 2,451 12 $ 38,576 2,309 13 $ 34,044 1,989 14 $ 32,788 1,924 15 $ 36,542 2,065 16 $ 26,192 1,729 17 $ 30,307 2,797 18 $ 29,613 2,294 19 $ 27,270 1,986 20 $ 29,654 2,448 21 $ 25,394 1,647 22 $ 24,369 1,478 23 $ 28,556 2,690 24 $ 29,803 3,144 25 $ 27,792 2,135 26 $ 31,322 2,696 27 $ 28,318 2,462 28 $ 29,579 2,512 29 $ 28,108 2,068 30 $ 27,550 1,709 Required: a. Estimate the labor…
