A sample of 20 automobiles was taken, and the miles per gallon (MPG), horsepower, and total weight were recorded. Develop a linear regression model to predict MPG, using horsepower as the only independent variable. Develop another model with weight as the independent variable. Which of these two models is better? Explain.
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- ANOVA Sigmficance F 0,046 df SS MS F 130433116.219 130433116.219 4.083 Regression Residual Total 113 3609911959.86s 31946123.539 114 3740345076.087 Cosfficrent Standard Error Stát Pvalne 1535.215 Intercept Age 10725.802 6.987 0,000 69.964 34.625 2.021 0.046 Which of the following statements is the best explanation of the R? Select one O'A3.5% of the accident damage can be explained by the age of the driver. B. 3.5% of the variation in accidernt damage can be eaplained by variation in the age of the drver. CC3.5% of the coefficients r stat and p value can be explained by the age of the dtver. D.3.5% of the total errar can be eiplained by the SSE Scanned with CamScannerAnalysis of Variance Source DF SS MS Regression 1 02364 13 14 Residual Error Total 11.3240 What is the value of SSR (Sums of Squares for Regression)?U.S. Population The U.S. population can be modeledby the function y = 165.6x1.345, where y is in thousands and x is the number of years after 1800.a. What was the population in 1960, according tothis model?b. Is the graph of this function concave up or concave down? What does this mean?c. Use numerical or graphical methods to findwhen the model estimates the population to be93,330,000.
- A researcher fitted following OLS regression using time series data from 1973 t0 2020 (Bar)BD =-3.7 + 0.08BD lag(t-1), -2.2LnER lag(t), + 42LnEXP lag(t)-33LnRE lag(t), +10 LnPl lag(t), R²=0.99 DW=1.4 RSS=4.5 Where BD is budget deficit as a percentage of GDP, ER, EXP, RE and Pl are Exchange rate, government expenditures, government revenues and per capita income, respectively. Ln shows natural log and "t" stands for time. i :-Interpret above results ii :- Is there any problem of Autocorrelation in above model? How do you know265 guizres/276906/take Grouping Information Using the lukey Method and .unf.educ Grouping ActivityT N Mean 9 145 444 A shop B. date 9 62.333 Means that do not share a letter are significantly different. Tukey Pairwise Comparisons: Age Grouping Information Using the Tukey Method and 95% Confidence Age N Mean Grouping mid 6 137.167 A old 6 98.500 A B. yng 6 76.000 Means that do not share a letter are significantly different O Marketers should focus on middle age rather than younger groups O Marketers should not pay more for access to middle age rather than older groups O All of the answers are correct. O Marketers should not pay more for access to older groups vs younger groupsThe following data relate the sales figures of restaurant, to the number of customers registered that week: Week Customers Sales (SR) First 16 330 Second 12 270 Third 18 380 Fourth 14 300 a) Perform a linear regression that relates bar sales to guests (not to time). b) If the forecast is for 20 guests next week, what are the sales expected to be?
- We have estimated the impact of gross domestic product (GDP), energy consumption (ENERGY) and population (POP) on CO2 emiisions (CO2) in Cyprus. The results are as follows, Dependent Variable: CO2 Method: Least Squares Date: 04/20/17 Time: 09.46 Sample: 1990 2013 Included observations: 24 Variable Coefficient Std. Error t-Statistic Prob. GDP ENERGY POP 2.002813 0.022114 -0.734352 0.203927 6.458672 0.011872 0.328388 0.293686 0,310097 1.862670 -2.236233 0.694371 0.7597 0.0773 0,0369 0.4954 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.825079 Mean dependentyar 0.798841 0.048515 Akaike info criterion 0.047074 Schwarz criterion 40.75460 Hannan-Quinn.criter. 31.44583 Durbin-Wats on stat 0.000000 3.625982 0.108170 -3.062883 -2.866541 -3.010793 1.410912 S.D. dependent yar a Write down the economie function for the above estimation by using the information obtained from above table| b- Write down the economic model for the above…a simple linear regression equation shows the relationship between-Question 19 An economist wants to estimate the relationship between earnings (in thousands of dollars) and years of education. She estimates the model Earnings BO+B1 *Education + E. The following is a portion of her results. Coefficient Standard Error Intercept 15.77 Education 4.21 Which of the following is true? 3.8 1.4 p-value 0.003 0.032 O If education is increased by one year, we predict that earnings will increase by $4,210. O If earnings are increased by $1000, we predict that education will increase by 21 O If education is increased by one year, we predict that earnings will increase by $3200. O If earnings are increased by $1000, we predict that education will increase by .032 years,
- Use the following STATA output to test whether the variable wgt is significant at 5% level: Source | SS df Number of obs = EC 3. Prob > F R-squared MS 392 300.76 0.0000 0.6993 Adj R-squared anba6970 4.2965 388) = Model Juu16656.4443 Residual 162,54916 5552.1481 388 18.4601782 Total Juu23818.9935 391 60.9181419 Root MSE Coef. Std. Err. P>It| [95% Conf. Interval] syl ena wat .2677968 -.012674 -.0057079 44.37096 .4130673 .0082501 .0007139 1.480685 -0.65 -1.54 -8.00 29.97 0.517 0.125 0.000 0.000 -1.079927 -.0288944 -.0071115 41.45979 .5443336 0035465 .0043043 47.28213 _cons The variable is not significant because p-value is less than 0.05. The variable is significant because p-value is less than 0.05. The variable is significant because p-value is less than 0.1. The variable is not significant because p-value is greater than 0.05wages = B1 + B2educ + ßzexper + e where wages denotes hourly wages. We estimate the regression in R and obtain the output ## Coefficients: ## Estimate Std. Error t value Pr(>|t|) ## (Intercept) 2.0 1.0 2 0.0455 * ## educ 0.5 0.5 1 0.3173 ## exper 2.0 0.5 4 6.33e-05 *** ## --- ## Signif. codes: ****' 0. 001 '**' 0.01 **' 0.05 ' 0.1 ' ' 1 Build a 90% confidence interval for B3 using a normal approximation. (Use that if Z ~ N(0, 1) and z1-a satisfies P(Z > z1-a) = a, then zo9 = 1.28, zo95 = 1.64, Z0.975 = 1.96, zo.99 = 2.33, and z0.995 = 2.58). Oa. [2 – 1.64 x (0.5), 2 + 1.64 x (0.5)] O b. [2 – 1.28 × (0.5), 2 + 1.28 x (0.5)] c. [2 – 1.28 x (0.5)², 2 + 1.28 × (0.5)²] O d. [2 – 1.64 × (0.5)², 2 + 1.64 × (0.5)²] O e. [2 – 1.96 × (0.5)², 2 + 1.96 × (0.5)²] O f. [2 – 1.96 × (0.5), 2 + 1.96 × (0.5)]A certain standardized test measures students' knowledge in English and math. The English and math scores for 10 randomly selected students were recorded and analyzed. The results are shown in the computer output. Predictor Coef SE Coef t-ratio Constant -124.13 78.712 0.046 Math 1.223 0.1966 6.220 0.000 S = 34.55 R-Sq = 82.8% R-Sq (Adj) = 83.5% Which of the following represents the standard deviation of the residuals? O 1.223 34.55 78.712 124.13