4.
You estimated the following regression. Which of the following is the estimated regression line?
Source | SS df MS Number of obs = 309
-------------+---------------------------------- F(1, 307) > 99999.00
Model | 3.4298e+09 1 3.4298e+09 Prob > F = 0.0000
Residual | 5008792.71 307 16315.2857 R-squared = 0.9985
-------------+---------------------------------- Adj R-squared = 0.9985
Total | 3.4348e+09 308 11152012 Root MSE = 127.73
------------------------------------------------------------------------------
Y | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
X | 39.83786 .0868877 458.50 0.000 39.66689 40.00883
_cons | 55.9075 9.036526 6.19 0.000 38.12613 73.68886
------------------------------------------------------------------------------
Y = 9.04 + 0.09*X
Y = 0.09 + 9.04*X
Y = 39.84 + 55.91*X
Y = 55.91 + 39.84*X
Step by stepSolved in 2 steps
- Which of the following is the point at which the regression line crosses the y-axis? Group of answer choices Y-intercept predicted value observed value slopearrow_forwardConsider the following time series: Quarter Year 1 Year 2 Year 3 1 69 66 60 2 44 36 46 3 60 62 55 4 79 82 73 (a) Choose a time series plot. (i) 100 80 60 40 20 3. 4 6 7 Period(t) 9 10 11 12 (ii) 100 80 60 40 20 1 2 3. 4 6 7 Period (t) 10 11 12arrow_forwardplease show calc functions ti-84arrow_forward
- You estimated a regression with the following output. Source | SS df MS Number of obs = 157 -------------+---------------------------------- F(1, 155) = 64808.73 Model | 1.0654e+09 1 1.0654e+09 Prob > F = 0.0000 Residual | 2548025.21 155 16438.8724 R-squared = 0.9976 -------------+---------------------------------- Adj R-squared = 0.9976 Total | 1.0679e+09 156 6845708.24 Root MSE = 128.21 ------------------------------------------------------------------------------ Y | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- X | 41.93209 .1647137 254.58 0.000 41.60672 42.25746 _cons | 94.53504 18.26855 5.17 0.000 58.44757 130.6225…arrow_forward9. You estimated a regression with the following output. Source | SS df MS Number of obs = 178 -------------+---------------------------------- F(1, 176) = 7719.75 Model | 247434661 1 247434661 Prob > F = 0.0000 Residual | 5641179.28 176 32052.155 R-squared = 0.9777 -------------+---------------------------------- Adj R-squared = 0.9776 Total | 253075841 177 1429807.01 Root MSE = 179.03 ------------------------------------------------------------------------------ Y | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- X | 35.48969 .4039248 87.86 0.000 34.69253 36.28685 _cons | 104.8311 38.79964 2.70 0.008 28.25872 181.4036…arrow_forwardYou estimated a regression with the following output. Source | SS df MS Number of obs = 383 -------------+---------------------------------- F(1, 381) = 1616.74 Model | 20894411.7 1 20894411.7 Prob > F = 0.0000 Residual | 4923967.53 381 12923.7993 R-squared = 0.8093 -------------+---------------------------------- Adj R-squared = 0.8088 Total | 25818379.2 382 67587.3802 Root MSE = 113.68 ------------------------------------------------------------------------------ Y | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- X | 10.5851 .2632541 40.21 0.000 10.06749 11.10272 _cons | 71.97038 19.03739 3.78 0.000 34.53887 109.4019…arrow_forward
- 3. You estimated a regression with the following output. Source | SS df MS Number of obs = 400 -------------+---------------------------------- F(1, 398) = 716.92 Model | 22118655.1 1 22118655.1 Prob > F = 0.0000 Residual | 12279166.2 398 30852.1764 R-squared = 0.6430 -------------+---------------------------------- Adj R-squared = 0.6421 Total | 34397821.3 399 86210.0784 Root MSE = 175.65 ------------------------------------------------------------------------------ Y | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- X | 5.299576 .1979268 26.78 0.000 4.910464 5.688689 _cons | 67.86719 18.3827 3.69 0.000 31.72786 104.0065…arrow_forwardThe accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x = 5 wins Click the icon to view the table of numbers of wins and earned run average. (b) x = 10 wins (c) x = 21 wins (d) x = 15 wins ERA 6- ERA 6- AERA 6- ERA 6- 4- 4- 4- 4- 2- 2- 2- 2- 0+ 6 0- 0- 0- 12 18 24 6. 12 18 24 12 18 24 6 12 18 24 Wins Wins Wins Wins (a) Predict the ERA for 5 wins, if it is meaningful. Select the correct choice below and, if necessary, fill in the answer box within your choice. A. ŷ= (Round to two decimal places as needed.) B. It is not meaningful to predict this value of y because…arrow_forwardYou estimated a regression with the following output. Source | SS df MS Number of obs = 310 -------------+---------------------------------- F(1, 308) = 5951.51 Model | 182258361 1 182258361 Prob > F = 0.0000 Residual | 9432159.79 308 30623.8954 R-squared = 0.9508 -------------+---------------------------------- Adj R-squared = 0.9506 Total | 191690521 309 620357.672 Root MSE = 175 ------------------------------------------------------------------------------ Y | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- X | 18.84872 .2443253 77.15 0.000 18.36796 19.32948 _cons | 38.37008 15.185 2.53 0.012 8.490623 68.24953…arrow_forward
- 1. You estimated a regression with the following output. Source | SS df MS Number of obs = 210 -------------+---------------------------------- F(1, 208) = 940.28 Model | 5529353.01 1 5529353.01 Prob > F = 0.0000 Residual | 1223155.7 208 5880.55624 R-squared = 0.8189 -------------+---------------------------------- Adj R-squared = 0.8180 Total | 6752508.71 209 32308.6541 Root MSE = 76.685 ------------------------------------------------------------------------------ Y | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- X | 13.66711 .4457062 30.66 0.000 12.78843 14.54579 _cons | 103.7139 41.86814 2.48 0.014 21.17362 186.2542…arrow_forwardNonearrow_forwardYou estimated a regression with the following output. Source | SS df MS Number of obs = 248 -------------+---------------------------------- F(1, 246) > 99999.00 Model | 1.2864e+09 1 1.2864e+09 Prob > F = 0.0000 Residual | 980713.166 246 3986.63889 R-squared = 0.9992 -------------+---------------------------------- Adj R-squared = 0.9992 Total | 1.2874e+09 247 5212005.66 Root MSE = 63.14 ------------------------------------------------------------------------------ Y | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- X | 38.34444 .0675026 568.04 0.000 38.21148 38.4774 _cons | 49.99803 5.986441 8.35 0.000 38.20681 61.78925…arrow_forward
- MATLAB: An Introduction with ApplicationsStatisticsISBN:9781119256830Author:Amos GilatPublisher:John Wiley & Sons IncProbability and Statistics for Engineering and th...StatisticsISBN:9781305251809Author:Jay L. DevorePublisher:Cengage LearningStatistics for The Behavioral Sciences (MindTap C...StatisticsISBN:9781305504912Author:Frederick J Gravetter, Larry B. WallnauPublisher:Cengage Learning
- Elementary Statistics: Picturing the World (7th E...StatisticsISBN:9780134683416Author:Ron Larson, Betsy FarberPublisher:PEARSONThe Basic Practice of StatisticsStatisticsISBN:9781319042578Author:David S. Moore, William I. Notz, Michael A. FlignerPublisher:W. H. FreemanIntroduction to the Practice of StatisticsStatisticsISBN:9781319013387Author:David S. Moore, George P. McCabe, Bruce A. CraigPublisher:W. H. Freeman