You have been asked to test whether having more education equates to increased income and less unemployment and to provide a predictive model. Education median wkly earnings unemployment % Doctoral...

Business statistics assignment


You have been asked to test whether having more education equates to increased income and less unemployment and to provide a predictive model.  Education            median wkly earnings                     unemployment % Doctoral               1623                                                       1.7 Professional       1730                                                       1.5 Master’s              1341                                                       2.4 Bachelor’s           1137                                                       2.8 Associate’s           798                                                 3.8 College (some)     738                                                      5.0 High School           678                                                      5.4 Less than HS          493                                                     8.0 Median All Workers 860                                                               4.3    1) You have been asked to run a linear regression to determine if having more education equates to increased income and less unemployment (is there evidence of association?) Choose the variables to include: T-value – P-value VIF – be careful there is collinearity   Choose the BEST equation for prediction. Highest R-Sq adjusted Mallows Cp closest to number of variables in the equation   2) You have been asked to answer the question: Does the number of 18-24 year olds stating that they were interviewed for a job in the past month differ from the expected proportion of all interviews?   education Population 18 – 24yr interviewed   1 Less than HS 64011 32000   2 High School 132569 92798   3 AA 247949 210756   4 BA 60948 59119             Note that 25% expected is not necessarily a reasonable expectation – the job market often needs workers at varying rates – not an equal 25% from each education level. 3) Using Minitab and the House data set Explore the data – descriptive statistics Create a graph – histogram or bar chart Build a regression model – simple LM and a multiple- regression model  value     MedInc medAge Rms bedRms popl     houseHls   latitude longitude 452600  8.3252   41           880         129         322         126         37.88     -122.23 358500  8.3014   21           7099       1106       2401       1138       37.86     -122.22 352100  7.2574   52           1467       190         496         177         37.85     -122.24 341300  5.6431   52           1274       235         558         219         37.85     -122.25 342200  3.8462   52           1627       280         565         259         37.85     -122.25 269700  4.0368   52           919         213         413         193         37.85     -122.25 299200  3.6591   52           2535       489         1094       514         37.84     -122.25 241400  3.1200   52           3104       687         1157       647         37.84     -122.25 226700  2.0804   42           2555       665         1206       595         37.84     -122.26 261100  3.6912   52           3549       707         1551       714         37.84     -122.25 281500  3.2031   52           2202       434         910         402         37.85     -122.26 241800  3.2705   52           3503       752         1504       734         37.85     -122.26 213500  3.0750   52           2491       474         1098       468         37.85     -122.26 191300  2.6736   52           696         191         345         174         37.84     -122.26 159200  1.9167   52           2643       626         1212       620         37.85     -122.26 140000  2.1250   50           1120       283         697         264         37.85     -122.26 152500  2.7750   52           1966       347         793         331         37.85     -122.27 155500  2.1202   52           1228       293         648         303         37.85     -122.27 158700  1.9911   50           2239       455         990         419         37.84     -122.26 162900  2.6033   52           1503       298         690         275         37.84     -122.27    4) You have been asked to determine if a process is in control. You select 6 samples from three lines for 5 days and measure the diameter produced. day-Line measure 1.1          2.2 1.1          2.2 1.1          2.1 1.1          2.3 1.1          2.2 1.1          2.2 1.2          2.1 1.2          2.1 1.2          2.0 1.2          1.9 1.2          1.9 1.2          1.9 1.3          1.8 1.3          1.9 1.3          2.0 1.3          2.1 1.3          2.1 1.3          2.0 2.1          2.1 2.1          2.0 2.1          1.9 2.1          1.9 2.1          1.8 2.1          1.9 2.2          2.0 2.2          2.0 2.2          2.1 2.2          2.0 2.2          2.1 2.2          2.0 2.3          1.9 2.3          1.8 2.3          1.9 2.3          1.9 2.3          1.9 2.3          1.7 3.3          1.9 3.3          1.8 3.3          2.2 3.3          2.0 3.3          2.0 3.3          2.0 3.2          2.0 3.2          2.1 3.2          2.0 3.2          2.0 3.2          1.9 3.2          1.9 3.1          1.9 3.1          1.8 3.1          1.9 3.1          1.8 3.1          1.9 3.1          2.1  4.1          2.0 4.1          2.0 4.1          2.0 4.1          2.1 4.1          2.0 4.1          2.0 4.2          1.9 4.2          1.9 4.2          1.8 4.2          1.9 4.2          1.9 4.2          1.9 4.3          2.1 4.3          2.0 4.3          2.0 4.3          2.0 4.3          2.0 4.3          2.0  5.1          2.1 5.1          2.1 5.1          2.1 5.1          2.2 5.1          2.0 5.1          2.2 5.2          2.2 5.2          2.1 5.2          2.0 5.2          2.0 5.2          1.9 5.2          1.8 5.3          1.8 5.3          1.9 5.3          1.8 5.3          1.7 5.3          1.8 5.3          1.8    What analysis do you run?   Why? · Shows the means of successive subgroups over time. · Monitors process mean. · Must be preceded by examination of the R chart to make sure that the variation in the process is in control.