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name:  <unnamed>

log:  C:\Users\Michael\Documents\newer web pages\soc_meth_proj3\fall_2013_381

> _logs\Class9.log

log type:  text

opened on:  24 Oct 2013, 12:12:29

. use "C:\Users\Michael\Documents\newer web pages\soc_meth_proj3\fifty_state_dataset.dta", clear

. twoway (scatter incwage  NH_White_proportion, mlabel(statefip)) (lfit incwage NH_White_proportion)

* generates the scatter plot. If you want to follow along with the class discussion, and the below analyses, you should generate the scatter plot.

. summarize  NH_White_proportion

Variable |       Obs        Mean    Std. Dev.       Min        Max

-------------+--------------------------------------------------------

NH_White_p~n |        51    .7626632    .1633623   .2354178   .9835737

. regress incwage  NH_White_proportion

Source |       SS       df       MS              Number of obs =      51

-------------+------------------------------           F(  1,    49) =    2.14

Model |  18878316.5     1  18878316.5           Prob > F      =  0.1500

Residual |   432407199    49  8824636.71           R-squared     =  0.0418

-------------+------------------------------           Adj R-squared =  0.0223

Total |   451285515    50   9025710.3           Root MSE      =  2970.6

-------------------------------------------------------------------------------

incwage |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]

--------------+----------------------------------------------------------------

NH_White_pr~n |   -3761.36   2571.649    -1.46   0.150    -8929.282    1406.562

_cons |   22161.23   2004.928    11.05   0.000     18132.18    26190.29

-------------------------------------------------------------------------------

* This is the regression line that Stata automatically put into the scatter plot with “lfit”

. predict M1_predicted

(option xb assumed; fitted values)

. gen residual=incwage- M1_predicted

. gen abs_residual=abs(residual)

. gsort -abs_residual

. dfbeta( NH_White_proportion)

_dfbeta_1: dfbeta(NH_White_proportion)

*the dfbeta command and the predict command are both post-regression commands that could have been executed in any order after the regression.

. gen abs_dfbeta=abs( _dfbeta_1)

. list statefip abs_residual residual  abs_dfbeta  _dfbeta_1

+--------------------------------------------------------------------+

|             statefip   abs_re~l    residual   abs_df~a   _dfbeta_1 |

|--------------------------------------------------------------------|

1. |          Connecticut   5617.314    5617.314   .0487289    .0487289 |

2. |           New Jersey   5432.736    5432.736   .1172426   -.1172426 |

3. |           New Mexico   5139.932   -5139.932   .5375599    .5375599 |

4. |              Montana   5024.921   -5024.921   .2145686   -.2145686 |

5. |          Mississippi   5009.293   -5009.293   .2366829    .2366829 |

|--------------------------------------------------------------------|

6. |             Maryland   4840.275    4840.275   .1743481   -.1743481 |

7. |        West Virginia   4798.199   -4798.199   .2921322   -.2921322 |

8. |        Massachusetts   4666.598    4666.598    .098265     .098265 |

9. |             Arkansas   4460.403   -4460.403   .0185422   -.0185422 |

10. |             Colorado   4390.833    4390.833   .0056333    .0056333 |

|--------------------------------------------------------------------|

11. |         North Dakota   4204.203   -4204.203    .192666    -.192666 |

12. |            Minnesota    4187.81     4187.81   .1740437    .1740437 |

13. |               Alaska   3780.312    3780.312   .0506594   -.0506594 |

14. |            Louisiana   3555.554   -3555.554   .1484154    .1484154 |

15. |              Alabama   3416.563   -3416.563   .0482474    .0482474 |

|--------------------------------------------------------------------|

16. | District of Columbia   3381.999    3381.999   .5903278   -.5903278 |

17. |             Michigan   3208.876    3208.876   .0356351    .0356351 |

18. |        New Hampshire   3021.199    3021.199   .1813799    .1813799 |

19. |         South Dakota   2937.162   -2937.162   .1303558   -.1303558 |

20. |             Virginia   2706.413    2706.413   .0332524   -.0332524 |

|--------------------------------------------------------------------|

21. |             Illinois   2687.422    2687.422     .04929     -.04929 |

22. |           Washington   2536.313    2536.313   .0665131    .0665131 |

23. |             Oklahoma   2383.868   -2383.868   .0102179   -.0102179 |

24. |                Idaho   2289.952   -2289.952    .070259    -.070259 |

25. |             Kentucky   2257.391   -2257.391    .075205    -.075205 |

|--------------------------------------------------------------------|

26. |            Wisconsin   2079.558    2079.558   .0656909    .0656909 |

27. |       South Carolina    1986.75    -1986.75    .022419     .022419 |

28. |             Delaware   1970.206    1970.206   .0329438   -.0329438 |

29. |              Wyoming   1860.133   -1860.133   .0957266   -.0957266 |

30. |              Florida   1833.188   -1833.188   .0603009    .0603009 |

|--------------------------------------------------------------------|

31. |              Arizona    1755.73    -1755.73    .062599     .062599 |

32. |               Hawaii   1728.106   -1728.106   .3419163    .3419163 |

33. |         Rhode Island   1562.148    1562.148   .0499289    .0499289 |

34. |             Missouri   1460.693    1460.693   .0429018    .0429018 |

35. |             Nebraska     1231.4     -1231.4   .0429309   -.0429309 |

|--------------------------------------------------------------------|

36. |                 Ohio   1017.316    1017.316    .024228     .024228 |

37. |               Kansas   1001.302   -1001.302    .021283    -.021283 |

38. |             New York   998.9494    998.9494   .0335865   -.0335865 |

39. |              Georgia   939.2884   -939.2884   .0433774    .0433774 |

40. |                Texas    873.475    -873.475   .0654734    .0654734 |

|--------------------------------------------------------------------|

41. |                 Utah   544.7642   -544.7642   .0203697   -.0203697 |

42. |                Maine    536.482    -536.482   .0362305   -.0362305 |

43. |               Nevada   347.9611    347.9611   .0080656   -.0080656 |

44. |              Vermont   328.0741   -328.0741   .0203959   -.0203959 |

45. |           California   294.7873    294.7873   .0240138   -.0240138 |

|--------------------------------------------------------------------|

46. |               Oregon   241.7805    241.7805   .0072873    .0072873 |

47. |         Pennsylvania    230.294    -230.294   .0063625   -.0063625 |

48. |              Indiana   165.3883   -165.3883   .0053708   -.0053708 |

49. |            Tennessee   89.31062    89.31062   .0009869    .0009869 |

50. |       North Carolina   46.82497   -46.82497   .0009033    .0009033 |

|--------------------------------------------------------------------|

51. |                 Iowa   17.83441    17.83441   .0008664    .0008664 |

+--------------------------------------------------------------------+

* Connecticut and New Jersey have the highest residuals in absolute value.

. gsort - abs_dfbeta

. list statefip abs_dfbeta  _dfbeta_1 abs_residual residual

+--------------------------------------------------------------------+

|             statefip   abs_df~a   _dfbeta_1   abs_re~l    residual |

|--------------------------------------------------------------------|

1. | District of Columbia   .5903278   -.5903278   3381.999    3381.999 |

2. |           New Mexico   .5375599    .5375599   5139.932   -5139.932 |

3. |               Hawaii   .3419163    .3419163   1728.106   -1728.106 |

4. |        West Virginia   .2921322   -.2921322   4798.199   -4798.199 |

5. |          Mississippi   .2366829    .2366829   5009.293   -5009.293 |

|--------------------------------------------------------------------|

6. |              Montana   .2145686   -.2145686   5024.921   -5024.921 |

7. |         North Dakota    .192666    -.192666   4204.203   -4204.203 |

8. |        New Hampshire   .1813799    .1813799   3021.199    3021.199 |

9. |             Maryland   .1743481   -.1743481   4840.275    4840.275 |

10. |            Minnesota   .1740437    .1740437    4187.81     4187.81 |

|--------------------------------------------------------------------|

11. |            Louisiana   .1484154    .1484154   3555.554   -3555.554 |

12. |         South Dakota   .1303558   -.1303558   2937.162   -2937.162 |

13. |           New Jersey   .1172426   -.1172426   5432.736    5432.736 |

14. |        Massachusetts    .098265     .098265   4666.598    4666.598 |

15. |              Wyoming   .0957266   -.0957266   1860.133   -1860.133 |

|--------------------------------------------------------------------|

16. |             Kentucky    .075205    -.075205   2257.391   -2257.391 |

17. |                Idaho    .070259    -.070259   2289.952   -2289.952 |

18. |           Washington   .0665131    .0665131   2536.313    2536.313 |

19. |            Wisconsin   .0656909    .0656909   2079.558    2079.558 |

20. |                Texas   .0654734    .0654734    873.475    -873.475 |

|--------------------------------------------------------------------|

21. |              Arizona    .062599     .062599    1755.73    -1755.73 |

22. |              Florida   .0603009    .0603009   1833.188   -1833.188 |

23. |               Alaska   .0506594   -.0506594   3780.312    3780.312 |

24. |         Rhode Island   .0499289    .0499289   1562.148    1562.148 |

25. |             Illinois     .04929     -.04929   2687.422    2687.422 |

|--------------------------------------------------------------------|

26. |          Connecticut   .0487289    .0487289   5617.314    5617.314 |

27. |              Alabama   .0482474    .0482474   3416.563   -3416.563 |

28. |              Georgia   .0433774    .0433774   939.2884   -939.2884 |

29. |             Nebraska   .0429309   -.0429309     1231.4     -1231.4 |

30. |             Missouri   .0429018    .0429018   1460.693    1460.693 |

|--------------------------------------------------------------------|

31. |                Maine   .0362305   -.0362305    536.482    -536.482 |

32. |             Michigan   .0356351    .0356351   3208.876    3208.876 |

33. |             New York   .0335865   -.0335865   998.9494    998.9494 |

34. |             Virginia   .0332524   -.0332524   2706.413    2706.413 |

35. |             Delaware   .0329438   -.0329438   1970.206    1970.206 |

|--------------------------------------------------------------------|

36. |                 Ohio    .024228     .024228   1017.316    1017.316 |

37. |           California   .0240138   -.0240138   294.7873    294.7873 |

38. |       South Carolina    .022419     .022419    1986.75    -1986.75 |

39. |               Kansas    .021283    -.021283   1001.302   -1001.302 |

40. |              Vermont   .0203959   -.0203959   328.0741   -328.0741 |

|--------------------------------------------------------------------|

41. |                 Utah   .0203697   -.0203697   544.7642   -544.7642 |

42. |             Arkansas   .0185422   -.0185422   4460.403   -4460.403 |

43. |             Oklahoma   .0102179   -.0102179   2383.868   -2383.868 |

44. |               Nevada   .0080656   -.0080656   347.9611    347.9611 |

45. |               Oregon   .0072873    .0072873   241.7805    241.7805 |

|--------------------------------------------------------------------|

46. |         Pennsylvania   .0063625   -.0063625    230.294    -230.294 |

47. |             Colorado   .0056333    .0056333   4390.833    4390.833 |

48. |              Indiana   .0053708   -.0053708   165.3883   -165.3883 |

49. |            Tennessee   .0009869    .0009869   89.31062    89.31062 |

50. |       North Carolina   .0009033    .0009033   46.82497   -46.82497 |

|--------------------------------------------------------------------|

51. |                 Iowa   .0008664    .0008664   17.83441    17.83441 |

+--------------------------------------------------------------------+

* DC, New Mexico, and Hawaii have the biggest dfbetas, meaning they are most influential over the slope. The slope had SE of 2571 dollars per unit of non-Hispanic white proportion. The dfbeta of DC tells us that DC alone made the slope more negative by -0.59*(2571).

. clear all

. *(8 variables, 11 observations pasted into data editor)

* A quick look at Anscombe’s data.

. twoway (scatter y2 x2) (lfit y2 x2)

. twoway (scatter y1 x1) (lfit y1 x1)

. log close

name:  <unnamed>

log:  C:\Users\Michael\Documents\newer web pages\soc_meth_proj3\fal

> l_2013_381_logs\Class9.log

log type:  text

closed on:  24 Oct 2013, 15:50:20

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