Fall 98

Answers for Assignment 4

1. When handing in your assignments, show as much of the coding and other instructions you used when obtaining the results. This is especially important when using recodes, computes or select cases. If you do not include these SPSS commands, then I have no way of knowing what you did if your results differ from what I obtained.

2. When using these recode, compute, and select cases commands, it is often
a good idea to run off the frequency distribution first (with

3. When recoding a variable that has many values, there are no rules concerning what is exactly the correct or incorrect way to recode. As a result, if the tables do not produce the results you expect, you might want to try another way of recoding the data. For example, in question 2, most of you might have tried further recodes to see if you could find a relationship between job hours and study hours.

4. When producing a cross-classification table, it is best to request either column or row percentages. Otherwise, you have to deal with unequal sample sizes in each column and attempt to estimate whether or not there is a relationship between the variables on this basis. This is usually quite difficult.

5. I could not figure out how to get the bar chart in this file for the web site so that is not included.

For questions 1 and 2, I first ran off the frequency distributions in order to see how I should recode these. These tables follow.

FREQUENCIES VARIABLES=coffee drunk .

Frequency | Percent | Valid Percent | Cumulative Percent | ||
---|---|---|---|---|---|

Valid | 1 None | 493 | 66.1 | 66.6 | 66.6 |

2 1 to 3 cups daily | 193 | 25.9 | 26.1 | 92.7 | |

3 4 to 6 cups daily | 42 | 5.6 | 5.7 | 98.4 | |

4 7 or more cups daily | 12 | 1.6 | 1.6 | 100.0 | |

Total | 740 | 99.2 | 100.0 | ||

Missing | 6 | 1 | .1 | ||

9 No response | 1 | .1 | |||

System Missing | 4 | .5 | |||

Total | 6 | .8 | |||

Total | 746 | 100.0 |

Frequency | Percent | Valid Percent | Cumulative Percent | ||
---|---|---|---|---|---|

Valid | 1 One | 6 | .8 | 1.0 | 1.0 |

2 2 to 4 | 224 | 30.0 | 36.8 | 37.8 | |

3 5 to 7 | 278 | 37.3 | 45.7 | 83.6 | |

4 8 or more | 100 | 13.4 | 16.4 | 100.0 | |

Total | 608 | 81.5 | 100.0 | ||

Missing | 0 | 1 | .1 | ||

6 Other | 1 | .1 | |||

8 NOT APPLICABLE | 1 | .1 | |||

9 NO RESPONSE | 8 | 1.1 | |||

System Missing | 127 | 17.0 | |||

Total | 138 | 18.5 | |||

Total | 746 | 100.0 |

FREQUENCIES VARIABLES=sthours jobhours /STATISTICS=STDDEV MEAN MEDIAN .

N | Mean | Median | Std. Deviation | ||
---|---|---|---|---|---|

Valid | Missing
| ||||

Study Hours | 716 | 30 | 15.81 | 12.00 | 12.21 |

HOURS PER WEEK AT JOB - W96 | 395 | 351 | 18.38 | 17.00 | 9.55 |

Frequency | Percent | Valid Percent | Cumulative Percent | ||
---|---|---|---|---|---|

Valid | 0 | 2 | .3 | .3 | .3 |

1 | 5 | .7 | .7 | 1.0 | |

2 | 20 | 2.7 | 2.8 | 3.8 | |

3 | 19 | 2.5 | 2.7 | 6.4 | |

4 | 26 | 3.5 | 3.6 | 10.1 | |

5 | 39 | 5.2 | 5.4 | 15.5 | |

6 | 36 | 4.8 | 5.0 | 20.5 | |

7 | 20 | 2.7 | 2.8 | 23.3 | |

8 | 42 | 5.6 | 5.9 | 29.2 | |

9 | 12 | 1.6 | 1.7 | 30.9 | |

10 | 122 | 16.4 | 17.0 | 47.9 | |

11 | 6 | .8 | .8 | 48.7 | |

12 | 23 | 3.1 | 3.2 | 52.0 | |

13 | 4 | .5 | .6 | 52.5 | |

14 | 13 | 1.7 | 1.8 | 54.3 | |

15 | 64 | 8.6 | 8.9 | 63.3 | |

16 | 2 | .3 | .3 | 63.5 | |

17 | 8 | 1.1 | 1.1 | 64.7 | |

18 | 12 | 1.6 | 1.7 | 66.3 | |

19 | 1 | .1 | .1 | 66.5 | |

20 | 86 | 11.5 | 12.0 | 78.5 | |

21 | 6 | .8 | .8 | 79.3 | |

22 | 4 | .5 | .6 | 79.9 | |

24 | 4 | .5 | .6 | 80.4 | |

25 | 36 | 4.8 | 5.0 | 85.5 | |

27 | 4 | .5 | .6 | 86.0 | |

28 | 6 | .8 | .8 | 86.9 | |

30 | 34 | 4.6 | 4.7 | 91.6 | |

32 | 2 | .3 | .3 | 91.9 | |

35 | 9 | 1.2 | 1.3 | 93.2 | |

36 | 3 | .4 | .4 | 93.6 | |

40 | 23 | 3.1 | 3.2 | 96.8 | |

42 | 1 | .1 | .1 | 96.9 | |

45 | 2 | .3 | .3 | 97.2 | |

50 | 9 | 1.2 | 1.3 | 98.5 | |

52 | 1 | .1 | .1 | 98.6 | |

56 | 1 | .1 | .1 | 98.7 | |

60 | 5 | .7 | .7 | 99.4 | |

70 | 1 | .1 | .1 | 99.6 | |

80 | 1 | .1 | .1 | 99.7 | |

90 | 1 | .1 | .1 | 99.9 | |

99 | 1 | .1 | .1 | 100.0 | |

Total | 716 | 96.0 | 100.0 | ||

Missing | 990 | 2 | .3 | ||

997 Uncertain | 1 | .1 | |||

999 No response | 17 | 2.3 | |||

System Missing | 10 | 1.3 | |||

Total | 30 | 4.0 | |||

Total | 746 | 100.0 |

Frequency | Percent | Valid Percent | Cumulative Percent | ||
---|---|---|---|---|---|

Valid | 1 | 4 | .5 | 1.0 | 1.0 |

2 | 3 | .4 | .8 | 1.8 | |

3 | 5 | .7 | 1.3 | 3.0 | |

4 | 6 | .8 | 1.5 | 4.6 | |

5 | 4 | .5 | 1.0 | 5.6 | |

6 | 10 | 1.3 | 2.5 | 8.1 | |

7 | 5 | .7 | 1.3 | 9.4 | |

8 | 19 | 2.5 | 4.8 | 14.2 | |

9 | 6 | .8 | 1.5 | 15.7 | |

10 | 28 | 3.8 | 7.1 | 22.8 | |

11 | 2 | .3 | .5 | 23.3 | |

12 | 22 | 2.9 | 5.6 | 28.9 | |

13 | 1 | .1 | .3 | 29.1 | |

13 | 9 | 1.2 | 2.3 | 31.4 | |

13 | 1 | .1 | .3 | 31.6 | |

14 | 6 | .8 | 1.5 | 33.2 | |

15 | 37 | 5.0 | 9.4 | 42.5 | |

16 | 1 | .1 | .3 | 42.8 | |

16 | 23 | 3.1 | 5.8 | 48.6 | |

17 | 8 | 1.1 | 2.0 | 50.6 | |

18 | 13 | 1.7 | 3.3 | 53.9 | |

19 | 4 | .5 | 1.0 | 54.9 | |

20 | 59 | 7.9 | 14.9 | 69.9 | |

21 | 1 | .1 | .3 | 70.1 | |

22 | 12 | 1.6 | 3.0 | 73.2 | |

23 | 6 | .8 | 1.5 | 74.7 | |

24 | 7 | .9 | 1.8 | 76.5 | |

25 | 29 | 3.9 | 7.3 | 83.8 | |

26 | 1 | .1 | .3 | 84.1 | |

27 | 3 | .4 | .8 | 84.8 | |

28 | 2 | .3 | .5 | 85.3 | |

29 | 1 | .1 | .3 | 85.6 | |

30 | 25 | 3.4 | 6.3 | 91.9 | |

32 | 7 | .9 | 1.8 | 93.7 | |

35 | 3 | .4 | .8 | 94.4 | |

36 | 1 | .1 | .3 | 94.7 | |

37 | 2 | .3 | .5 | 95.2 | |

40 | 11 | 1.5 | 2.8 | 98.0 | |

43 | 1 | .1 | .3 | 98.2 | |

45 | 1 | .1 | .3 | 98.5 | |

48 | 1 | .1 | .3 | 98.7 | |

50 | 3 | .4 | .8 | 99.5 | |

55 | 2 | .3 | .5 | 100.0 | |

Total | 395 | 52.9 | 100.0 | ||

Missing | 99 NO RESPONSE | 6 | .8 | ||

System Missing | 345 | 46.2 | |||

Total | 351 | 47.1 | |||

Total | 746 | 100.0 |

RECODE coffee (1=0) (2=2) (3=5) (4=8) INTO rcoffee . EXECUTE . RECODE drunk (1=1) (2=3) (3=6) (4=10) INTO rdrunk . EXECUTE . FREQUENCIES VARIABLES=rcoffee rdrunk /STATISTICS=STDDEV MEAN .

N | Mean | Std. Deviation | ||
---|---|---|---|---|

Valid | Missing
| |||

RCOFFEE | 740 | 6 | .9351 | 1.6214 |

RDRUNK | 608 | 138 | 5.5033 | 2.4407 |

Frequency | Percent | Valid Percent | Cumulative Percent | ||
---|---|---|---|---|---|

Valid | .00 | 493 | 66.1 | 66.6 | 66.6 |

2.00 | 193 | 25.9 | 26.1 | 92.7 | |

5.00 | 42 | 5.6 | 5.7 | 98.4 | |

8.00 | 12 | 1.6 | 1.6 | 100.0 | |

Total | 740 | 99.2 | 100.0 | ||

Missing | System Missing | 6 | .8 | ||

Total | 6 | .8 | |||

Total | 746 | 100.0 |

Frequency | Percent | Valid Percent | Cumulative Percent | ||
---|---|---|---|---|---|

Valid | 1.00 | 6 | .8 | 1.0 | 1.0 |

3.00 | 224 | 30.0 | 36.8 | 37.8 | |

6.00 | 278 | 37.3 | 45.7 | 83.6 | |

10.00 | 100 | 13.4 | 16.4 | 100.0 | |

Total | 608 | 81.5 | 100.0 | ||

Missing | System Missing | 138 | 18.5 | ||

Total | 138 | 18.5 | |||

Total | 746 | 100.0 |

After recoding, the new codes represent the midpoints of the intervals into which the data were originally grouped. As a result, the means and standard deviations should closely approximate the actual values of the variables being measured, assuming that respondents are truthful and that this sample is reasonably representative of University of Regina undergraduates.

For coffee consumption, almost exactly two-thirds of respondents report that they do not drink coffee, with about two-thirds of the remainder reporting under four cups daily. Only 2 per cent report drinking seven or more cups daily. Since those who do not drink coffee are included in the average, the mean number of cups of coffee drunk daily is reported to be just under one cup. Given that there are some who drink a considerable amount of coffee, the distribution is quite varied, with a standard deviation of 1.6 cups daily.

For the number of drinks required to become drunk, there is a lot of
variation, with the standard deviation being 2.4 drinks. That is, there
are a lot of respondents in each of the 2-4, 5-7, and 8 or more categories.
The mean is 5.5 drinks required to become drunk. Only 16 per cent
report requiring 8 or more drinks before becoming drunk.

RECODE sthours (Lowest thru 9=5) (10 thru 19=15) (20 thru Highest=25) INTO rst . EXECUTE . RECODE jobhours (Lowest thru 9=5) (10 thru 19=15) (20 thru Highest=25) INTO rj . EXECUTE . CROSSTABS /TABLES=rst BY rj /FORMAT= AVALUE TABLES /CELLS= COUNT COLUMN .

RJ | Total | |||||
---|---|---|---|---|---|---|

5.00 | 15.00 | 25.00
| ||||

RST | 5.00 | Count | 14 | 48 | 70 | 132 |

% within RJ | 22.6% | 31.0% | 38.0% | 32.9% | ||

15.00 | Count | 22 | 66 | 59 | 147 | |

% within RJ | 35.5% | 42.6% | 32.1% | 36.7% | ||

25.00 | Count | 26 | 41 | 55 | 122 | |

% within RJ | 41.9% | 26.5% | 29.9% | 30.4% | ||

Total | Count | 62 | 155 | 184 | 401 | |

% within RJ | 100.0% | 100.0% | 100.0% | 100.0% |

Since tables with a lot of cells are difficult to analyze, I used only three categories for each of the two variables. As most of you noted, there is not much of a relationship between hours worked at a job or jobs and study hours. This may partly be due to the fact that those without jobs are not included in this table, since only those who report some hours worked at jobs are included.

The above cross-classification table does show some sort of relationship between these variables though. Notice in the third row of the table, 42% of those with less than 10 hours at jobs report 20 or more hours per week spent studying. In contrast, for those with 10 or more hours at a job (categories 15 and 25 in the table), only somewhere between one-quarter and 30 per cent report report this many hours studied.

Again, in the first row of the table, note that as the number of job hours is increased (moving from left to right) the percentage of those who report less than 10 hours spent studying increases regularly.

As a result, this table does show some tendency for those with fewer
hours worked to study somewhat more, and those with more hours worked
to be more concentrated in the fewer study hours categories.

COMPUTE ch = ch6 + ch611 + ch12 . EXECUTE . FREQUENCIES VARIABLES=ch /STATISTICS=STDDEV MEAN /BARCHART FREQ .

N | Mean | Std. Deviation | ||
---|---|---|---|---|

Valid | Missing
| |||

CH | 716 | 30 | .2109 | .7028 |

Frequency | Percent | Valid Percent | Cumulative Percent | ||
---|---|---|---|---|---|

Valid | .00 | 639 | 85.7 | 89.2 | 89.2 |

1.00 | 32 | 4.3 | 4.5 | 93.7 | |

2.00 | 25 | 3.4 | 3.5 | 97.2 | |

3.00 | 15 | 2.0 | 2.1 | 99.3 | |

4.00 | 2 | .3 | .3 | 99.6 | |

5.00 | 2 | .3 | .3 | 99.9 | |

6.00 | 1 | .1 | .1 | 100.0 | |

Total | 716 | 96.0 | 100.0 | ||

Missing | System Missing | 30 | 4.0 | ||

Total | 30 | 4.0 | |||

Total | 746 | 100.0 |

Almost 90 per cent of respondents report that they did not have children. For those with children, the number at each successively larger number of children is somewhat less, with there being only 2 respondents with 4 children, 2 with 5 children, and one with 6 children.

This large concentration of respondents at 0 children produces a
very small mean of 0.2 children per respondent. The fact that there
are respondents with several children means that the standard deviation
is considerably larger than the mean, at 0.7 children.

COMPUTE prob = regret + suffer +relation + actions + blackout + violent + la . EXECUTE . FREQUENCIES VARIABLES=prob /STATISTICS=STDDEV MEAN .

N | Mean | Std. Deviation | ||
---|---|---|---|---|

Valid | Missing
| |||

PROB | 587 | 159 | 9.4821 | 2.0969 |

Frequency | Percent | Valid Percent | Cumulative Percent | ||
---|---|---|---|---|---|

Valid | 7.00 | 113 | 15.1 | 19.3 | 19.3 |

8.00 | 97 | 13.0 | 16.5 | 35.8 | |

9.00 | 124 | 16.6 | 21.1 | 56.9 | |

10.00 | 104 | 13.9 | 17.7 | 74.6 | |

11.00 | 57 | 7.6 | 9.7 | 84.3 | |

12.00 | 35 | 4.7 | 6.0 | 90.3 | |

13.00 | 29 | 3.9 | 4.9 | 95.2 | |

14.00 | 16 | 2.1 | 2.7 | 98.0 | |

15.00 | 6 | .8 | 1.0 | 99.0 | |

16.00 | 1 | .1 | .2 | 99.1 | |

17.00 | 1 | .1 | .2 | 99.3 | |

18.00 | 4 | .5 | .7 | 100.0 | |

Total | 587 | 78.7 | 100.0 | ||

Missing | System Missing | 159 | 21.3 | ||

Total | 159 | 21.3 | |||

Total | 746 | 100.0 |

MEANS TABLES=prob BY alcuse permit /CELLS MEAN COUNT STDDEV .

Cases | ||||||
---|---|---|---|---|---|---|

Included | Excluded | Total | ||||

N | Percent | N | Percent | N | Percent | |

PROB * USED ALCOHOL? | 584 | 78.3% | 162 | 21.7% | 746 | 100.0% |

PROB * Permitted to Drink Underage? | 583 | 78.2% | 163 | 21.8% | 746 | 100.0% |

2 Very rarely | Mean | 8.7569 |
---|---|---|

N | 144 | |

Std. Deviation | 1.9833 | |

3 Special occasions | Mean | 9.2231 |

N | 130 | |

Std. Deviation | 2.1359 | |

4 Weekends | Mean | 9.8474 |

N | 249 | |

Std. Deviation | 1.9158 | |

5 Several times weekly | Mean | 10.0189 |

N | 53 | |

Std. Deviation | 2.0521 | |

6 Every day | Mean | 11.8750 |

N | 8 | |

Std. Deviation | 3.9438 | |

Total | Mean | 9.4829 |

N | 584 | |

Std. Deviation | 2.0987 |

1 Not at all | Mean | 9.6864 |
---|---|---|

N | 118 | |

Std. Deviation | 2.3632 | |

2 Occasional permission | Mean | 9.3494 |

N | 352 | |

Std. Deviation | 1.9670 | |

3 No limits | Mean | 9.7345 |

N | 113 | |

Std. Deviation | 2.1672 | |

Total | Mean | 9.4923 |

N | 583 | |

Std. Deviation | 2.0955 |

This is an example of a scale constructed from several variables. Each of the variables is coded in a similar manner, with 1 representing minimal or no alcohol related problems, 2 some problems, and 3 representing greater alcohol related problems. While the severity of the problems is greater for some of the questions (e.g. got into trouble with the law) than for others (e.g. regret drinking so much), by adding these together, the scale treats each problem as equal. This is one of the problematic aspects of this scale.

By adding together seven variables, each with code 1 to 3, the minimum possible value that anyone could have on this scale is 7 and the maximum is 21 (in the case that the respondent answers 3 for each of the 7 questions). Note that no one has a value more than 18, with the great bulk of respondents having values between 7 and 10 on the scale. This means that about three-quarters of respondents have had relatively few alcohol related problems. Several respondents, however, did report 14 or more, indicating considerable alcohol related problems.

From the first means table, it does appear that those who report greater amounts, or at least more frequent, alcohol consumption, report more alcohol related problems. The index averages 8.8 for those who report drinking alcohol only very rarely. Then it increases to 9.2 for those who drink on special occasions, 9.8 for those drinking on weekends, 10.0 for those drinking several times a week, to 11.9 for the small number of respondents who report drinking every day. While these differences are not real large, they are consistent and regular. This leads a researcher to believe that those who drink more frequently are likely to have more alcohol related problems.

For the second means table, there is litle or no apparent relation
between the index and whether or not parents allowed children to drink
alcohol. The means for each of the categories are very similar (9.7, 9.3
and 9.7) with no regular or consistent direction to the differences.

USE ALL. COMPUTE filter_$=(ch > 0). VARIABLE LABEL filter_$ 'ch > 0 (FILTER)'. VALUE LABELS filter_$ 0 'Not Selected' 1 'Selected'. FORMAT filter_$ (f1.0). FILTER BY filter_$. EXECUTE . FREQUENCIES VARIABLES=ch /STATISTICS=STDDEV MEAN .

N | Mean | Std. Deviation | ||
---|---|---|---|---|

Valid | Missing
| |||

CH | 77 | 0 | 1.9610 | 1.0814 |

Frequency | Percent | Valid Percent | Cumulative Percent | ||
---|---|---|---|---|---|

Valid | 1.00 | 32 | 41.6 | 41.6 | 41.6 |

2.00 | 25 | 32.5 | 32.5 | 74.0 | |

3.00 | 15 | 19.5 | 19.5 | 93.5 | |

4.00 | 2 | 2.6 | 2.6 | 96.1 | |

5.00 | 2 | 2.6 | 2.6 | 98.7 | |

6.00 | 1 | 1.3 | 1.3 | 100.0 | |

Total | 77 | 100.0 | 100.0 | ||

Total | 77 | 100.0 |

This requires the use of the select cases to eliminate the respondents with no children. After that, the distribution of those with children can be seen, and this is the same as in question 3. For those who do have children, the mean is almost 2, so those undergraduates who do have children average about two children per household.

Note that the standard deviation is actually larger in this distribution
than it was in question 3. For the distribution of those with
children, the standard deviation is 1.1 children, as opposed to
0.7 for all respondents. In the case of all respondents, the values
of the variable are so heavily concentrated at 0 children that the
standard deviation is small. Although the range is reduced when those
with no children are eliminated, the remaining cases are more
spread out over the values between 1 and 6 than in the prior case.
This is an example of where the two measures of variation actually
give different results.

FILTER OFF. USE ALL. EXECUTE . USE ALL. COMPUTE filter_$=(sex = 1). VARIABLE LABEL filter_$ 'sex = 1 (FILTER)'. VALUE LABELS filter_$ 0 'Not Selected' 1 'Selected'. FORMAT filter_$ (f1.0). FILTER BY filter_$. EXECUTE . MEANS TABLES=sthours hwhours dephours BY job /CELLS MEAN COUNT STDDEV .

Cases | ||||||
---|---|---|---|---|---|---|

Included | Excluded | Total | ||||

N | Percent | N | Percent | N | Percent | |

Study Hours * Hold a job? | 249 | 92.2% | 21 | 7.8% | 270 | 100.0% |

DEPENDENT HOURS * Hold a job? | 248 | 91.9% | 22 | 8.1% | 270 | 100.0% |

HOUSEHOLD WORK HOURS * Hold a job? | 248 | 91.9% | 22 | 8.1% | 270 | 100.0% |

Hold a job? | Study Hours | DEPENDENT HOURS | HOUSEHOLD WORK HOURS | |
---|---|---|---|---|

1 No | Mean | 16.30 | 6.31 | 5.89 |

N | 112 | 112 | 114 | |

Std. Deviation | 14.97 | 18.75 | 25.80 | |

2 Yes | Mean | 13.77 | 3.72 | 2.29 |

N | 137 | 136 | 134 | |

Std. Deviation | 10.66 | 5.01 | 10.53 | |

Total | Mean | 14.91 | 4.89 | 3.95 |

N | 249 | 248 | 248 | |

Std. Deviation | 12.81 | 13.17 | 19.17 |

USE ALL. COMPUTE filter_$=(sex =2). VARIABLE LABEL filter_$ 'sex =2 (FILTER)'. VALUE LABELS filter_$ 0 'Not Selected' 1 'Selected'. FORMAT filter_$ (f1.0). FILTER BY filter_$. EXECUTE . MEANS TABLES=sthours hwhours dephours BY job /CELLS MEAN COUNT STDDEV .

Cases | ||||||
---|---|---|---|---|---|---|

Included | Excluded | Total | ||||

N | Percent | N | Percent | N | Percent | |

Study Hours * Hold a job? | 458 | 96.4% | 17 | 3.6% | 475 | 100.0% |

DEPENDENT HOURS * Hold a job? | 458 | 96.4% | 17 | 3.6% | 475 | 100.0% |

HOUSEHOLD WORK HOURS * Hold a job? | 455 | 95.8% | 20 | 4.2% | 475 | 100.0% |

Hold a job? | Study Hours | DEPENDENT HOURS | HOUSEHOLD WORK HOURS | |
---|---|---|---|---|

1 No | Mean | 17.82 | 5.31 | 9.53 |

N | 205 | 204 | 204 | |

Std. Deviation | 13.08 | 7.25 | 30.98 | |

2 Yes | Mean | 14.94 | 4.52 | 3.62 |

N | 253 | 254 | 251 | |

Std. Deviation | 10.63 | 5.18 | 14.43 | |

Total | Mean | 16.23 | 4.87 | 6.27 |

N | 458 | 458 | 455 | |

Std. Deviation | 11.86 | 6.20 | 23.51 |

First note that the means of study hours, hours with dependents, and hours at housework all are lower for those with jobs, both males and females.

Second note that the pattern does differ. For males, those with jobs spend approximately three hours less weekly at each of these three tasks than do those with jobs. In contrast, for females, study hours are about three hours less for those with jobs, in contrast to those without jobs. But for hours with dependents there is very little difference in the mean, less than one hour less for those with jobs. Then there is a large reduction, almost six hours, in the housework hours for those with jobs.

In terms of males and females, the latter generally spent more hours
at each of the tasks than did the former. The only case where females
spent less hours is that hours with dependents is reported as
one hour less for females without jobs than for males without jobs.

Paul Gingrich

November 12, 1998