Table 4. Partial Data Sample

from Q6, hours exercising

25

25

25

25

25

25

30

30

30

30

30

30

40

40

40

40

80

n =

SUM

mean

5.04

4.78

4.54

median

3.00

3.00

3.00

mode

0

0

0

range

80

40

30

To investigate potential variables of interest, the data was sorted into male and female, and health-care related questions of interest displayed for both groups. This convenient procedure shows that while both groups scored similarly on many questions, the difference between means for questions 20-23 may yield interesting results with further study.

Comparing means between groups this way often delivers interesting results. Considering means for exercise rates by hour for different education levels (Figure 4), does not reveal any particular trend.

Displaying mean hours worked by education does however suggest further research may reveal correlation between education level and hours of work, which could then be tested for likelihood at various levels of accuracy.

Displaying smoking incidence by education level reveals a clear trend that suggests higher education may coincide with better health, if smoking coincides with negative health outcomes.

Sorting the data by Likert-scale means ranking for preference for "alternative" health care, however the respondent defined that deliberately ambiguous and subjective term, resulted in a continuous ranking of ten classes. The rest of the means for various questions can then be compared against each other within these groups. Figures 7 and 8 display various means for the highest and lowest rankings for preference for alternative health care, means of one and ten respectively. Figure 7 shows data with higher entries in order to avoid scaling low answers so small as to impede usefulness of display.

In this sample at least, higher-educated respondents who rated alternative health care the highest had higher mean education than those who were least likely to prefer that alternative (Fig. 7, Q3). Interestingly, higher mean preference for alternative health coincided with mean fewer hours exercising, and not surprisingly, less smoking.

Quick display of other variable means via bar graph shows some will be more interesting than others given limited resources of time and report space. Reducing the scale on the y-axis displays an apparently wider difference on Q6 than in Fig. 7, which illustrates the value of comparing similar results on appropriate scales.

Table 5. Lowest vs. highest answers on Q23 "alt health"

Answered "1" on "prefer alt. health"

Q1

Q2

Q3

Q20

Q21

Q22

Q23

n (Males)

38.00

38.00

38.00

38.00

38.00

38.00

38.00

n (Females)

37.00

37.00

37.00

37.00

36.00

37.00

37.00

Mean Male

0.00

31.74

3.21

4.00

4.39

4.76

1.00

Mean Female

1.00

30.97

3.27

4.92

5.50

5.51

1.00

Subample Mean

0.49

31.36

3.24

4.45

4.93

5.13

1.00

Variance (M)

0.00

2.33

9.24

11.38

8.83

0.00

Variance (F)

0.00

health" n (Males)
7.00

7.00

7.00

7.00

7.00

7.00

7.00

n (Females)

14.00

13.00

14.00

14.00

14.00

14.00

14.00

Mean Male

0.00

37.14

3.43

5.86

5.57

5.71

10.00

Mean Female

1.00

39.69

3.50

5.64

6.79

6.21

10.00

Subample Mean

0.67

38.80

3.48

5.71

6.38

6.05

10.00

Variance (M)

0.00

93.14

1.95

11.81

11.95

13.90

0.00

Variance (F)

0.00

2.73

9.79

9.26

7.72

0.00

Sample STDEV

0.48

12.75

1.54

3.15

3.15

3.04

0.00

STDEV (M)

0.00

9.65

1.40

3.44

3.46

3.73

0.00

STDEV (F)

0.00

14.44

1.65

3.13

3.04

2.78

0.00

Table 5 displays descriptive statistics, measures of central tendency, and dispersion for the highest and lowest rankings of mean preference for "alternative health care," sorted for gender as well. The results demonstrate that more than three times as many respondents ranked the lowest mean preference than the highest, and that twice as many females answered "10" as did males (Q1, top). Means for males and females of both groups were integers, which shows no entries were classified incorrectly or there would be decimals. Similar results for Q23 cross-check the accuracy of these results, where subsample means are perfect 1 or 10, indicating no other entries were included. Means for other questions indicate for example that males were slightly older for the low-preference group but women were older for the "10" group. The difference in variance between the two genders within groups indicates males showed wider dispersion in age for the low-preference group but the opposite for the high-preference cohort. This is supported by the standard deviation, the square root of variance. These descriptive statistics can thus be compared for all other questions, indicating for example that women had higher means than males for the remaining questions in the low-preference category, but that trend continued for all questions except 20 in the high-preference group.

Conclusions

What these results suggest is that higher preference for alternative health care coincides with healthier eating habits (self-assessed, question 15 and 18), which comes as no major surprise, but also for more, but more restless sleeping, which coincides with higher self-reported stress (Q22) and less ability to concentrate when sleep is interrupted (Q21), especially for women. These results suggest further investigation comparing sleeping and eating habits in this population, perhaps. Question 17 suggests for another example that restaurant marketers may want to investigate advertising more to traditional, rather than alternative health consumers.