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These dynamics suggest sample means may indicate questionable results without further testing to verify if skew distorts generalizability. There are plausible cases where such an extreme value would be kept, say if we were testing for risk of a rare event, in which case that would be the data point of interest compared to the rest.
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
1.20
12.41
10.31
10.70
0.00
Sample STDEV
0.50
12.45
1.32
3.30
3.32
3.13
0.00
STDEV (M)
0.00
14.50
1.53
3.04
3.37
2.97
0.00
STDEV (F)
0.00
10.11
1.10
3.52
3.21
3.27
0.00
Answered "10" on "prefer alt. health" n (Males)
7.00
7.00
7.00
7.00.....