## 13.7 Observing relationships: The NHANES study

In Sect. 12.10, the NHANES data were introduced [, , ), and graphs were used to understand the data relevant to answering this RQ:

Among Americans, is the mean direct HDL cholesterol different for current smokers and non-smokers?

Using the software output (jamovi: Fig. 13.12; SPSS: Fig. 13.13), the direct HDL cholesterol can be summarised numerically:

• Average value:
• Sample mean: $$\bar{x} = 1.36$$mmol/L.
• Sample median: $$1.29$$mmol/L.
• Variation:
• Sample standard deviation: $$s=0.399$$mmol/L.
• Sample IQR: $$0.49$$mmol/L.
• Shape: Slightly skewed right (from Fig. 13.1 or 12.38).
• Outliers: SPSS identified some outliers (Fig. 12.38), mostly unusually large values.

The RQ is about comparing the mean direct HDL cholesterol in the two smoking groups, so compiling a table of summaries for each group is useful, using different output (jamovi: Fig. 13.14; SPSS: Fig. 13.15). Table 13.8 shows the numerical summaries of direct HDL cholesterol for each group.

TABLE 13.8: Summarising quantitative data
Group Sample size Mean Median Std. dev. IQR
All participants: 8474 1.36 1.29 0.399 0.49
Smokers: 1388 1.31 1.24 0.424 0.52
Non-smokers: 1668 1.39 1.32 0.428 0.54
Notice that information about current smoking status is unavailable for all people in the study. This could impact the results, especially if those who provide data and those who do not are different regarding direct HDL.

The RQ, as usual, asks about the population. The RQ cannot be answered with certainty, only using a sample, since every sample is likely to be different.

Clearly, the sample means are different, but the RQ asks if the population means are different. Broadly, two possible reasons could explain why the sample mean direct HDL cholesterol is different for current smokers and non-smokers:

• The population means are the same, but the sample means are different simply because of the people who ended up in the sample. Another sample, with different people, might produce different sample means. Sampling variation explains the difference in the sample percentages.

• The population means are different, and the difference between the sample means simply reflects this difference between the population means.

The difficulty, of course, is knowing which of these two reasons (‘hypotheses’) is the most likely reason for the difference between the sample means. This question is of prime importance (after all, it answers the RQ), and is addressed at length later in this book.

### References

Center for Disease Control and Prevention. National Center for Health Statistics. Third National Health and Nutrition Examination Survey, 1988–1994, NHANES III Laboratory Data File [Internet]. Hyattsville, MD: Public Use Data File Documentation Number 76200; U.S. Department of Health; Human Services, Centers for Disease Control; Prevention; 1996. Available from: https://wwwn.cdc.gov/nchs/data/nhanes3/1a/readme.txt.
Center for Disease Control and Prevention (CDC). National Center for Health Statistics. National Health and Nutrition Examination Survey Data. Hyattsville, MD: U.S. Department of Health; Human Services, Centers for Disease Control; Prevention; 1988--1994.
Pruim R. NHANES: Data from the US National Health and Nutrition Examination Study [Internet]. 2015. Available from: https://CRAN.R-project.org/package = NHANES.