Manual Statistical Misconceptions

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Reflections on conceptions of research methodology among management academics Mark N. Saunders , Frank Bezzina.

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Statistical Misconceptions: Classic Edition

Refutation texts compensate for detrimental effects of misconceptions on comprehension and metacomprehension accuracy and support transfer. Risk factors for cardiovascular disease among undergraduate students in Edinburgh, Scotland Nada M. The acute effects of anthocyanin-rich wild blueberries on cognition and postprandial glucose response in healthy young adults Lynne S. Related Papers.

Statistical misconceptions

Nevertheless, the inappropriate assumption of causality is the biggest source of error in interpreting the results of correlation analysis. In , for example, the Journal of Pediatrics published a study in which the authors concluded that eating breakfast can solve the problem of teenage obesity, based simply on the fact that teenagers who do eat breakfast are less likely to be obese. Although the correlation found by the authors indicates a possible causality, it is unlikely that eating breakfast can solve the potential problem of teenage obesity.

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More likely, there is a common cause behind these two phenomena eating breakfast and teenage obesity —poverty, for example—but no direct relationship between them. Similar examples of authors misinterpreting the correlation coefficient are common in the epidemiological literature.

Common misconceptions about data analysis and statistics

One group of researchers, for example, found a correlation between women taking combined hormone replacement therapy HRT and a lower-than-average incidence of coronary heart disease CHD and concluded that HRT lowered the risk of CHD. It was later determined that lower-than-average incidence of CHD is caused by the benefits associated with a higher average socioeconomic status of those taking HRT, not by therapy itself. Studies including this type of error are published even in leading biomedical journals.

For example, a Nature study found a strong association between myopia, or near-sightedness, and night-time ambient light exposure during sleep in children. The authors concluded that it seems prudent that infants and young children sleep at night without artificial lighting in the bedroom.

How not to be ignorant about the world - Hans and Ola Rosling

Correlations, especially the high value of the linear correlation coefficient, may point to the existence of causality, but the conclusion requires systematic examination. Many researchers do make such assumptions, however, thereby falling victim to the ecological inference fallacy. On the basis of this finding, he concluded that chocolate consumption enhances cognitive function and closely correlates with the number of Nobel laureates in each country.

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But without accurate data at the individual level, it is impossible to draw such a conclusion. For example, it was unknown how much and whether Nobel laureates consumed chocolate. Based on the previous two examples, it is clear that high values of the linear correlation coefficient cannot by themselves be sufficient to conclude about the relationship between the variables.