Data which exist in categories that only have 2 possible values are known as binary data. “Yes” or “No” survey responses, dead or alive, male or female, etc. are examples of binary values. These data can be expressed as proportions (e.g. the proportion of male students in a class), are known as binomial variables, and follow a binomial distribution. The
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Most introductory statistics courses include a section explaining Type I (false positive) and Type II (false negative) errors in hypothesis testing. If you have been through such courses, you would have learned that the tolerance for Type I error is set by the significance level (alpha =0.05; the usual default) while Type II error is controlled by statistical power which
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In doing research, we apply the scientific method to answer questions. For example, does cigarette smoking cause lung cancer? What are the mechanisms of weakness after stroke? Why do cells become cancerous? What properties are specific to the poison of South American tree frogs? We want to understand all the individuals being studied (i.e. people, cells, frogs, etc.) but it
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An important part of conducting sound science involves interpreting data correctly. Unfortunately, we don’t do that very well. For example, we are fooled by regression to the mean, we report findings when there are none, and we are overconfident about statistical power and significance. As scientists and lay persons, we want to be certain about research findings. But statistics only
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Many medical and scientific questions are the sort that cannot be answered using randomised study designs. For example, Does cigarette smoking cause lung cancer?, What is the risk hip fracture in adults?, and Do rats indirectly destroy coral reefs? Scientists often use observational cohort studies to answer these types of questions. In cohort studies, (1) a sample of subjects or
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The pressure to publish and current incentives that reward highly-cited discoveries leads to research findings that are not reproducible and inadvertently results in the natural selection of bad science. It is difficult to encourage scientists to take effort in conducting reproducible and rigorous research without better incentives. What kinds of metrics and incentives might reward scientists for conducting sound science?
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Scientifically Sound 