However, we might equally have: 1=brown eyes, 2=green eyes, 3=blue eyes. We might have: 1=blue eyes, 2=brown eyes, 3=green eyes. Nominal variables (from Latin for name) are things like eye colour or hair colour.
Variables can broadly be divided into two types, categorical and numerical.Ĭategorical variables can be dichotomous (also called binary), nominal or ordinal. Examples include pi (approximately 3.142) and e (approximately 2.718). In contrast, a constant is something that always keeps the same value. For example, height, weight and gender are variables. In this section you will learn about continuous, categorical and nominal variables.Ī variable is by definition, something that you measure that is able to vary. When undertaking any statistical analysis, the type of statistics calculated or statistical test undertaken depends to a large extent on the type of variable being analysed. When we draw conclusions about the whole population based on our sample data, it is called inferential statistics, because we are making inferences about the population based only on sample data. When we describe our sample in terms of for example, average age, or percentage female, we are undertaking descriptive statistics. Apart from a national census, it is usually impossible to collect information on everyone in the population, for either logistical or cost reasons. Whenever we collect health information, it is invariably on a sample. Describe the mean, median, standard deviation, range, IQR and correlation coefficient.Use correct descriptive statistics for categorical and numeric variables.Appreciate the rationale for using statistics in health sciences.On completion of this topic students should be able to: Having an understanding of statistics will empower health professionals and provide them with key tools in both understanding and applying evidence in their practice. Examples include interpreting clinical values measured on a patient, understanding clinical guidelines or departmental reports, and importantly, reading scientific papers in order to assess the evidence for treatment. Health professionals are confronted with statistics on a daily basis.
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