Common Terms and Equations
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Basic terms and concepts used to collect and present data are essential to using health statistics and to assessing their quality. This section gives an overview of some of the basics of statistical research as it relates to health care, including sampling, confidence intervals, bias, validity, dependent and independent variables, age adjustment (including direct standardization) and more.
- Sampling: Take a look at how a small group of people can help us estimate information about a large population.
- Confidence Intervals: See how to identify how accurate certain data is.
- Correlation and Causation: Differentiate between two different types of relationships between variables.
- Validity: Find out how to measure the accuracy of statistics.
- Dependent and Independent Variables: Identify the different ways variables relate to the people being studied.
- Age Adjustment: Learn how to adapt statistics to account for age differences between communities or groups.
- Hypotheses: Understand the language behind experiment design.
- Normal Distribution: Visualize how data is normally distributed in populations.
- Standard Deviation: Learn about the metric used to describe dispersion of data.
- Z-score Learn a formula to determine a data point’s position along a normal distribution curve in relation to the sample mean.
- t-test and Z-test : Determine statistical significance using these statistical tests.
- Significance Level : Understand how researchers conceptualize statistical significance.
- p-value: The final step, learn the concept behind probability of error.
- Incorporation into Health Subjects: These skills are transferable into any field, take a look at some examples in health research.