Descriptive statistics are simple summaries of your data and measures and can be considered the cornerstone of statistical analysis. Before running most other types of statistical analysis (especially inferential statistics), researchers need to look at descriptive statistics for their data.<\/p>\n\n\n\n
Descriptive statistics are a set of methods used to describe and summarize the key features or characteristics of a dataset. Simply put, descriptive statistics help us consolidate large amounts of data into a concise and easy-to-use form. For example, if we have to examine differences in blood pressure for a sample of 1000 patients pre- and post-intervention, it\u2019s very tedious to check each patient\u2019s data individually. Instead, we can use descriptive statistics to summarize blood pressure levels of the entire sample for each time point. We then need to compare only 2 numbers, which makes our calculations simpler.<\/p>\n\n\n\n
Another important use of descriptive statistics is to understand the distribution of your data \u2013 whether it is normally distributed or not. This is critical in determining the types of tests that you would use for inferential analysis, going forward. Choosing parametric vs non-parametric tests is dependent on the type of data and its distribution.<\/p>\n\n\n\n
Finally, descriptive statistics can be used to conduct simple analysis and draw inferences, for example, measuring change pre and post-intervention.<\/p>\n\n\n\n
Let\u2019s look at the different types of descriptive statistics and how to use them.<\/p>\n\n\n\n
These are used when you want to show how often something happens or a response is given.
Example: Major adverse cardiovascular events were observed in 28\/683 patients (4.09%).<\/p>\n\n\n\n
These are used when you want to show what is most common or typical of a set of data.
Example: Mean pain intensity scores were 2.6 for the intervention group and 4.9 for the control group.<\/p>\n\n\n\n
These are used to indicate how spread out your data are. Usually, they are reported alongside the measure of central tendency you\u2019re using (mean with standard deviation, median with interquartile range)<\/p>\n\n\n\n
While conducting your analyses or writing your research paper, here are five key considerations to keep in mind whenever you choose or report descriptive statistics.<\/p>\n\n\n\n
If you\u2019re looking for an expert statistical analysis service<\/strong><\/a> to support you in choosing and analyzing descriptive statistics, book a conversation<\/a> <\/strong>with our expert consultant today.<\/em> References:<\/strong><\/p>\n\n\n\n
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