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The purpose of this guide is to learn how basic statistics for data analysis. This guide explains some basic concepts in statistics and apply them to creating confidence intervals and hypothesis tests that will help you and your audience understand your data most.

METHOD
1Step 1
Identifying Types of Data

Data can be categorical or quantitative. Categorical data is generally used to estimate proportions of different populations, while quantitative data can be statistically analyzed.

2Step 2
Ways of Organizing Data

Aggregating data is useful to make one-dimensional statistics like “90% had a good understanding of waterborne disease.” Cross-tabulating data can show how a respondent’s answers to different questions may be linked.

3Step 3
Basic Statistical Parameters

Basic statistical concepts such as distribution, mean, median, mode, standard deviation, etc. can illustrate different findings from the survey results. These techniques are useful in telling different stories about the data.

4Step 4
Common Analyses

Statistical techniques such as measuring the confidence interval or the Chi-Squared test can measure the margin of error in the statistical parameters and quantify the likelihood that cross-tabulated data are related.