A lot of clients came to us for help on data that was collected from questionnaires/surveys, which reminds us the importance and usefulness of the topic – Analysis of Survey Data. We’ll start with data cleaning, briefly discuss several kinds of missing values, and imputation methods for the miss values, such as hot deck imputation, predictive mean matching and multiple imputation. Then, we’ll show the methods to check the reliability and validity of survey information, including definitions, different evaluation methods, and remedies for poor reliability. Inferences from survey data will be discussed in the last part, including topics of checking whether a result can be extended to population, and some useful categorical data analysis methods. For each part, we’ll show how to use R/SAS to conduct these calculations with some real survey data illustrations.