How to analyze survey data

To analyze survey data, you need to go through several steps including data cleaning, data exploration, and data analysis. Here are some details on these steps and other tips for you to successfully analyze survey data:

• Data cleaning

When analyzing survey data the first thing you must do is a process called data cleaning. This means you need to check your collected information for missing values, inconsistencies, and outliers. You can then clean the data by taking out missing values or making corrections to any errors or inconsistent data.

• Data exploration

Next you need to go into the data exploration phase. Here you examine the distribution of responses to the survey. This will help you detect any patterns and/or relationships between any variables related to your survey. To excel in this phase you should use different visualization methods, such as:

• Scatterplots

• Histograms

• Bar charts

Executing this gives you a deeper understanding of the data you have gathered from your survey.

• Data analysis

Now you move on to the analysis stage. Here you can perform statistical-based analysis on the data you have cleaned. The goal here is to find answers to your research questions. This process can involve specific statistics concepts, such as

• Mean

• Median

• Mode

• Standard deviation

You should also seek to use inferential statistics like hypothesis testing and regression analysis. The particular methods you use depend on your survey format, the contents of your data, and any personal preferences you might have for analysis.

• Report the results

Finally, after your data analysis is complete, you are ready to report your survey results. You should seek to report your data results in a concise and clear way. To do this you might utilize different visual formats, such as:

• Tables

• Graphs

• Charts

These tools are an effective method for illustrating your survey findings. They also help to interpret the findings in the context of your original survey/research question.

• Your research question should be at the forefront of your mind when analyzing the survey data

• Employ statistical software to help your findings remain accurate and also to increase effectiveness and efficiency in your workflow

• Use caution when interpreting your survey results, causal claims solely based on correlation should be avoided

• Make sure your survey sample size is adequate for the goal of your analysis

• Determine if you should utilize a coding system to categorize open-end survey responses