Survey Analysis

Learn how to correctly analyze survey data so results can be used to accurately inform decisions.

Challenge

Proper data analysis is a crucial step in understanding the results of your project. It is important that data analysis is done correctly so results can be used to accurately inform decisions.

Solutions

Analyzing your Data

There are a number of software programs designed to analyze research data. Before starting your analysis, the data should be reviewed to identify and correct errors that may have occurred as the information was gathered. University Survey & Assessment Services (USAS) and CLA-OIT Research Support Services offer professional data analysis services.

Below is a description of the most popular data analysis packages used at the University of Minnesota:

Sometimes the language used to analyze survey data can be confusing. Here is an explanation of common terms:

• Descriptive Statistics: statistics that describe the sample data without drawing inferences about the larger population.
• Inferential Statistics: statistics that describe the sample data by drawing inferences about parameters of the population(s) you have sampled.
• Cumulative Frequency: the sum of the number of occurrences within a given answer, including all responses up to the present; increases with each successive addition.
• Frequency: the number of occurrences within a given answer.
• Mean: the average, or sum of responses divided by the number of responses.
• Median: the mid-point; a numeric value separating the lower half of the results from the upper half.
• Response Rate: the number of people who answered the survey request divided by the number of people in the sample; usually expressed as a percentage
• Standard Deviation: a measure of the variability from the average response; the average distance of scores from the mean score.

The task of data analysis becomes more complex when the number of items or questions is large. A frequency table can be constructed for each item on the survey, but this can result in upwards of 50 or 100 tables. As the volume of statistics increases, the problem becomes one of organizing the results into a coherent and meaningful set of findings. 

Reporting your Findings

The final step of a survey project is reporting the findings. Reports should be informative, relevant to the target audience, and customized to the individual or organization’s needs. Reports can be presented as visual presentations, written, or electronic reports.

A comprehensive, formal report generally includes the following elements:

1. Title Page
2. Table of Contents
3. Executive Summary
4. Contextual Background of the Research and Purpose
5. Survey/Research Population
6. Research Methodology
7. Conclusion and Recommendations
8. Appendix
9. Contact Information

Not all reports require each of the above elements. In fact, the method, scope, and type of project often determine which style of reporting is used. Other popular styles for reporting survey findings include:

Some factors to consider when writing a successful report include:

• Formatting: Keep the report organized to make it easier for the reader to comprehend the findings by using color and headings.
• Language: The language used in the report should be appropriate for the audience. Make the information understandable, define any terms that may be unfamiliar, and summarize the findings. The report writer can also use images or visual representations sparingly.
• Voice: All findings, interpretations, conclusions, and recommendations should be written objectively. Similarly, if the data is off-putting, present it in an informative manner rather than a judgmental manner.