Creating a Data Analysis Plan

These are a few tips that can be followed in order to create an effective data analysis plan: 

• Go Back to your Goals and Research Questions

By going back to the goals and research questions that you had initially outlined, you can refocus on the objectives of your study. This will allow you to plan how you’re going to organize survey data while keeping these goals and research questions in mind. 

• Analyse Results for your Top Research Questions

Data analysis plans usually begin with the analysis of responses to the primary research questions within the survey. Responses to these questions are the foundation of your topline results.

• Organize your Questions

In order to extract an insightful understanding of your survey data, you must organize survey questions by attributing each one to your rop research question. This helps categorize responses and can outline which data you require to answer the main questions of the survey. 

• Create Demographic Groups

An important part of identifying the significance of the data collected, is identifying different demographic groups by segmenting survey respondents.In order to do this, demographic questions must be included within your survey. These questions must extract information on variables such as age, gender, institution, and more. By understanding the ways in which different demographic groups respond differently to your survey, you can gain perspective that will help you turn data into actionable insights. 

• Understand the Statistical Significance of Data Collected

It is important to be sure that your respondents are representative of your target population. If random sampling, for instance, was used to select a sample group, a more arbitrary group of individuals are responding to your survey. It is important to understand the statistical significance of the data collected, as a low statistical significance will have a higher probability for error, giving you unreliable results. 

• Outline the Difference between Correlation and Causation

Every aspect of the data must be analysed before making assumptions, as certain correlations found within the data may not have a causal relationship. You want to avoid drawing any inaccurate conclusions; hence, you must analyse any correlation before expressing a relationship between the variables.

• Compare Survey Results with past Data

Comparing your survey results with data collected in the past will give you an idea of trends and can help you understand whether your company is doing better or worse over time. If this is your first time collecting data, make sure you use these results as a benchmark for your next data analysis.