How to Choose the Right Data Analysis Method for Questionnaires
Understanding the Different Methods of Data Analysis
A questionnaire is one of the main parts of every survey. It contains the list of questions, you use them to receive the answers, which are the essence of the survey data.
When you choose open-ended questions, they usually demand personal opinion, so you obtain qualitative data. Choosing multiple choice or ranking questions leads to quantitative data, as it can be calculated.
What Are Data Analysis Methods?
As you can see, different types of questions lead to different types of data. Data that can be grouped, added, and calculated is quantitative data. Data that can’t be calculated needs to be processed in other ways, it demands comprehension, therefore qualitative methods are involved.
Though quantitative data is used in most surveys as a reliable source for decision-making, qualitative data can provide fruitful results regarding market performance, brand recognition, or product launching. It is used mainly within focus groups that include experts and professionals.
Qualitative methods are used to analyze qualitative data, and quantitative methods are used to examine quantitative data. Qualitative methods include content analysis, narrative analysis, discourse analysis, and grounded theory. Quantitative methods include calculation of average, percentage, frequency, range, regression, correlation, and variance analysis. Let’s start with the qualitative ones.
Discovering the Different Types of Qualitative Analysis
Content analysis is used for writing content to differentiate between various thoughts and statements in the text. The key to this kind of analysis is to be free of personal biases and superstitions.
Narrative analysis involves the study of opinions, experiences, thoughts, views, or stories of different people. After you gather multiple stories and experiences you choose the most appropriate ones.
Discourse analysis studies the opinions and thoughts of different respondents as a plural and holistic flow of communication. Hence, different stories are viewed as a part of one problem or phenomenon.
The Grounded theory method uses an explanation of the obtained qualitative data as the main tool. Analysts should understand the relation between the data and reality and if it makes sense, she/he should give the needed interpretation of the data or make conclusions.
Exploring the Many Quantitative Analysis Approaches
Those were qualitative methods. Nevertheless, qualitative methods look more appealing as they provide precise data, which can be measured with digits. Average is the most popular numeric method, it is calculated as the sum of all values divided by the total number of values.
Percentage shows the weight of a specific answer in the total sum of answers (out of 100 per cent).
Frequency shows how many times the answer occurred during the survey (in the data set). The higher the frequency, the more important the specific answer.
The range shows the distance between the maximum and minimum. The range is a very important indicator, as it shows fluctuations and volatility.
Regression is a complex quantitative method that examines relations between two and more variables. For example, it can show the influence of one factor on other variables.
Correlation shows the strength of the relationship between variables. For example, you may study the connection between price lowering and demand behaviour.
The last approach to quantitative analysis, which we briefly explain here, is variance analysis. It helps to understand the difference between the planned and the actual performance. For example, if the difference between planned and real numbers is great, then you have to consider a more precise planning method.