Survey data statistical analysis starts with knowing and choosing the right kinds of questions for your survey. The reason why it's important to know the different types of survey questions in advance is that the types of questions asked on surveys will dictate the kind of analysis we can perform and the conclusions we can draw. This is why it is paramount to get your survey questions right first.
Using the Right Questions for Survey Data Statistical Analysis
Your survey questions can be divided into three types. This is sometimes called the Level of Measurement. First, we have category-type queries that are referred to as nominal questions. Nominal questions are ones where survey participants will choose from a list of categories, which may include 'male' or 'female,' or they may include ethnic origin.
Secondly, we have ordinal-type queries that are just like category questions. However, ordinal-type questions have some order between them. For example, you might ask your survey respondents to indicate their age into categories.
Thirdly, we have continuous-type questions. These are the kinds of questions where answers are given with numbers. It might be an open-ended question that asks something like 'How many times have you attended conventions.' It could also involve something like asking the individual to write about the seriousness of some experience they've had.
Steps to Doing Survey Statistical Analysis
The first step of survey data statistical analysis is to code your questionnaire. This means looking at each question and allocating a number for each possible response. For example, on a category-type question about gender, you can allocate 1=male and 2=female. If the question is about age, and it's based on categories, you can allocate your numbers the following way:
1=15-20-year-old age group
2=21-30-year-old age group
And so on.
The next step is to transfer information from questionnaires to a Spreadsheet or a statistical page such as an SVSS. Once the questions have been entered, you need to come up with a strategy for your analysis. Ideally, they should be linked to your research questions.
Getting the Most Out of Survey Questions
The first stage of survey data analysis should be to summarize and describe the responses to each question in turn. For category-type questions, you can count or determine the frequency of the questions. For example, you can find the frequency and occurrence of the males of and females. This is usually reported using percentages, pie charts, and bar charts.
Ordinal questions, such as the responses to various age categories, are reported in the same manner. When it comes to describing and summarizing continuous-type questions, you can use measures of central tendency. This is called the average. However, in research language, we refer to it as the mean, median, and mode.
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