Methods of validating questionnaire

Unlike closed-ended questions, open-ended questions are more difficult to code since it needs human expertise to determine if one response is equivalent to another.In this case, several experts are asked to code the responses in order to minimize bias.Questionnaires can be classified as both, quantitative and qualitative method depending on the nature of questions.Specifically, answers obtained through closed-ended questions with multiple choice answer options are analyzed using quantitative methods and they may involve pie-charts, bar-charts and percentages.Handling nominal data usually includes identifying the percentage of responses per category.Chi-square tests and multi-way tables are commonly used to measure the relationship between nominal scale variables.Data coding simply means converting the nominal and ordinal scale data in such a way that the statistical package to be used can handle the survey data accurately.This step is actually performed when you design the questionnaire, but the data codes become helpful during data analysis.

On the other hand, it is best to use advanced statistical procedures such as Spearman’s rank correlation and Kendall’s tau to determine the relationship among the ordinal scale variables.After administering the survey, the next step in survey research process is to analyze the responses of the participants.Handling survey data includes conducting a precise survey data analysis which lets you interpret the results accurately.Data validation ensures that the survey questionnaires are completed and present consistent data.In this step, you should not include the questions that were not answered by most respondents in the data analysis as this would result to bias in the results.

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