I am currently working on a research that is entitled as ”Influence of the TikTok Application on Chosen Students of 11th Graders from University of San Beda-Rizal”.
The significance of the study are the following:
- If TikTok has any influence on respondents
- What are the aspects that is influenced by TikTok
- Based on the aspects from respondents’ answers, in what way does TikTok influence these aspects?
- Are the influences positive or negative?
The questionnaire is made up of multiple choices, essay type, and likert scale.
What statistical test should I do? I’ve been advised that the Chi-square should be used, others have advised me to use mean and mode.
PROBLEMATIC DESIGN. The research design in this case is not well-formed. By mixing may types of responses in one instrument, you might get internal inconsistency from each respondent due to confusion or distraction.
ESSAY. This is a form of "interview" but the response is written instead of verbal. The problem with is type of response is that it has to be mined and coded before it could be analyzed. The real responses may be lost in the process.
MULTIPLE CHOICE. This is ordinal data. You need to identify success and fail choices then coded success as 1 and fail as 0. The significance may be tested by the deMoivre-Laplace statistic.
LIKERT SCALE. If you treat the scale as score, then run your tests as parametric or non-parametric depending on how you define your X and your Y in the survey.
SUGGESTION. Redefine your variables and reconstruct your instrument. Limit nominal data to demographic info. Limit ordinal data to multiple choice. For LIKERT SCALE, do as stated above. Avoid essay response.
You can use mean or mode-based tests where you have ordinal and/or likert scales in your questionnaire, and chi-square tests for questions where you have nominal scales. On this type of data set, I would also recommend using different multivariate approaches, e.g. exploratory factor analysis and cluster analysis to extract more information than you can do by looking at one variable at the time.
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