Step 1: Formulate a main research question and 3 sub questions.
Look at the objective of the study; what information do you need in order to meet the objective of this study? Note: The effectiveness can be measured for different groups of respondents. What would be an
interesting question to research? Formulate the research (sub)questions in such a way that the answers can be found by performing the following analyses techniques: correlations and hypothesis testing. In other
words, each question should include at least two concepts or variables. Examples of such questions are:
• To what extent do men and women differ in their alcohol consumption?
• To what extent does alcohol consumption affect one’s mood?
Determine which variables you need to analyse to answer your research questions.
Step 2: Explore and clean your data set.
Determine the measurement level of the variables in the dataset that are related to your research questions, and define them as such in the dataset. Explore these variables, using descriptive statistics and graphs.
Note down any anomalies, outliers, or extreme skews or multimodalities in your distributions that you can identify using these methods. Visual tools help the researcher identify anomalies, outliers, and trends in
data.
Step 3: Analyse the chosen variables with descriptive statistics and inferential statistics.
Descriptive statistics inform us on average measurements of a scale or item, how much these measurements vary across observations, the range of measurements, and other aspects you might want to know
about your data. Besides frequency tables and contingency tables, this form of analysis also includes creating visual representations of your data with bar graphs, pie charts, histograms, and scatter plots.
Perform further analyses necessary to answer your research questions, using correlations, confidence intervals and hypothesis testing.
Step 4: In a concluding paragraph answer your research questions, problem statement and report on the objective of the study.
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