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IDENTIFY THE VARIABLES YOU HAVE AVAILABLE. GENERATE A HYPOTHESIS. RUN DESCRIPTIVE STATISTICS. PUT TOGETHER YOUR FIRST TABLE.
Summarize the data. For example, make a pie chart. Find key measures of location. Calculate measures of spread: these tell you if your data is tightly clustered or more spread out. Make future predictions based on past behavior. Test an experiment's hypothesis.
Anatomy of a statistical analysis section Begin by stating what kinds of data do you have, categorical or numerical. Then explain how you expressed those data. For example: 'Weights of widgets were expressed as means ± standard deviation. Categorical data (widget class) were expressed as frequencies'.
Statistical data should be interpreted correctly. Write a persuasive essay that provides the reader with an opportunity to make a verdict based on your arguments. Include visuals such as tables and graphs in your essay. Have the idea of what the audience expects during analysis of the data.
Name the goal of the research. For example, fill some gap in the data, resolve a problem, disprove some statement, or else. Give a brief overview of the most important results. Don't overload your text with terms and numbers in the Introduction.
The introduction should include the conclusion. Do not explain the basic principles of statistical analysis! Do not try to say too much in one paragraph. Test whether your report enables readers to reproduce the procedure you used.
Without an appropriate preliminary statistical analysis to make the important points stand out and, without an e client organization and presentation, the reader might be lost. In a statistical report, graphics show the data that is analyzed in the text.
Means: Always report the mean (average value) along with a measure of variability (standard deviation(s) or standard error of the mean). Frequencies: Frequency data should be summarized in the text with appropriate measures such as percents, proportions, or ratios.
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