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How to prepare a data interpretation
Data interpretation may be the most important key in proving or disproving your hypothesis. It is important to select the proper statistical tool to make useful interpretation of your data. If you pick an improper data analysis method, your results may be suspect and lack credibility.
Before doing any statistical analyses of the data you have collected, look closely at the data to determine the best method of organizing it By visually scanning the data and reorganizing it, you may be able to spot trends or other anomalies that may help you in your analysis of the data.
Descriptive statistics provide a description of what the data look like. They provide a means to describe the points of central tendency (mean, mode, median, etc.) and dispersion (standard deviation, variance, interquartile range, etc.
Using statistics to determine relationships is paramount to the success of good research. Using tools such as ANOVA, correlations, Fisher Exact Tests, regression, etc. can also be used.
These are the key points to be borne in mind.


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