Data analysis is one of the most important steps in conducting a research study. It is very important that the researcher is very accurate and careful when working with the data by continually checking and double-checking their work. As the saying goes, garbage in, garbage out. Likewise, Samuel Johnson once said, "It is more from careless about truth than from intentionally lying that there is so much falsehood in the world."
If a researcher makes one thoughtless mistake in data analysis, such as mistyping one number, then their entire research study can be incorrect. When a research study is incorrect, then the recommendations made for educational practice will likely be unproductive, and can even hinder student learning. For example, suppose a research study concludes that an expensive teaching method significantly improves learning. However, the researcher was careless in entering her data. If she would have been accurate in data entry, then the statistics would have shown that the expensive teaching method did not improve student learning. But, because the study incorrectly reported that the teaching method helped student learning, schools spent huge sums of money to adopt this teaching method. This is highly unethical because that money could have gone to teaching materials or textbooks that actually does improve student learning. Thus, student learning was negatively affected by a careless researcher. Therefore, a researcher should always check, double-check, triple-check, and quadruple-check their work at every stage in the data analysis process.
If the research study has been well planned out, then the data analysis step is actually quite straight-forward. The statistical techniques for analyzing the Research Questions and Research Hypotheses should have already been identified in Method of Data Analysis. However, there are a few steps that need to be completed before these statistics can be calculated, each of which will be described in turn.
Much time and effort will be saved if the statistics are calculated on the computer. The next four pages will describe how to code the data (e.g., enter data into the computer), how to calculate descriptive statistics so the reader has a better understanding of the sample of the study and to answer the research questions, how to calculate the inferential statistics to analyse the Research Hypotheses, and finally how to best communicate the results of the statistics by creating Tables and Figures. Finally, reporting the statistics will be described in Writing the Results.
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