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Discussion: Performing Data Analysis

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Data analyses cannot be performed until data hasbeen cleaned. In fact, many of the errors found in standard dataanalyses can be traced directly back to “dirty” data. In a perfectworld, collected data would be flawless, but as when working with humansin any capacity, errors occur.

To begin the cleaning process, you first need tocheck collected data for errors, problems, dubious responses, and otherissues. Many such checks may be done electronically using statisticalsoftware. Once the proper adjustments are made, you can run theanalyses. Which analyses techniques you use should align with yourhypothesis. In other words, a survey researcher uses his or herhypotheses to drive the data analyses. The hypotheses dictate the”family” of analyses used for the data. The more parsimonious andtestable the theory driving the hypotheses, the more straightforward thedata analyses will be.

To prepare for this Discussion, consider whydata cleaning, including the assessment of missing data, is important.Then think about the role that descriptive statistics plays in dataanalyses. Finally, consider the relationship between hypothesis(es) anddata analyses and how you would illustrate this relationship using atleast one of your hypotheses and data analytic strategies from yourFinal Project as an example.

With these thoughts in mind:

Part 1

Post an explanation of theimportance of data cleaning, including assessment of missing data.Provide one example of data cleaning and the potential impact it mighthave on data analyses. Then explain the importance of descriptivestatistics in data analyses. Finally, explain the relationship betweenhypothesis(es) and data analyses using at least one of your hypothesesand data analytic strategies from your Final Project as an example.

Be sure to support your postings and responses with specific references to the Learning Resources.

Read a selection of your colleagues’ postings.

Part 2

Respond to at least two of your colleagues’ postings in one or more of the following ways:

• Ask a probing question.
• Share an insight from having read your colleagues’ postings.
• Offer and support an opinion.
• Validate an idea with your own experience.
• Make a suggestion.
• Expand on your colleagues’ postings.

Return to this Discussion in a few daysto read the responses to your initial posting. Note what you learnedand/or any insights you gained as a result of your colleagues’ comments.