Quantitative research is all about what you have measured in your data. Your results will often only be as good as the data that you collect. Your data is what your hypotheses depend on for their testing, and the data is the evidence for answering the questions you want to answer. Understanding your data and the relationships within it is crucial to successful research.

The first thing you will need to consider is how much your data will need to be cleaned and transformed to be in a useful form for analysis. It is extremely rare that data comes in a form that is directly useable for analysis and statistical testing. You will need to decide how to handle missing values, values that have impossible values, and some values that may need to be changed from categorical values to numeric ones. You might end up merging or splitting up collected data to make it useful. The end goal is to have data that can be used for exploratory data analysis, statistical testing, and creating data visualizations. Expect this step to take a significant amount of time.

You will also need to consider where you will store your data and in what form? Where you keep your data will strongly influence your workflow. Will your data be manageable in files, such as comma-separated format, that can easily be loaded into spreadsheet programs and data analysis programs? Taking this route will require careful management of the files and their backup. Or, will your data be such that it needs to be stored in a database management system? This choice will require ensuring the backup of your data, and it is necessary to have a working knowledge of how to get data in and out of the database. Will you keep your data on a local hard drive for storage, or will you utilize a cloud-based resource? Having your data in the cloud allows you to access it wherever you have internet connectivity. Cloud-based resources are appropriate whether you keep your data in files or a database.

Once you have clean and tidy data, you can proceed to explore what you have collected. You will want to know some basic things about your data and do an initial assessment of the relationships that might exist between your variables. You can do histograms of your variables to visualize the shape of their distributions. You can run tests to determine if your variables are from a normal population or other probability distributions. You can create a pairwise correlation plot of all or groups of your variables to visually determine if there are any distinct relationships between certain variables. You might find box plots or other data visualizations suitable for elucidating the secrets hidden within your data.

At some point, you will need to perform your statistical testing. Depending on the volume of data and the particular testing being done, this might be a compute-intensive task that takes quite some time to run. Or, it might involve a series of runs that soaks uptime. From your exploratory analysis, you should have a good idea of how far you from meeting the assumptions of the tests you are using and a justification for using them. Consider ways to visualize the results of your statistical tests, such as plots of residuals.

Lastly, you need to consider the tools you will use to conduct your analysis and create your visualizations. Perhaps you are already proficient with one of the numerous tools available like R, Tableau, SAS, SPSS, and Minitab. Sometimes, it is possible to do your work with a tool like Microsoft Excel. Whichever tool you choose, it is important that you are able to produce output that can be imported into your dissertation documents in an acceptable form and that your visuals are of publication quality.

Assignment: Present a Data Analysis Strategy

Instructions

For this assignment, you must develop a data analysis strategy for your research study. You must then present your design in a presentation.

Your presentation should include the following:

• Title Slide
• Introduction
  • Problem Statement
  • Research Purpose
  • Research Questions
  • Definition of Key Terms
• Review of the Literature
  • Validity of Research Topic
  • Hypothesis
• Research Design
  • Proposed Data Collection Strategy
  • Proposed Data Analysis Strategy
• Resources

• 150-200 words of speaker notes for each slide to assist with the delivery of the presentation
• Recording of your presentation of each slide using the recording feature in PowerPoint

Length: 12-15 slide presentation, with audio recording

References: Include a minimum of 5 scholarly resources.

The completed assignment should address all of the assignment requirements, exhibit evidence of concept knowledge, and demonstrate thoughtful consideration of the content presented in the course. The writing should integrate scholarly resources, reflect academic expectations and current APA standards.

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