Teach Using Xl Data Help Marketing Research

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Teach Using Xl Data Help Marketing Research

Week 5 10pts “Correlation on Project” Assignment (please leave at least two blocks of time of a few hours each to do this assignment)

Part 1: (Individually) review Ch.10-11.

  1. Give a description of the analyses appropriate to each of the four objectives found in Table 11.1: 1) Summarizing, 2) Generalizing, 3) Comparing, 4) Relating.
  2. Review Figure 11.1: Write a research question based on your project topic that would investigate to difference between groups. Write a research question based on your project topic that would investigate a relationship between two variables (i.e., when there is more of one, there is more/less of the other).
  3. What would you like to test from your pretest project survey: Does it use a crosstab, correlation, or regression (see Figure 14.13)?

Part 2: With your Team, share the progress on your team project. Are you on track? Note the policy that all team members submit all team assignments while listing all contributors on the top of each assignment. Non-contributors are penalized.

In order to include your chosen analysis result from your pretest survey, you will need to use StatCrunch or XL Data Analyst. I will teach using XL Data Analyst:

(Here is a video on How to Analyze Your Own Data using XL Data Analyst youtu.be/NqBJPsY6Rdo.)

  1. First, open your AAConcepts data file (from Week 2) and delete the data: Click in the upper-left above the spreadsheet to select-all, click Home tab, then click Clear All in the upper right.
  1. Then, click File – Save As and enter the new filename with your pretest survey data entered into it to save your pretest data.
  1. Enter your first question as a variable name in cell A1. Ex: “Gender” or “Satisfaction.”
  1. Enter the rest of your survey questions are variable names in the following columns for row 1.
  1. Take the survey responses one at a time: Number them, starting at “2” to designate “Row 2.” You may even number them as “Respondent 1, Row 2,” if you wish.

Remember a respondent is a row. All of a single respondent’s responses take up a row. Enter the first respondent’s responses in row 2, corresponding to each question-variable. Make sure what they are answering is what you’re variable name/column represents.

  1. A word about coding: If you have a categorical variable, such as Gender, put in a 0 for Male and a 1 for Female (p.335). If you asked about a categorical variable, such as Job Type, code and key in each different type as a different number, making sure you wrote down for yourself which number corresponds to which Job Type: For example, 1 is for Education, 2 is for Business, 3 is for Software Programming, 4 is for Healthcare.

In addition, if you have more metric-type answers, such as Strongly Disagree, Disagree, Neutral, Agree, Strongly Agree; put in a 1 for Strongly Disagree, 2 for Disagree, 3 for Neutral, 4 for Agree, and 5 for Strongly Agree.

  1. Enter each respondent’s responses on each corresponding row.
  1. Next, click the “Define Variables” tab. Select blocks B1:B4 through the end of the Define Variables columns and click “Home – Clear Contents.” Your “Define Variables” sheet should now be cleared. Hit “Save.”
  1. Click on the Data tab, select and copy the first row — the variable names. Click on the Define Variables tab and click on first cell, B1, and right-click to Paste Special – Paste Link (N), to paste in the “Variable Labels.”
  1. Under each Variable Label in the Define Variables sheet, enter in the Value Codes for each (you may skip “Description,” if you wish): The Value Codes are the possible numerical responses for the question, as in 1,2,3,4,5. There may not be any spaces in Value Codes whatsoever.
  1. Under each Variable Label in the Define Variables sheet, enter in the Value Labels for each (e.g., 1=Male, 2=Female).

Value labels will appear in XL Data Analyst tables in place of the value codes. Hit “Save.”

  1. Now that you’ve entered all of your data in your saved file, you can use XL Data Analyst to run an analysis. From Figure 14.13, which analysis do you choose: Crosstab, Correlation, or Regression?
  1. For a Crosstab, use Figure 14.3 and Figure 14.4. Start by clicking on the Add-In, XL Data Analyst – Relate – Crosstabs.
  1. For a Correlation, use Figure 14.8 and Figure 14.9. Start by clicking on Relate – Correlate.
  1. For a Regression, use Figure 14.11 and Figure 14.12. Share the table you get as a result.

Part 3: With your team, share the following sections from your project:

1. Statement of the problem. Include a situation analysis with your primary and secondary research included. If you have completed your pretest analysis result, include it here. Remember, under each table in a paper, write a sentence or two describing the table and the findings including the numerical result and significance. Determine the probable cause of the problem.

2. The research objectives. Include hypotheses, sample, constructs, and unit of measurement.

3. The research method proposed by the researcher to accomplish the research objectives.

4. 4+ references reference list. Include at least 5+ in-text cited facts.