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Ordering and grouping data 1

The purpose of this assignment is to practice organizing data through ordering and grouping variables.

Data often appear disordered and it is difficult to see any connections or relationships. Ordering the data by certain variables or grouping variables into specific categories, such as age or sex categories, can help bring clarity to the data. Knowing how to organize data is an important skill to initiate the analytical process.

For this assignment, students will use Excel and SPSS Statistics to order variables. Using the “Example Dataset,” complete the steps below using both Excel and SPSS Statistics. View the Excel and SPSS tutorials for assistance in completing this assignment. Submit one Word document and include a screen shot of the data after completing the first two steps of Part 1 in Excel and SPSS to compare your results. Use a second Word document to complete Part 2 of the assignment.

Part 1: Ordering and Grouping Data Using Excel and SPSS

For Part 1, accomplish the following:

  1. Order (sort) observations according to age.
  2. Group observations by sex and investigate the age and income for males and females.
  3. Create a new variable titled “Exercise Group” based on the variable “Minutes Exercise.” Use the following categories to create your groups: 1 = 0-30 minutes; 2 = 31-60 minutes; 3 = 61-90 minutes; 4 = 91-120 minutes; and 5 = 120+ minutes.

Part 2: Data Interpretation

Study the results of the dataset grouping and ordering. Discuss the following in a 500-750 word summary:

  1. Describe the measurement levels for each of the variables in the dataset.
  2. Discuss what you learned from ordering the data by age and why this information is important.
  3. Describe the process you used to group the data in Excel and SPSS.
  4. Describe what you learned by grouping the variables by category of exercise.
  5. Are these data from a correlational study, experimental study, or quasi-experimental (observational) study? Discuss your rationale and identify a study question appropriate for this dataset.

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