1. Define each of the following scales and provide at least one example for each:
• Nominal Scale
• Ordinal Scale
• Interval Scale
• Ratio Scale
2. Briefly explain why the scale of measurement is important and relevant to statistics (3-4 sentences).
3. Define each of the following types of distributions and provide at least one example of a data that would likely create the type of distribution:
• Normal Distribution
• Positive Distribution
• Negative Distribution
• Bimodal Distribution
• Inverted U-shaped Distribution
4. Define each of the following measures and provide at least one example of the most appropriate instance when to utilize the type of measure (also include the appropriate Greek symbol for each):
• Mean
• Median
• Mode
• Range
• Standard Deviation
5. Displays a data set for 20 cases. Manually enter the data in SPSS and then follow the directions on the subsequent pages and create the frequency tables and graphs. Once completed, copy and paste the output tables here. You should resize the images once pasted in this document to ensure a good fit. Tip: Before entering the data you will first need to select Variable View (bottom left tab) and enter the names CaseId and Weight.
6. Below is a cross-tabulation table of data from a 12-week study of diet and exercise. Compute the following probabilities (show the calculations):
• Marginal Probability
• Joint Probability
• Conditional Probability
|
Achievement of Goal Weight
|
|
Weight Loss Strategy
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Achieved Goal Weight
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Did Not Achieve Goal Weight
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Total
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Diet alone
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20
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80
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100
|
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Diet and exercise
|
60
|
40
|
100
|
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Total
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80
|
120
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200
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Hypotheses and Significance
7. Define each of the following terms and provide at least one example for each (include the statistical symbols for each:
• Null Hypothesis
• Nondirectional Hypothesis
• Directional Hypothesis
• Statistical Significance
• Type I Error
• Type II Error
• Power