STATISTICAL ANALYSIS
• MAIN FUNTIONS:
1. If you did a CENSUS, statistics
– provide a summary
2. If you ONLY want to DESCRIBE your sample, statistics
– evaluate your sample
– provide a summary
3. If you want to draw know about the population
– statistics allow you to draw these inferences!
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What do you want to know?
1. Univariate numbers
–
Mean, median, mode, standard deviation, variance
• e.g., average home price, number of customers
2. Bivariate relationships
–
In what way do customers differ from non-customers?
• age, sex, income, where they live
3. Multivariate relationships
What is the largest predictor of purchasing?
age, sex, income
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• Covariation
– how strong is the relationship between variables?
• Null hypothesis (Ho)
– no difference
• Alternative hypothesis (Ha)
– there is a relationship between the variables
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• Directionality
– do you have a predicted direction?
• (e.g., customers are more satisfied).
• Degrees of freedom
– how many observations do you have?
• Significance level
– likelihood of relationship occurring by chance
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Statistical analysis
• EXAMINING COVARIATION:
• Who is more likely to buy -- men or women?
• Who buys the most?
• Is income related to likelihood of purchasing?
• Are people who purchase different from those who don’t?
• Is there some underlying pattern among these?
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Independent and Dependent Variables
• INDEPENDENT VARIABLE (IV)
– Cause
• DEPENDENT VARIABLE (DV)
– Outcome
IV DV
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Example 1:
Male
Female
70% [30%]
40% [60%]
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Example 2:
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Choosing among statistics:
– 1. number of independent variables
– 2. level of measurement (nominal to ratio)
– 3. number of dependent variables
– 4. level of measurement (nominal to ratio)
– 5. other considerations (normality)
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