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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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1.
2.
3.
Univariate numbers
◦ Mean, median, mode, standard deviation, variance
 e.g., average home price, number of customers
Bivariate relationships
◦ In what way do customers differ from noncustomers?
 age, sex, income, where they live
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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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 VARIABLE (IV)

◦ Cause
DEPENDENT VARIABLE (DV)
◦ Outcome
IV DV
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Male
Female
70% [30%]
40% [60%]
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◦ 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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