
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!
Marketing Research
7/17/2016
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Univariate numbers
1.
◦
Mean, median, mode, standard deviation,
variance

e.g., average home price, number of customers
Bivariate relationships
2.
◦
In what way do customers differ from noncustomers?

age, sex, income, where they live
Multivariate relationships
3.
◦
What is the largest predictor of purchasing?

age, sex, income
Marketing Research
7/17/2016
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
INFERENTIAL Statistics
◦ Would the sample results apply to the population?

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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7/17/2016
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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
Marketing Research
7/17/2016
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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?
Marketing Research
7/17/2016
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
INDEPENDENT VARIABLE (IV)
◦ Cause

DEPENDENT VARIABLE (DV)
◦ Outcome
IV
DV
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Male
Female
Bought [Did not]
70%
[30%]
40%
[60%]
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Male
Female
Purchase Price
$60K
$50K
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Choosing among statistics:
◦ 1.
◦ 2.
◦ 3.
◦ 4.
number of independent variables
level of measurement (nominal to ratio)
number of dependent variables
level of measurement (nominal to ratio)
◦ 5. other considerations (normality)
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