Basics of Data analyses

Coding data - assigning categories to responses; Use exhaustive, exclusive categories

Checking data files for errors in data entry

Using Cross-Tabulations to assess relationships

Dividing samples into sub-groups on variables

Computing percentages in each group

Compute percentages in the direction of the causal variable

Look out for incorrect conclusions of relationships

Hypothesis Testing

The logic of hypotheses testing; Null versus alternate hypotheses

Types of errors

Type I error - Rejecting a true null H

Type II error - Accepting a false null

Alpha, confidence level (1-alpha), beta, & power (1 - beta)

Procedure in hypotheses testing

Examination of Differences

Hypotheses about 1 mean

Hypotheses about 2 means

More Data analyses

Correlation

Looking for relationships between variables

Applications:

Regression

Representing relationships between independent and dependent variables in the form of an equation

Applications

Discriminant analysis

Using an equation to discriminate between groups

Applications:

Factor analysis

Looking for factors (i.e., combinations of variables)

Applications:

Cluster analysis

Putting objects into groups such that objects within a group are similar to each other and different from objects in other groups

Applications:

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