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Univariate Analysis. The first step to analyzing data. Quantitative Data Analysis. Purpose It is the examination of variables and relationship among variables using numbers. summarized a variable examine relationship among variables To test hypotheses . The first step.

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univariate analysis

Univariate Analysis

The first step to analyzing data

quantitative data analysis
Quantitative Data Analysis
  • Purpose
    • It is the examination of variables and relationship among variables using numbers.
    • summarized a variable
    • examine relationship among variables
    • To test hypotheses
the first step
The first step
  • To become familiar with each variable that you intend to use in your analysis.
    • Make sure that variable has enough cases across responses for meaningful analysis.
    • To reorganize the responses to an original variable to better suit the specific analysis to be undertaken.
  • To accomplish this must examine each variable separately. This is called Univariate analysis.
types of analysis appropriate for different types of variables
Types of analysis appropriate for different types of variables.
  • Categorical Variables
    • Frequency distributions
    • Bar graphs
  • Numerical Variables
    • Measures of central tendencies
      • Means, modes, medians
    • Measures of spread
      • Standard deviation
      • Range
      • histograms
frequencies
Frequencies
  • The number of cases that fall into each attribute of a variable.
    • Categorical variables
      • The number cases and percent of total cases that fall into each response category of the variable.
    • Numerical variables
      • The number of cases for a variable that fall into each possible response category.
examples of categorical variables using race of respondent from gss dataset
Examples of Categorical VariablesUsing Race of Respondent from GSS Dataset
  • Say we want to test the following model and hypotheses:
  • An we want to first just look at relationship between age and stereotypical attitudes using a table that will tell us the number of people in an age group by their racial attitude called a crosstabulation.

age

Interaction with blacks

Negative Attitude towards blacks

Race/ethnicity

the actual indicators
The actual Indicators
  • Age asks respondents their age at the time of the interview.
    • Numerical
  • The dependent variable negative attitudes will be created from 3 categorical variables that asked respondents how most people in the group (blacks) can be characterized on each of the following characteristics:
    • Rich vs. poor
    • Hard-working vs. lazy
    • Violence prone vs. not violence prone
    • Unintelligent vs. intelligent