Class Notes (837,550)
Canada (510,314)
Brock University (12,132)
CHYS 3P15 (11)
Lecture 9

Lecture 9, Mar 12.docx

6 Pages
Unlock Document

Child and Youth Studies
Patricia Kirkpatrick

3P15, Mar 12, Lecture 9 Chapter 12 Bivariate Statistics for Nominal Data Introduction • Social scientists are interested in uncovering the associations or relationships between several variables. • To simultaneously analyze two variables that cannot be ranked or ordered, you need to use bivariate analysis for nominal variables. Some Sample Research Questions • Are members of particular visible minority groups more susceptible to certain diseases? • Are men more likely than women to gamble? • Are Torontonians more likely than Edmontonians to be homeowners? • Does this differ for men and women? What You Need to Begin Answering these Questions • A representative sample • A knowledge of the level of measurement of each variable • A knowledge of bivariate statistics and measures of association Analysis with Two Nominal Variables • The first step for performing bivariate analysis is organizing the data so that patterns can be easily discerned. • It is useful to create a frequency table, with the information organized into two columns (e.g., Table 12.1). • The variable that we think is modifying the outcome is an independent variable. • The outcome of interest is the dependent variable. • *Note that these will not always be clear* Effectiveness of a Pizza Commercial on Television Response of Respondent to Television Commercial f Order a Pizza 40 Grab Food from the 100 Refrigerator Change Channels 110 No Reaction 750 Total 1000 Bivariate Statistics: Visualizing a Relationship • Need to make data intelligible to identify the existence of relationships • Often convenient to use a cross-tabulation or contingency table • Put independent variable (IV) in columns, dependent variable (DV) in rows (if known) A Bivariate Contingency Table Sex of Response of Respondent to Respondent Television Commercial Female Male Order a Pizza 10 30 Grab Food from the Refrigerator 60 40 Change Channels 60 50 No Reaction 490 260 Total 620 380 Measures of Association • It is always useful to able to see relationships in bivariate tables. • It is also useful, however, to have a single number to indicate the significance of the relationship. • Is there a significant relationship between sex of respondent and reaction to pizza commercial? The Chi-Square Test of Significance • Introduced by Karl Pearson in 1900 • Useful for determining whether a rel
More Less

Related notes for CHYS 3P15

Log In


Join OneClass

Access over 10 million pages of study
documents for 1.3 million courses.

Sign up

Join to view


By registering, I agree to the Terms and Privacy Policies
Already have an account?
Just a few more details

So we can recommend you notes for your school.

Reset Password

Please enter below the email address you registered with and we will send you a link to reset your password.

Add your courses

Get notes from the top students in your class.