CMST300 Exam 3 Chapter 12

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1. Inferential statistics
can show how variables relate to one another, help us to draw conclusions about a population based on a sample.
2. Standard error
The extent to which the sample estimates will be distributed around the population parameter

how close our findings match what we should find in the population

*error decreases as population increases
3. Assumptions of standard error
• 1. Samples must be drawn from a population
• 2. Assumes simple random sampling
• 3. Assumes 100% completion rate
4. H1
Hypothesis, Statement that tells us how we expect variables to be related.
5. H0
Null hypothesis, statement that says there is no relationship.
6. Type I Error
When Null is true, but is rejected
7. Type II Error
When null hypothesis is false, but we mistakenly fail to reject.
8. How do you prevent a type I error?
set a standard for .05
9. To prevent a type II error
• have a larger sample
• use interval/ratio data
• use a directional hypothesis--say it goes one way instead of saying its different
10. Chi-Square
1 categorical variable

eg. do political ads attack policy or character more often
11. T-Test
• IV: 1 categorical variable with TWO groups
• DV: 1 continuous variable (amount of disclosure)
12. ANOVA
**Analysis of variance

• IV: 1 categorical variable with 3+ groups
• DV: 1 continuous variable (number of hours on homework)
13. Correlation
**Test of association

• IV: A continuous variable (exam grade)
• DV: A continuous variable
 Author: calhounk1 ID: 245374 Card Set: CMST300 Exam 3 Chapter 12 Updated: 2013-11-06 13:51:40 Tags: CMST300 Exam Folders: Description: cmst300 Show Answers: