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
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CMST300 Exam 3 Chapter 12
2013-11-06 13:51:40
CMST300 Exam

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