Lecture 9

Question 1

chi squared test (x^2)

Answer 1

• evaluates the probability of how well categorical observations fit expected observations.
• descriptive probability test assesses the conditional probability, aka testing how well observed events fit expected outcomes, or how well two categorical variables correlate
• compares the probability of categorical observations given expected observations.
• always one-tailed. It tests the existence of a difference, not a direction

Question 2

goodness of fit test

Answer 2

• tests the likelihood of an event outcome assuming chance or expected outcome
• AKA how well does the observed data fit the expected data

Question 3

test of independence

Answer 3

• tests whether there’s a relationship between two categorical variables, or whether the variables are independent
• AKA a categorical correlation

Question 4

Cramér’s V

Answer 4

• for chi squared goodness of fit effect size
• for chi squared test of independence when more than 2x2 design; use smallest row/column
• measure of the
  association between the observed and expected values

Question 5

phi coefficient (Φ)

Answer 5

• for chi squared effect size if 2x2 design
• the linear categorical correlation