bivariate

Question 1

bivariate analysis

Answer 1

examines the relationship between two variables

Question 2

numerical vs numerical

Answer 2

scatterplots, correlation, linear regression

Question 3

categorical vs categorical

Answer 3

contingency tables, bar charts, chi squared

Question 4

numerical vs categorical

Answer 4

boxplots, t tests, ANOVA

Question 5

null hypothesis

Answer 5

assumes no relationship or difference

Question 6

alternative hypothesis

Answer 6

assume relationship or difference exists

Question 7

steps of hypothesis testing

Answer 7

1. state null and alternative hypothesis
2. compute test statistic from sample data
3. determine p value
4. compare p value to significance level
5. if p value is less than reject null

Question 8

two sample t test

Answer 8

• numerical outcome, categorical exposure
• comparing means of 2 groups (ex: mean age between men and women)
• hypotheses: H₀: μ₁ = μ₂ (no difference in means).
  H₁: μ₁ ≠ μ₂ (difference in means).
• interpretations: Small p-value (p < 0.05) → Reject H₀ → Significant difference.
  Large sample sizes can detect small, but statistically significant differences