Sampling Variability

Question 1

What is sampling variability?

Answer 1

• Sampling variability: variation in the value of a statistic from sample to sample

Question 2

Distinguish between research questions associated with confidence intervals or hypothesis tests

Answer 2

If a study:

• Estimates the value of a population parameter (descriptive goal)
  
  • Use confidence interval inference procedure
• Assess evidence for a claim about a population parameter/relationship (causitive goal)
  
  • Use hypothesis test inference procedure

Question 3

Compare independent vs. paired data

Answer 3

• Independent: no way of matching the data
• Paired: explicited matches between responses/subjects (siblings, repeated measures)

Question 4

Categorical (1): nomial

Answer 4

• Nominal: values can be named
• Ex., male, female, non-binary

Question 5

Categorical (2): ordinal

Answer 5

• Ordinal: values can be ordered/ranked
• Ex., disagree, agree, strongly agree

Question 6

Quantitative (3): interval

Answer 6

• Interval: distance between successive values is constant
• Ex., numbers
  
  • Note: some studies use numbers to mean categorical values (ex., 1 = strongly disagree)
  • If the number can be replaced with a letter or other symbol and maintain meaning, it is NOT quantitative

In interval data, ratios don’t have logical meaning (cannot be said that 3 is 3x greater than 1)

Question 7

Quantitative (4): ratio

Answer 7

• Ratio: zero means none
• Ex., height of plant
• Something that is not ‘ratio’ would be 0^oC, as 0^oC does not mean an absence of energy

Question 8

Discrete vs. continuous?

Answer 8

Quantitative values are further classified as discrete (2 or 3 cats) or continuous (2.25 or 3.799 seconds)