Module 7

Question 1

What are the different types of bias?

Answer 1

Selection Bias: Underrepresentation of groups.

Nonresponse Bias: Difference between respondents and nonrespondents.

Social-Desirability Bias: Gap between “socially acceptable” and actual responses.

Question 2

What is simple random sampling?

Answer 2

Equal chance for all samples

Every sample of size n has an equal chance of being chosen.
Used in most statistical methods for unbiased results.

Question 3

What is stratified sampling?

Answer 3

Divides population into strata for better representation

Population divided into strata (mutually exclusive groups).
Random samples are drawn proportionally from each stratum.
Guarantees representation of subgroups and greater precision.

Question 4

What is cluster sampling?

Answer 4

Uses clusters (i.e. geographic regions)

Population divided into clusters (e.g., geographic regions).
Entire clusters are randomly selected.
Less precision but cost-effective.

Question 5

What are the goals of sampling?

Answer 5

Normal distributions, large sample size, no biases, representative of the population

Question 6

Central limit theorem

Answer 6

For large samples, the sampling distribution of the sample mean approximates a normal distribution regardless of the population’s shape.

For large sample sizes (n ≥ 30):
The sampling distribution of the sample mean (X̄) is approximately normal.
True regardless of the population’s shape.
Mean of sample means = population mean (μ).

Question 7

Exponential distribution

Answer 7

Used for modeling time between events (e.g., emails).

Formula for cumulative probability: P(X ≤ x) = 1 - e^(-λx).