Table of contents
- 1. Intro to Stats and Collecting Data55m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically1h 45m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables2h 33m
- 6. Normal Distribution and Continuous Random Variables1h 38m
- 7. Sampling Distributions & Confidence Intervals: Mean1h 3m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 12m
- 9. Hypothesis Testing for One Sample1h 1m
- 10. Hypothesis Testing for Two Samples2h 8m
- 11. Correlation48m
- 12. Regression1h 4m
- 13. Chi-Square Tests & Goodness of Fit1h 20m
- 14. ANOVA1h 0m
1. Intro to Stats and Collecting Data
Intro to Stats
Problem 1.RE.7e
Textbook Question
State Populations Currently, California has the largest population with 39,776,830 residents, and Wyoming has the smallest population with 573,520 residents.
e. If we randomly select two states and survey all of their adult residents, what type of sample is obtained? (random, systematic, convenience, stratified, cluster)

1
Understand the different types of sampling methods: Random sampling involves selecting individuals purely by chance, systematic sampling involves selecting every nth individual, convenience sampling involves selecting individuals who are easiest to reach, stratified sampling involves dividing the population into subgroups and sampling from each, and cluster sampling involves dividing the population into clusters and randomly selecting entire clusters.
Identify the key characteristics of the problem: The problem involves selecting two states and surveying all of their adult residents.
Consider the definition of cluster sampling: In cluster sampling, the population is divided into clusters (in this case, states), and entire clusters are selected randomly. All individuals within the selected clusters are then surveyed.
Analyze the problem in the context of cluster sampling: Since the problem involves selecting entire states (clusters) and surveying all adult residents within those states, it aligns with the definition of cluster sampling.
Conclude that the type of sample obtained is a cluster sample, as the selection process involves choosing entire clusters (states) and surveying all individuals within those clusters.

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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Sampling Methods
Sampling methods are techniques used to select a subset of individuals from a population to estimate characteristics of the whole population. Common methods include random, systematic, convenience, stratified, and cluster sampling, each with unique procedures and applications. Understanding these methods helps in choosing the appropriate technique for data collection based on the research objective.
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Cluster Sampling
Cluster sampling involves dividing the population into distinct groups, or clusters, and then randomly selecting entire clusters for study. This method is efficient when dealing with large, geographically dispersed populations, as it reduces travel and administrative costs. In the context of the question, selecting two states and surveying all their residents exemplifies cluster sampling.
Recommended video:
Sampling Distribution of Sample Proportion
Stratified Sampling
Stratified sampling involves dividing the population into homogeneous subgroups, or strata, and then randomly sampling from each stratum. This ensures representation across key characteristics, improving the accuracy and reliability of results. Unlike cluster sampling, stratified sampling requires sampling from each subgroup, not entire groups, making it distinct in its approach to achieving representativeness.
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Sampling Distribution of Sample Proportion
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