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 1.3.12
Textbook Question
In Exercises 9–20, identify which of these types of sampling is used: random, systematic, convenience, stratified, or cluster.
Reported and Observed Results A Harris Interactive study involved 1013 adults who were interviewed about washing their hands in restrooms and another 6336 adults who were observed in public restrooms.

1
Understand the different types of sampling methods: random, systematic, convenience, stratified, and cluster.
Random sampling involves selecting individuals from a population in such a way that each individual has an equal chance of being chosen.
Systematic sampling involves selecting every nth individual from a list or sequence.
Convenience sampling involves selecting individuals who are easiest to reach or sample.
Stratified sampling involves dividing the population into subgroups (strata) and then taking a sample from each subgroup.

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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Types of Sampling
Sampling is a method used to select a subset of individuals from a population to estimate characteristics of the whole population. The main types include random sampling, where every individual has an equal chance of being selected; systematic sampling, which involves selecting every nth individual; convenience sampling, based on ease of access; stratified sampling, which divides the population into subgroups; and cluster sampling, where entire groups are randomly selected.
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Random Sampling
Random sampling is a technique where each member of the population has an equal probability of being chosen. This method helps to eliminate bias and ensures that the sample is representative of the population, which is crucial for the validity of statistical inferences. It is often achieved through methods like lottery or random number generators.
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Sampling Distribution of Sample Proportion
Observational Study
An observational study is a research method where the researcher observes and records behavior without manipulating any variables. In the context of the question, the study involved observing adults in public restrooms to gather data on handwashing habits. This type of study can provide valuable insights but does not establish cause-and-effect relationships.
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Visualizing Qualitative vs. Quantitative Data
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