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 1.3.8c
Textbook Question
Sampling Method Assume that the population consists of all students currently in your statistics class. Describe how to obtain a sample of six students so that the result is a sample of the given type.
c. Stratified sample

1
Identify the strata within the population. In this case, you might divide the students into different groups based on characteristics such as year of study, major, or performance level.
Ensure that each stratum is mutually exclusive and collectively exhaustive, meaning every student belongs to one and only one stratum, and all students are included in the strata.
Determine the number of students to sample from each stratum. This can be proportional to the size of the stratum or equal across strata, depending on the research goals.
Randomly select students from each stratum. Use a random sampling method such as drawing names from a hat or using a random number generator to ensure each student has an equal chance of being selected within their stratum.
Combine the selected students from each stratum to form the final sample of six students, ensuring that the sample reflects the diversity of the population as represented by the strata.

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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Stratified Sampling
Stratified sampling is a method of sampling that involves dividing a population into smaller groups, known as strata, that share similar characteristics. A random sample is then taken from each stratum. This technique ensures that each subgroup is adequately represented in the sample, improving the accuracy and representativeness of the results.
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Sampling Distribution of Sample Proportion
Population and Sample
In statistics, the population refers to the entire group that you want to draw conclusions about, while a sample is a subset of the population that is used to represent the whole. Sampling is crucial because it allows researchers to gather insights without needing to study the entire population, which is often impractical or impossible.
Recommended video:
Sampling Distribution of Sample Proportion
Random Sampling
Random sampling is a technique where each member of the population has an equal chance of being selected. This method helps to eliminate bias in the selection process, ensuring that the sample is representative of the population. In stratified sampling, random sampling is applied within each stratum to maintain the randomness and representativeness of the sample.
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Sampling Distribution of Sample Proportion
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