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 53m
8. Sampling Distributions & Confidence Intervals: Proportion1h 12m
- Sampling Distribution of Sample Proportion
  29m
- Confidence Intervals for Population Proportion
  42m
9. Hypothesis Testing for One Sample2h 19m
10. Hypothesis Testing for Two Samples3h 22m
11. Correlation1h 6m
12. Regression1h 4m
13. Chi-Square Tests & Goodness of Fit1h 20m
14. ANOVA1h 0m

1. Intro to Stats and Collecting Data

Intro to Stats

Statistics

1. Intro to Stats and Collecting Data

Intro to Stats

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2:19 minutes

Problem 1.3.2

Textbook Question

What is the difference between a census and a sampling?

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A census involves collecting data from every single member of a population. For example, if you want to know the income of all residents in a city, a census would require surveying every resident.

Sampling, on the other hand, involves selecting a subset of the population to collect data from. This subset, called a sample, is used to make inferences about the entire population.

The key difference is that a census gathers data from the entire population, while sampling gathers data from only a part of the population.

Censuses are typically more accurate because they include everyone, but they are also more time-consuming, expensive, and sometimes impractical for large populations.

Sampling is more efficient and cost-effective, but it requires careful design to ensure the sample is representative of the population to avoid bias in the results.

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Key Concepts

Here are the essential concepts you must grasp in order to answer the question correctly.

Census

A census is a comprehensive data collection method that aims to gather information from every individual or unit within a defined population. It is often used to obtain accurate demographic data, such as population size, age distribution, and other characteristics. While a census provides complete data, it can be time-consuming and costly, making it impractical for large populations.

Sampling

Sampling is the process of selecting a subset of individuals or units from a larger population to estimate characteristics of the whole population. This method is often used when a census is impractical due to time or cost constraints. Various sampling techniques, such as random sampling or stratified sampling, can be employed to ensure that the sample accurately represents the population.

Population vs. Sample

In statistics, the population refers to the entire group of individuals or items that are of interest, while a sample is a smaller group selected from that population. Understanding the distinction is crucial, as analyses and conclusions drawn from a sample can be generalized to the population only if the sample is representative. This concept underpins the validity of statistical inferences made from sampled data.

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Textbook Question

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Explain how you could design an experiment so that it uses a randomized block design.

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Textbook Question

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a. Temperature

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Textbook Question

200 students volunteer for an experiment to test the effects of sleep deprivation on memory recall. The students will be placed in one of five different treatment groups, including the control group.

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Textbook Question

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Identify the sampling technique used, and discuss potential sources of bias (if any). Explain.

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