About This Chapter
TECEP Principles of Statistics: Population, Samples & Probability - Chapter Summary
This study guide resource helps you solve statistics problems related to probability, population and samples in preparation for the TECEP Principles of Statistics exam. These video lessons and quizzes help you practice the following skills:
- Defining random sampling
- Understanding stratified random samples
- Determining sample size
- Finding the mean and standard error of a sampling distribution
- Identifying types of probability sampling methods
- Making sense of sampling distributions and the central limit theorem
- Using the central limit theorem to find probabilities about means
- Explaining the law of large numbers
These lessons efficiently break down the definitions, methods and theorems related to population, samples and probability topics. You can take the self-assessment quizzes to help you practice the concepts you've learned and strengthen your abilities to answer population, samples and probability problems on the test itself.
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1. What is Random Sampling? - Definition, Conditions & Measures
Random sampling is used in many research scenarios. In this lesson, you will learn how to use random sampling and find out the benefits and risks of using random samples.
2. Stratified Random Samples: Definition, Characteristics & Examples
Random sampling isn't always simple! There are many different types of sampling. In this lesson, you will learn how to use stratified random sampling and when it is most appropriate to use it.
3. How to Determine Sample Size
How many subjects should a researcher use in his or her experiment? In this lesson, we'll examine the elements that go into sample size, including how to figure out how big a sample should be and what real-world issues influence sample size.
4. Find the Mean & Standard Error of the Sampling Distribution
Have you ever had a situation where one grade destroyed your average? Wouldn't you like a way of proving that your work was actually pretty good with that one exception? The standard error gives you such a chance.
5. Probability Sampling Methods: Definition & Types
Choosing a sample is one of the most important steps in research. But how should you choose? In this lesson, we'll look at three types of probability sampling: simple random, systematic, and stratified sampling.
6. Sampling Distributions & the Central Limit Theorem: Definition, Formula & Examples
Want proof that all of this normal distribution talk actually makes sense? Then you've come to the right place. In this lesson, we look at sampling distributions and the idea of the central limit theorem, a basic component of statistics.
7. Finding Probabilities About Means Using the Central Limit Theorem
The central limit theorem provides us with a very powerful approach for solving problems involving large amount of data. In this lesson, we'll explore how this is done as well as conditions that make this theorem valid.
8. Understanding the Law of Large Numbers
The law of large numbers is a concept that is often misunderstood in statistics. In this lesson, you will learn the real meaning of the law of large numbers and how it is employed.
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Other chapters within the TECEP Principles of Statistics: Study Guide & Test Prep course
- TECEP Principles of Statistics: Measurement
- TECEP Principles of Statistics: Summarizing Data
- TECEP Principles of Statistics: Central Tendency & Variability
- TECEP Principles of Statistics: Probability
- TECEP Principles of Statistics: Probability Distributions
- TECEP Principles of Statistics: Correlation
- TECEP Principles of Statistics: Regression
- TECEP Principles of Statistics: Hypothesis Testing & Estimation
- TECEP Principles of Statistics: t-Tests
- TECEP Principles of Statistics: ANOVA
- TECEP Principles of Statistics: Chi-Square Test
- TECEP Principles of Statistics Flashcards