Chapter 5 Wrap-Up
Concept Check
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Section Resources
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5.1 Point Estimation and Sampling Distributions
5.2 The Sampling Distribution of the Sample Mean (CLT)
5.3 Introduction to Confidence Intervals
5.4 The Behavior of Confidence Intervals
Key Terms
Try to define the terms below on your own. Check your response by scrolling over the term, or looking at the end-of-book glossary!
5.1 Point Estimation and Sampling Distributions
- Statistical inference
- Point estimate
- Parameter
- Statistic
- Sampling variability
- Sampling distribution
- Law of large numbers
- Standard error
5.2 The Sampling Distribution of the Sample Mean (CLT)
5.3 Introduction to Confidence Intervals
5.4 The Behavior of Confidence Intervals
5.5 Introduction to Hypothesis Tests
- Hypothesis test
- Null hypothesis (H0)
- Alternative hypothesis (HA)
- Test statistic
- p-value
- Significance level
- Statistically significant
5.6 Hypothesis Tests in Depth
Extra Practice
Extra practice problems are available at the end of the book (Chapter 5 Extra Practice).
Using information from a sample to answer a question, or generalize, about a population
The value that is calculated from a sample used to estimate an unknown population parameter
A number that is used to represent a population characteristic and can only be calculated as the result of a census
A number calculated from a sample
The idea that samples from the same population can yield different results
The probability distribution of a statistic at a given sample size
As the number of trials in a probability experiment increases, the relative frequency of an event approaches the theoretical probability
The standard deviation of a sampling distribution
If there is a population with mean μ and standard deviation σ, and you take sufficiently large random samples from the population, then the distribution of the sample means will be approximately normally distributed.
The facet of statistics dealing with using a sample to generalize (or infer) about the population
An interval built around a point estimate for an unknown population parameter
Roughly 68% of values are within one standard deviation of the mean, roughly 95% of values are within two standard deviations of the mean, and 99.7% of values are within three standard deviations of the mean
How much a point estimate can be expected to differ from the true population value; made up of the standard error multiplied by the critical value
Point on a distribution that acts as a cut-off value for accepting or rejecting the null hypothesis
A decision-making procedure for determining whether sample evidence supports a hypothesis
The claim that is assumed to be true and is tested in a hypothesis test
A working hypothesis that is contradictory to the null hypothesis
A measure of the difference between observations and the hypothesized (or claimed) value
The probability that an event will occur, assuming the null hypothesis is true
Probability that a true null hypothesis will be rejected, also known as type I error and denoted by α
Finding sufficient evidence that the observed effect is not just due to variability, often from rejecting the null hypothesis
The decision is to reject the null hypothesis when, in fact, the null hypothesis is true
Erroneously rejecting a true null hypothesis or erroneously failing to reject a false null hypothesis
The probability of failing to reject a true hypothesis
