Chapter 7: Confidence Interval for One Population Mean
We will focus on inferential statistics hereafter. Inferential statistics includes estimation and hypothesis testing: estimation is to estimate the value of a population parameter; hypothesis testing is to test the plausibility of a statement about the value of a population parameter. Estimation consists of point estimates and confidence interval estimates. This chapter introduces how to obtain a point estimate and a confidence interval for the population mean [latex]\mu[/latex].
As a result of completing this chapter, you will be able to do the following:
- Explain the difference between an estimator, a point estimate, and a parameter.
- Explain the practical importance of confidence intervals.
- Distinguish between the standard normal distribution and the t distribution.
- Construct a [latex](1-\alpha) \times 100\%[/latex] z and t confidence interval.
- Interpret a confidence interval.
- Explain the relationship between confidence level, precision, length of the interval, and margin of error.
- Calculate the required sample size given the margin of error and confidence level.
