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  1. What is a standard error and what is a margin of error?

  2. What is the difference between point and interval estimation?

  3. Understand the “anatomy” of a confidence interval (i.e., point estimate, standard score, standard error, and margin of error). Be able to identify each part of a confidence interval.

  4. Be able to find/compute the point estimate, standard error, margin of error, and confidence interval when estimating \(p\).

  5. Be able to find/compute the point estimate, standard error, margin of error, and confidence interval when estimating \(\mu\) (also know how to do this when sampling without replacement when \(N\) is known).

  6. Be able to find/compute the point estimate, standard error, margin of error, and confidence interval when estimating \(\tau\) when sampling without replacement.

  7. What is meant by the confidence level of a confidence interval? How do you find the value of \(z\) or \(t\) for a specified confidence level?

  8. What effect does increasing the confidence level have on the margin of error and the confidence interval? What effect does increasing the sample size have on the margin of error and the confidence interval?

  9. How do you choose the sample size when estimating \(p\) with \(\hat{p}\)?

  10. How do you choose the sample size when estimating \(\mu\) with \(\bar{x}\)?

  11. What is sampling with versus without replacement?

  12. What do we need to assume when making inferences about \(\mu\), \(p\), and \(\tau\) using the methods we have discussed?

  13. What is meant by saying that a statistic is unbiased? What does it mean to say that a statistic is biased?

  14. What are the three sources of bias that we discussed in class?

  15. When is the sampling distribution of \(\bar{x}\) or \(\hat{p}\) approximately normal in shape?

  16. What is the randomized response method? How does it work? Why is it used?

  17. As always, be comfortable with symbols/notation (e.g., \(\mu\), \(\bar{x}\), \(p\), \(\hat{p}\), \(m\), \(n\), \(N\), \(s\), \(\sigma\), \(\tau\)).

Formulas/expressions you should understand when and how to use. \[ \sqrt{\hat{p}(1-\hat{p})/n} \ \ \ \ \ z\sqrt{\hat{p}(1-\hat{p})/n} \ \ \ \ \ \hat{p} \pm z\sqrt{\hat{p}(1-\hat{p})/n} \] \[ \frac{s}{\sqrt{n}}\ \ \ \ \ \ t\frac{s}{\sqrt{n}} \ \ \ \ \ \bar{x} \pm t\frac{s}{\sqrt{n}} \] \[ \frac{s}{\sqrt{n}}\sqrt{1 - \frac{n}{N}} \ \ \ \ \ t\frac{s}{\sqrt{n}}\sqrt{1 - \frac{n}{N}} \ \ \ \ \ \bar{x} \pm t\frac{s}{\sqrt{n}}\sqrt{1 - \frac{n}{N}} \] \[ N\frac{s}{\sqrt{n}}\sqrt{1 - \frac{n}{N}} \ \ \ \ \ tN\frac{s}{\sqrt{n}}\sqrt{1 - \frac{n}{N}} \ \ \ \ \ N\bar{x} \pm tN\frac{s}{\sqrt{n}}\sqrt{1 - \frac{n}{N}} \] \[ n = \frac{z^2p(1-p)}{m^2} \ \ \ \ \ n = \frac{z^2\sigma^2}{m^2} \] \[ n - 1 \ \ \ \ \ n\hat{p} \ge 15 \ \ \ \ \ n(1-\hat{p}) \ge 15 \]