7. Sampling Distributions & Confidence Intervals: Mean

If the confidence level is increased from $90\%$ to $99\%$, what happens to the width of the confidence interval for a population mean, assuming all other factors remain constant?

Suppose you have a data table showing the relationship between hours studied and exam scores. After calculating the regression line, how would you use a regression calculator to make a reasonable prediction for a student who studied $5$ hours?

In the context of probability and statistics, the cumulative distribution function is denoted and defined as which of the following?

Which of the following statements is the best definition of a point estimate?

Which distribution should be used to construct a confidence interval for the mean when the sample size is small and the degrees of freedom are $df=5$?

Which of the following accurately describes the critical region in hypothesis testing?

Which of the following is true of the Central Limit Theorem?

Which of the following is a primary benefit of having a large sample size when constructing confidence intervals?

In the context of hypothesis testing, what does the $\mathrm{level of significance}$ represent?

Which of the following best describes the meaning of a $99\%$ confidence interval for a population mean?

In the context of confidence intervals, what does the margin of error account for?

Which concept below is not a main idea of estimating a population proportion?

Which of the following best describes the interpretation of a $96\%$ confidence level in the context of confidence intervals?

Which of the following best describes the main disadvantage of the moving average when used to estimate a population parameter in the context of confidence intervals?

In the context of confidence intervals, if Figure 7-7 shows 'line a' representing the range within which a population parameter is expected to fall with a certain level of confidence, what type of statistical forecasting does 'line a' most likely depict?