Constructing and Interpreting Confidence Intervals

This video tutorial explains how to construct and interpret confidence intervals using the margin of error. It covers the concept of margin of error, properties of normal distribution, and the relationship between confidence level, margin of error, and confidence interval. The tutorial provides examples to illustrate the construction and interpretation of confidence intervals.

What does the margin of error represent in a statistical sample?

• The total number of samples taken

• The bias in the sample selection

• The accuracy of the sample statistic

• The exact value of the population parameter

Which of the following is true about a normal distribution?

• It is a skewed curve with no mean

• It is a flat line with no variation

• Approximately 68% of data falls within one standard deviation of the mean

• It has no standard deviation

How is a confidence level of 95% interpreted?

• 95% of the time, the sample mean equals the population mean

• 95% of all samples will capture the true population parameter

• The interval will always contain the population parameter

• The sample size is 95% of the population

What happens to the confidence interval if the margin of error increases?

• The confidence interval becomes narrower

• The confidence interval remains the same

• The confidence interval becomes wider

• The confidence interval becomes invalid

In the basketball fan example, what is the confidence interval for the average hours watched?

• 67 to 83 hours

• 70 to 80 hours

• 75 to 85 hours

• 60 to 90 hours

What is the correct interpretation of a confidence interval?

• It shows the bias in the sample

• It indicates the number of samples taken

• It gives a range of plausible values for the population parameter

• It provides the exact value of the population parameter

In the high school graduate example, what is the confidence interval for the proportion of people sending gifts?

• 55% to 75%

• 60% to 65%

• 58% to 66%

• 50% to 70%