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In Exercises 1–3, refer to the accompanying screen display that results from the Verizon airport data speeds (Mbps) from Data Set 32 “Airport Data Speeds” in Appendix B. The confidence level of 95% was used.

Degrees of Freedom

a. What is the number of degrees of freedom that should be used for finding the critical value tα2?

b. Find the critical value tα2corresponding to a 95% confidence level.

c. Give a brief general description of the number of degrees of freedom.

Short Answer

Expert verified

a. The value of the degrees of freedom is equal to 49.

b. The critical value is equal to 2.0096.

c. The number of observations in the sample that can assume any value independently of other values stands for the number of degrees of freedom. Here, out of 50 values, 49 of them are independent values, while the last observation (50th) is dependent on the values of the other 49 observations.

Step by step solution

01

Given Information

A sample of Verizon airport data speeds is considered.

02

Value of the degrees of freedom

The formula for computing the degrees of freedom is written below:

df=n-1

Here, n is the sample size and has a value equal to 50.

Substitute the value of n as follows:

df=50-1=49

Thus, the value of the degrees of freedom is equal to 49.

03

Critical value 

b.

The confidence level is equal to 95%. Thus, the corresponding level of significance is equal to 0.05.

Referring to the t-distribution table, the value of tα2for 49 degrees of freedom when αis equal to 0.05 is equal to 2.0096.

04

Meaning of the value of the degrees of freedom

c.

For a sample containing values, the number of independent values refers to the value of the degrees of freedom.

Here, out of 50 observations, 49 values can have any value that is assumed independently of other values. Based on the 49 observations, the 50th observation can be calculated, and it is dependent on the value of the 49 observations.

Thus, the value of the degrees of freedom is equal to 49.

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Most popular questions from this chapter

Constructing and Interpreting Confidence Intervals. In Exercises 13–16, use the given sample data and confidence level. In each case, (a) find the best point estimate of the population proportion p; (b) identify the value of the margin of error E; (c) construct the confidence interval; (d) write a statement that correctly interprets the confidence interval.

Survey Return Rate In a study of cell phone use and brain hemispheric dominance, an Internet survey was e-mailed to 5000 subjects randomly selected from an online group involved with ears. 717 surveys were returned. Construct a 90% confidence interval for the proportion of returned surveys.

Cell Phone Radiation Here is a sample of measured radiation emissions (cW/kg) for cell phones (based on data from the Environmental Working Group): 38, 55, 86, 145. Here are ten bootstrap samples: {38, 145, 55, 86}, {86, 38, 145, 145}, {145, 86, 55, 55}, {55, 55, 55, 145}, {86, 86, 55, 55}, {38, 38, 86, 86}, {145, 38, 86, 55}, {55, 86, 86, 86}, {145, 86, 55, 86}, {38, 145, 86, 556}.

a. Using only the ten given bootstrap samples, construct an 80% confidence interval estimate of the population mean.

b. Using only the ten given bootstrap samples, construct an 80% confidence interval estimate of the population standard deviation.

Finding Critical Values. In Exercises 5–8, find the critical value that corresponds to the given confidence level.

99.5%

Formats of Confidence Intervals. In Exercises 9–12, express the confidence interval using the indicated format. (The confidence intervals are based on the proportions of red, orange, yellow, and blue M&Ms in Data Set 27 “M&M Weights” in Appendix B.)

Blue M&Ms Express the confidence interval 0.270±0.073 in the form ofp^-E<p<p^+E

Finite Population Correction Factor For Formulas 7-2 and 7-3 we assume that the population is infinite or very large and that we are sampling with replacement. When we sample without replacement from a relatively small population with size N, we modify E to include the finite population correction factor shown here, and we can solve for n to obtain the result given here. Use this result to repeat part (b) of Exercise 38, assuming that we limit our population to a county with 2500 women who have completed the time during which they can give birth.

E=zα2p^q^nN-nN-1

n=Np^q^zα22p^q^zα22+N-1E2

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