1. © The McGraw-Hill Companies, Inc., 2000 6-1 Chapter 6 Estimates and Sample Size with One Sample

2. © The McGraw-Hill Companies, Inc., 2000 6-2 Outline 6-1 Introduction 6-3 Estimating a Population Mean with:  known  6-4 Estimating a Population Mean with:  unknown 

3. © The McGraw-Hill Companies, Inc., 2000 6-4 Objectives Find the confidence interval for the mean when  is known or n  30. Determine the minimum sample size for finding a confidence interval for the mean. Find the confidence interval for the mean when  is unknown and n  30.

4. © The McGraw-Hill Companies, Inc., 2000 6-6 6-3 Confidence Intervals for the Mean (  known or n  30) and Sample Size X A point estimate is a specific numerical value estimate of a parameter. The best estimate of the population mean is the sample mean. 

5. © The McGraw-Hill Companies, Inc., 2000 6-7 unbiased estimator The estimator must be an unbiased estimator. That is, the expected value or the mean of the estimates obtained from samples of a given size is equal to the parameter being estimated. 6-3 Three Properties of a Good Estimator

6. © The McGraw-Hill Companies, Inc., 2000 6-8 consistent estimator The estimator must be consistent. For a consistent estimator, as sample size increases, the value of the estimator approaches the value of the parameter estimated. 6-3 Three Properties of a Good Estimator

7. © The McGraw-Hill Companies, Inc., 2000 6-9 relatively efficient estimator The estimator must be a relatively efficient estimator. That is, of all the statistics that can be used to estimate a parameter, the relatively efficient estimator has the smallest variance. 6-3 Three Properties of a Good Estimator

8. © The McGraw-Hill Companies, Inc., 2000 6-10 6-3 Confidence Intervals interval estimate An interval estimate of a parameter is an interval or a range of values used to estimate the parameter. This estimate may or may not contain the value of the parameter being estimated.

9. © The McGraw-Hill Companies, Inc., 2000 6-11 6-3 Confidence Intervals confidence interval A confidence interval is a specific interval estimate of a parameter determined by using data obtained from a sample and the specific confidence level of the estimate.

10. © The McGraw-Hill Companies, Inc., 2000 6-12 6-3 Confidence Intervals confidence level The confidence level of an interval estimate of a parameter is the probability that the interval estimate will contain the parameter.

11. © The McGraw-Hill Companies, Inc., 2000 6-13 confidence level The confidence level is the percentage equivalent to the decimal value of 1 – . 6-3 Formula for the Confidence Interval of the Mean for a Specific 

12. © The McGraw-Hill Companies, Inc., 2000 6-14 6-3 Maximum Error of Estimate or Margin of Error (E) maximum error of estimate The maximum error of estimate or margin of error (E) margin of error (E) is the maximum difference between the point estimate of a parameter and the actual value of the parameter.

13. © The McGraw-Hill Companies, Inc., 2000 6-15 The president of a large university wishes to estimate the average age of the students presently enrolled. From past studies, the standard deviation is known to be 2 years. A sample of 50 students is selected, and the mean is found to be 23.2 years. Find the 95% confidence interval of the population mean. 6-3 Confidence Intervals - 6-3 Confidence Intervals - Example

14. © The McGraw-Hill Companies, Inc., 2000 6-16 Sincetheconfidence isdesiredzHence substitutingintheformula Xz n Xz n onegets,, –+ 2 95% 196 22 interval                   .. 6-3 Confidence Intervals - 6-3 Confidence Intervals - Example

15. © The McGraw-Hill Companies, Inc., 2000 6-17 232 2  50 23.2 2 23206 206 226238 95% 226238 50.(1.96)() ()...... or 23.2 0.6 years.,,,..,.           Hencethepresidentcansaywith confidencethattheaverageage ofthestudentsisbetweenand yearsbasedonstudents 6-3 Confidence Intervals - 6-3 Confidence Intervals - Example  50

16. © The McGraw-Hill Companies, Inc., 2000 6-18 A certain medication is known to increase the pulse rate of its users. The standard deviation of the pulse rate is known to be 5 beats per minute. A sample of 30 users had an average pulse rate of 104 beats per minute. Find the 99% confidence interval of the true mean. 6-3 Confidence Intervals - 6-3 Confidence Intervals - Example

17. © The McGraw-Hill Companies, Inc., 2000 6-19 Sincetheconfidence isdesiredzHence substitutingintheformula X z n Xz n onegets,, –+ 2 99% 258 2 interval                    .. 6-3 Confidence Intervals - 6-3 Confidence Intervals - Example

18. © The McGraw-Hill Companies, Inc., 2000 6-20 104(2.58) 5 30 104 (2.58) 5 30 10424 24 10161064 99% 1016106.4     .()().....,,,.    Henceonecansaywith confidence that the average pulse rateisbetweenand beats per minute, based on 30 users. 6-3 Confidence Intervals - 6-3 Confidence Intervals - Example

19. © The McGraw-Hill Companies, Inc., 2000 6-21 6-3 Formula for the Minimum Sample Size Needed for an Interval Estimate of the Population Mean

20. © The McGraw-Hill Companies, Inc., 2000 6-22 The college president asks the statistics teacher to estimate the average age of the students at their college. How large a sample is necessary? The statistics teacher decides the estimate should be accurate within 1 year and be 99% confident. From a previous study, the standard deviation of the ages is known to be 3 years. 6-3 Minimum Sample Size Needed for an Interval Estimate of the Population Mean -Example 6-3 Minimum Sample Size Needed for an Interval Estimate of the Population Mean - Example

21. © The McGraw-Hill Companies, Inc., 2000 6-23 Sinceor zandEsubstituting inn z E gives n =. ( –.), =., =, = (.)()     0011099 2581 2 3 1 59960 2 2 2 2               .. 6-3 Minimum Sample Size Needed for an Interval Estimate of the Population Mean -Example 6-3 Minimum Sample Size Needed for an Interval Estimate of the Population Mean - Example

22. © The McGraw-Hill Companies, Inc., 2000 6-24 6-4 Characteristics of the t-Distribution The t-distribution shares some characteristics of the normal distribution and differs from it in others. The t- distribution is similar to the standard normal distribution in the following ways: It is bell-shaped. It is symmetrical about the mean.

23. © The McGraw-Hill Companies, Inc., 2000 6-25 6-4 Characteristics of the t-Distribution The mean, median, and mode are equal to 0 and are located at the center of the distribution. The curve never touches the x axis. The t distribution differs from the standard normal distribution in the following ways:

24. © The McGraw-Hill Companies, Inc., 2000 6-26 6-4 Characteristics of the t-Distribution The variance is greater than 1. degrees of freedom The t distribution is actually a family of curves based on the concept of degrees of freedom, which is related to the sample size. As the sample size increases, the t distribution approaches the standard normal distribution.

25. © The McGraw-Hill Companies, Inc., 2000 6-27 6-4 Standard Normal Curve and the t Distribution

26. © The McGraw-Hill Companies, Inc., 2000 6-13 When n < 30 and  is unknown use t-distribution with degrees of freedom = n – 1. 6-4 Formula for the Confidence Interval of the Mean for a Specific 

27. © The McGraw-Hill Companies, Inc., 2000 6-28 Ten randomly selected automobiles were stopped, and the tread depth of the right front tires were measured. The mean was 0.32 inches, and the standard deviation was 0.08 inches. Find the 95% confidence interval of the mean depth. Assume that the variable is approximately normally distributed. 6-4 Confidence Interval for the Mean (  unknown and n < 30) - 6-4 Confidence Interval for the Mean (  unknown and n < 30) - Example

28. © The McGraw-Hill Companies, Inc., 2000 6-29 Since  is unknown and s must replace it, the t distribution must be used with  = 0.05. Hence, with 9 degrees of freedom, t  /2 = 2.262 (see Table F in text). From the next slide, we can be 95% confident that the population mean is between 0.26 and 0.38. 6-4 Confidence Interval for the Mean (  unknown and n < 30) - 6-4 Confidence Interval for the Mean (  unknown and n < 30) - Example

29. © The McGraw-Hill Companies, Inc., 2000 6-30 6-4 Confidence Interval for the Mean (  unknown and n < 30) - 6-4 Confidence Interval for the Mean (  unknown and n < 30) - Example Thustheconfidence ofthepopulationmeanisfoundby substituting in Xt s Xt s nn 0.32–(2.262) 0.08  10 (2.262) 0.08  10 95% 032 026038 22 interval                                ... nn