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# MTH120_Chapter9

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### MTH120_Chapter9

1. 1. 9- 1 Chapter Nine Estimation and Confidence IntervalsGOALSWhen you have completed this chapter, you will be able to:ONEDefine a what is meant by a point estimate.TWODefine the term level of level of confidence.THREEConstruct a confidence interval for the population mean whenthe population standard deviation is known.FOURConstruct a confidence interval for the population mean whenthe population standard deviation is unknown.
2. 2. 9- 2 Chapter Nine continued Estimation and Confidence IntervalsGOALSWhen you have completed this chapter, you will be able to:FIVEConstruct a confidence interval for the population proportion.SIXDetermine the sample size for attribute and variable sampling.
3. 3. 9- 3 Point and Interval Estimates• A point estimate is a single value (statistic) used to estimate a population value (parameter).A confidence interval is a range of valueswithin which the population parameter isexpected to occur.
4. 4. 9- 4Point Estimates and Interval Estimates• The factors that determine the width of a confidence interval are: 1. The sample size, n. 2. The variability in the population, usually estimated by s. 3. The desired level of confidence.
5. 5. 9- 5 Point and Interval Estimates• If the population standard deviation is known or the sample is greater than 30 we use the z distribution. s X ±z n
6. 6. 9- 6 Point and Interval Estimates• If the population standard deviation is unknown and the sample is less than 30 we use the t distribution. s X ±t n
7. 7. 9- 7 Interval Estimates• An Interval Estimate states the range within which a population parameter probably lies.The interval within which a population parameter isexpected to occur is called a confidence interval.The two confidence intervals that are used extensivelyare the 95% and the 99%.
8. 8. 9- 8 Interval Estimates• For a 95% confidence interval about 95% of the similarly constructed intervals will contain the parameter being estimated. Also 95% of the sample means for a specified sample size will lie within 1.96 standard deviations of the hypothesized population mean.For the 99% confidence interval, 99% of thesample means for a specified sample size will liewithin 2.58 standard deviations of thehypothesized population mean.
9. 9. 9- 9Standard Error of the Sample Means• The standard error of the sample mean is the standard deviation of the sampling distribution of the sample means.• It is computed by σ σx = n• σ is the symbol for the standard error of the x sample mean.• σ is the standard deviation of the population.• n is the size of the sample.
10. 10. 9- 10 Standard Error of the Sample Means• If I is not known and nn30, the standard deviation of the sample, designated s, is used to approximate the population standard deviation. The formula for the standard error is: s sx = n
11. 11. 95% and 99% Confidence Intervals for 9- 11 µ• The 95% and 99% confidence intervals for are constructed as follows when:• 95% CI for the population mean is given by s X ±1.96 n 99% CI for the population mean is given by s X ± 2.58 n
12. 12. 9- 12 Constructing General Confidence Intervals for µ• In general, a confidence interval for the mean is computed by: s X ±z n
13. 13. 9- 13 EXAMPLE 3 The Dean of the Business School wants to estimate the mean number of hours worked per week by students. A sample of 49 students showed a mean of 24 hours with a standard deviation of 4 hours. What is the population mean?The value of the population mean is not known.Our best estimate of this value is the sample meanof 24.0 hours. This value is called a point estimate.
14. 14. 9- 14 Example 3 continued Find the 95 percent confidence interval for the population mean. s 4 X ±1.96 = 24.00 ±1.96 n 49 = 24.00 ±1.12The confidence limits range from 22.88 to 25.12. About 95 percent of the similarly constructedintervals include the population parameter.
15. 15. 9- 15 Confidence Interval for a Population Proportion• The confidence interval for a population proportion is estimated by: p(1 − p) p± z n
16. 16. 9- 16 EXAMPLE 4• A sample of 500 executives who own their own home revealed 175 planned to sell their homes and retire to Arizona. Develop a 98% confidence interval for the proportion of executives that plan to sell and move to Arizona. (.35)(.65) .35 ±2.33 =.35 ±.0497 500
17. 17. 9- 17Finite-Population Correction Factor• A population that has a fixed upper bound is said to be finite.• For a finite population, where the total number of objects is N and the size of the sample is n, the following adjustment is made to the standard errors of the sample means and the proportion:• Standard error of the sample means: σ N −n σx = n N −1
18. 18. 9- 18Finite-Population Correction Factor Standard error of the sample proportions: p (1 − p ) N −n σp = n N −1This adjustment is called the finite-populationcorrection factor.If n/N < .05, the finite-population correction factoris ignored.
19. 19. 9- 19 EXAMPLE 5• Given the information in EXAMPLE 4, construct a 95% confidence interval for the mean number of hours worked per week by the students if there are only 500 students on campus.• Because n/N = 49/500 = .098 which is greater than 05, we use the finite population correction factor. 1.96( 4 )( 500 − 49 ) = 24.00 ± 1.0648 24 ± 49 500 − 1
20. 20. 9- 20 Selecting a Sample Size There are 3 factors that determine the size of a sample, none of which has any direct relationship to the size of the population. They are:• The degree of confidence selected.• The maximum allowable error.• The variation in the population.
21. 21. 9- 21 Variation in the Population• To find the sample size for a variable: 2  z •s  n =   E • where : E is the allowable error, z is the z- value corresponding to the selected level of confidence, and s is the sample deviation of the pilot survey.
22. 22. 9- 22 EXAMPLE 6A consumer group would like to estimate themean monthly electricity charge for a singlefamily house in July within \$5 using a 99 percentlevel of confidence. Based on similar studies thestandard deviation is estimated to be \$20.00.How large a sample is required? 2  (2.58)(20)  n=  = 107  5 
23. 23. 9- 23 Sample Size for Proportions• The formula for determining the sample size in the case of a proportion is: 2 Z  n = p(1 − p)  E • where p is the estimated proportion, based on past experience or a pilot survey; z is the z value associated with the degree of confidence selected; E is the maximum allowable error the researcher will tolerate.
24. 24. 9- 24 EXAMPLE 7• The American Kennel Club wanted to estimate the proportion of children that have a dog as a pet. If the club wanted the estimate to be within 3% of the population proportion, how many children would they need to contact? Assume a 95% level of confidence and that the club estimated that 30% of the children have a dog as a pet. 2  1.96  n = (.30)(.70)  = 897  .03 