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Download Chap. 8: Estimation of Population Parameters: Confidence Intervals
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Statistics for Business and Economics Estimation of Population Parameters: Confidence Intervals Chapter 8 Learning Objectives 1. State What Is Estimated 2. Distinguish Point & Interval Estimates 3. Explain Interval Estimates 4. Compute Confidence Interval Estimates for Population Mean & Proportion 5. Compute Sample Size Thinking Challenge Suppose you’re interested in the average amount of money that students in this class (the population) have on them. How would you find out? Statistical Methods Statistical Methods Descriptive Statistics Inferential Statistics Estimation Hypothesis Testing Estimation Process Population Mean, mX, is unknown Random Sample Mean `X = 50 I am 95% confident that mX is between 40 & 60. Unknown Population Parameters Are Estimated Estimate Population Parameter... Mean mx Proportion Variance Differences p with Sample Statistic `x ps 2 2 sx s m1 - m2 `x1 -`x2 Estimation Methods Estimation Point Estimation Confidence Interval Interval Estimation Bootstrapping Prediction Interval Point Estimation 1. Provides Single Value Based on Observations from 1 Sample 2. Gives No Information about How Close Value Is to the Unknown Population Parameter 3. Sample Mean`X = 3 Is Point Estimate of Unknown Population Mean Estimation Methods Estimation Point Estimation Confidence Interval Interval Estimation Bootstrapping Prediction Interval Interval Estimation 1. Provides Range of Values 2. Gives Information about Closeness to Unknown Population Parameter Based on Observations from 1 Sample Stated in terms of Probability Knowing Exact Closeness Requires Knowing Unknown Population Parameter 3. e.g., Unknown Population Mean Lies Between 50 & 70 with 95% Confidence Key Elements of Interval Estimation A Probability That the Population Parameter Falls Somewhere Within the Interval. Confidence Interval Confidence Limit (Lower) Sample Statistic (Point Estimate) Confidence Limit (Upper) Confidence Limits for Population Mean Parameter = Statistic ± Error © 1984-1994 T/Maker Co. (1) m x X Error (2) Error X - m x or X m x X - mx (3) Z (4) Error Zs x (5) m x X Zs x sx Error sx Many Samples Have Same Confidence Interval `X = mx ± Zs`x sx_ mx-2.58s`x mx-1.65s`x mx-1.96s`x mx mx+1.65s`x 90% Samples 95% Samples 99% Samples `X mx+2.58s`x mx+1.96s`x Level of Confidence 1. Probability that the Unknown Population Parameter Falls Within Interval 2. Denoted (1 - a) % a Is Probability That Parameter Is Not Within Interval 3. Typical Values Are 99%, 95%, 90% Intervals & Level of Confidence Sampling Distribution of Mean _ a/2 sx 1-a a/2 m`x = mx _ X (1 - a) % of Intervals Contain mX . Intervals Extend from `X - Zs`X to `X + Zs`X a % Do Not. Large Number of Intervals Factors Affecting Interval Width 1. Data Dispersion 2. Sample Size Measured by sX Intervals Extend from `X - Zs`X to`X + Zs`X s`X = sX / n 3. Level of Confidence (1 - a) Affects Z © 1984-1994 T/Maker Co. Confidence Interval Estimates Confidence Intervals Mean sx Known Proportion sx Unknown Variance Finite Population Confidence Interval Estimate Mean (sX Known) 1. Assumptions Population Standard Deviation Is Known Population Is Normally Distributed If Not Normal, Can Be Approximated by Normal Distribution (n 30) 2. Confidence Interval Estimate sX sX X - Za / 2 m X X Za / 2 n n Estimation Example Mean (sX Known) mean of a random sample of n = 25 is`X = 50. Set up a 95% confidence interval estimate for mX if sX = 10. sX sX X - Za / 2 m X X Za / 2 n n 10 10 50 - 196 . . m X 50 196 25 25 46.08 m X 53.92 The Thinking Challenge You’re a Q/C inspector for Gallo. The sX for 2-liter bottles is .05 liters. A random sample of 100 bottles showed`X = 1.99 liters. What is the 90% confidence interval estimate of the true mean amount in 2-liter bottles? 2 liter © 1984-1994 T/Maker Co. Confidence Interval Solution* X - Za / 2 199 . - 1645 . sX n .05 100 m X X Za / 2 sX n . 1645 . m X 199 1982 . . m X 1998 .05 100 Confidence Interval Estimates Confidence Intervals Mean sx Known Proportion sx Unknown Variance Finite Population Confidence Interval Estimate Mean (sX Unknown) 1. Assumptions Population Standard Deviation Is Unknown Population Must Be Normally Distributed 2. Use Student’s t Distribution 3. Confidence Interval Estimate X - t a / 2, n -1 S n m X X t a / 2, n -1 S n Student’s t Distribution Standard Normal Bell-Shaped t (df = 13) Symmetric t (df = 5) ‘Fatter’ Tails 0 Z t Student’s t Table Upper Tail Area df .25 .10 .05 a/2 Assume: n=3 df = n - 1 = 2 a = .10 a/2 =.05 1 1.000 3.078 6.314 2 0.817 1.886 2.920 .05 3 0.765 1.638 2.353 t Values 0 2.920 t Degrees of Freedom (df) 1. Number of Observations that Are Free to Vary After Sample Statistic Has Been Calculated degrees of freedom 2. Example Sum of 3 Numbers Is 6 X1 = 1 (or Any Number) X2 = 2 (or Any Number) X3 = 3 (Cannot Vary) Sum = 6 = n -1 = 3 -1 =2 Estimation Example Mean (sX Unknown) random sample of n = 25 has`X = 50 & S = 8. Set up a 95% confidence interval estimate for mX. S S X - t a / 2, n -1 m X X t a / 2, n -1 n n 8 8 50 - 2.0639 m X 50 2.0639 25 25 46.69 m X 53.30 A Thinking Challenge You’re a time study analyst in manufacturing. You’ve recorded the following task times (min.): 3.6, 4.2, 4.0, 3.5, 3.8, 3.1. What is the 90% confidence interval estimate of the population mean task time? Confidence Interval Solution* `X = 3.7 S = 3.8987 n = 6, df = n -1 = 6 -1 = 5 S / n = 3.8987 / 6 = 1.592 t.05,5 = 2.0150 3.7 - (2.015)(1.592) mX 3.7 + (2.015)(1.592) .492 mX 6.908 Confidence Interval Estimates Confidence Intervals Mean sx Known Proportion sx Unknown Variance Finite Population Estimation for Finite Populations 1. Assumptions Sample Is Large Relative to Population n / N > .05 2. Use Finite Population Correction Factor 3. Confidence Interval (Mean, sX Unknown) X - t a / 2, n -1 S n N-n N -1 m X X t a / 2, n -1 S n N-n N -1 Confidence Interval Estimates Confidence Intervals Mean sx Known Proportion sx Unknown Variance Finite Population Confidence Interval Estimate Proportion 1. Assumptions Two Categorical Outcomes Population Follows Binomial Distribution Normal Approximation Can Be Used n·p 5 & n·(1 - p) 5 2. Confidence Interval Estimate ps - Z ps (1 - ps ) n p ps Z ps (1 - ps ) n Estimation Example Proportion A random sample of 400 graduates showed 32 went to grad school. Set up a 95% confidence interval estimate for p. ps - Z a / 2 .08 - 196 . ps (1 - ps ) n .08 (1-.08 ) 400 p ps Z a / 2 . p .08 196 .053 p .107 ps (1 - ps ) n .08 (1-.08 ) 400 Thinking Challenge You’re a production manager for a newspaper. You want to find the % defective. Of 200 newspapers, 35 had defects. What is the 90% confidence interval estimate of the population proportion defective? Confidence Interval Solution* n·p 5 n·(1 - p) 5 ps (1 - ps ) ps (1 - ps ) ps - Z a / 2 p ps Z a / 2 n n .175 (.825) .175 (.825) .175 - 1645 . . p .175 1645 200 200 .1308 p .2192 Estimation Methods Estimation Point Estimation Confidence Interval Interval Estimation Bootstrapping Prediction Interval Bootstrapping Method 1. Used If Population Is Not Normal 2. Requires Computer 3. Steps Take Initial Sample Sample Repeatedly from Initial Sample Compute Sample Statistic Form Resampling Distribution Limits Are Values That Cut Off Smallest & Largest a/2 % Estimation Methods Estimation Point Estimation Confidence Interval Interval Estimation Bootstrapping Prediction Interval Prediction Interval 1. Used to Estimate Future Individual X Value 2. Not Used to Estimate Unknown Population Parameter 3. Prediction Interval Estimate X - t a / 2, n -1 S 1 1 n X f X t a / 2, n -1 S 1 1 n Finding Sample Sizes (1) (2) (3) Z X - mx sx Error sx Error Zs x Z n 2 Z sx 2 Error 2 sx n I don’t want to sample too much or too little! Sample Size Example What sample size is needed to be 90% confident of being correct within 5? A pilot study suggested that the standard deviation is 45. n 2 Z sx 2 Error 2 1645 . 45) ( )( 219.2 @ 220 (5) 2 2 2 Thinking Challenge You work in Human Resources at Merrill Lynch. You plan to survey employees to find their average medical expenses. You want to be 95% confident that the sample mean is within ± $50. A pilot study showed that sX was about $400. What sample size do you use? Sample Size Solution* Z sx 2 n 2 Error 2 196 . ) (400 ) ( (50) 2 2 2 245.86 @ 246 Conclusion 1. Stated What Is Estimated 2. Distinguished Point & Interval Estimates 3. Explained Interval Estimates 4. Computed Confidence Interval Estimates for Population Mean & Proportion 5. Computed Sample Size End of Chapter Any blank slides that follow are blank intentionally.