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Unformatted text preview: Click to edit Master subtitle style Professor Thomas R. Sexton Professor Thomas R. Sexton 11 Confidence Intervals Professor Thomas R. Sexton College of Business Stony Brook University Professor Thomas R. Sexton Professor Thomas R. Sexton 22 Our First Estimation Problem n What proportion of Stony Brook students smoke? n Very large population ( N 23,000). n Sample size = n = 100 students n X = 20 students smoke Professor Thomas R. Sexton Professor Thomas R. Sexton 33 Constructing an Interval Estimate n What we want is an interval of the form: n This is an interval that has a predetermined probability of capturing , the unknown population parameter. n How should we compute the endpoints? Professor Thomas R. Sexton Professor Thomas R. Sexton 44 Solve for Professor Thomas R. Sexton Professor Thomas R. Sexton 55 Confidence Interval for Professor Thomas R. Sexton Professor Thomas R. Sexton 66 What Proportion of Stony Brook Students Smoke? Professor Thomas R. Sexton Professor Thomas R. Sexton 77 Margin of Error (Sampling Error) n In any confidence interval, the part after the is called the margin of error or the sampling error . n Together with the confidence level, the margin of error tells us how precisely we have estimated the parameter. n In this example, we say that we have a margin of error of 0.0784 (or 7.84 percentage points) with 95% confidence. Professor Thomas R. Sexton Professor Thomas R. Sexton 88 Changing the Confidence Level Professor Thomas R. Sexton Professor Thomas R. Sexton 99 Finite Populations: Confidence Intervals n When our sample size, n , is more than 5% of the population, N , and we are sampling without replacement, then we need to apply the Finite Population Correction Factor (FPCF) when computing confidence intervals. Professor Thomas R. Sexton Professor Thomas R. Sexton 1010 Confidence Interval for with FPCF Professor Thomas R. Sexton Professor Thomas R. Sexton 1111 What Proportion of Business Management Majors Smoke? Professor Thomas R. Sexton Professor Thomas R. Sexton 1212 Our Other Estimation Problem n How satisfied are your customers? n Very large population ( N = 10,000) n Random sample of n = 100 customers n You compute the mean and SD of the n = 100 customer satisfaction scores (on a scale of 0 100): Professor Thomas R. Sexton Professor Thomas R. Sexton 1313 Constructing an Interval Estimate n What we want is an interval of the form: n This is an interval that has a predetermined probability of capturing , the unknown population parameter. n How should we compute the endpoints? Professor Thomas R....
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 Fall '09
 ThomasSexton
 Business

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