Single Population Parameters Point and Confidence Interval Estimates for a Pop Mean Point Estimate ± (Critical Value)(Standard Error) Confidence interval for μ ( known) Steps: Define the population of interest and select a simple random sample of size n Specify the confidence level Compute the sample mean Determine the standard error of the sampling distribution using Determine the critical value‚ z‚ from the standard normal table. Look up confidence level in standard normal table to find
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revenue each day. 2a. Confidence interval is a range of values constructed from sample data so that the population parameter is likely to occur within that range at a specific probability (Lind‚ Marchal & Wathen‚ 2013). Using the 95% level of confidence‚ the confidence interval for Unicafe West is 220.42 6.211. The confidence interval limits are $214.21 and $226.63 (rounded off to 2 decimal places). Using the 95% level of confidence‚ the confidence interval for Unicafe North is 218.766
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Minimum 50000 34 Maximum 60000 55 Range 10000 21 confidence interval 95.% lower 54‚135.75 41.64 confidence interval 95.% upper 58‚717.16 50.18 half-width 2‚290.71 4.27 z 1.96 1.96 confidence interval 95.% lower 53‚822.32 41.05 confidence interval 95.% upper 59‚030.59 50.77 half-width 2‚604.13 4.86 t(df = 10) 2.228 2.228
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ACL Chapter 9 Problems Problem 1 In addition to determining sample size‚ ACL can also select a random sample for you. Draw a sample of Accounts Receivable (AR) transactions from the Roger Company AR table assuming the confidence is 95‚ the upper error limit is 9 percent‚ and the expected error rate is 5 percent. 1. Open the Roger_Company_AR table 2. Select Sampling >> Sample Records and the Sample window appears 3. Make sure Record is the chosen Sample Type 4. Under Sample
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Practice Problems and Exams 1 The Islamic University of Gaza Faculty of Commerce Department of Economics and Political Sciences An Introduction to Statistics Course (ECOE 1302) Spring Semester 2009-2010 Chapter 1 - Introduction and Data Collection Practice Exam - Solution Instructors: Dr. Samir Safi Mr. Ibrahim Abed SECTION I: MULTIPLE-CHOICE 1. The universe or "totality of items or things" under consideration is called a) a sample. b) a population. c) a parameter. d) a statistic. 2. A summary
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allows you to be 95% confident that the confidence interval contains the population parameter? We know from the CLT that sample means are normally distributed around the real population mean (). Any time you have a sample mean within E (margin of error) of then the confidence interval will contain . Since 95% of the sample means are within E of then 95% of the confidence interval constructed in this way will contain. • Why do we use confidence intervals verses point estimates? The sample mean
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= 0.55033 The standard deviation is the square root of the variance‚ which is average of the squares of the distance that each value is from the mean. 2. 95% Confidence Interval = 6.056489716 The CI (confidence interval) is a specific interval estimate of parameter determined by using data obtained from a sample and the specific confidence level of the estimate. 3. Conduct a hypothesis test to verify if the claim that a bottle contains less than sixteen (16) ounces is supported. Clearly state the
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Table of contents 1. Introduction1 2. Problem Statement1 3. Hypothesis1 4. P-value1 5. Statistical summary2 6. 95% confidence interval 2 7. Conclusion3 Appendix 14 1. Introduction This report is about the case study of PAR‚ INC. From the following book: Statistics for Business an Economics‚ 8th edition by D.R. Anderson‚ D.J. Sweeney and Th.A. Williams‚ publisher: Dave Shaut. The case is described at page 416‚ chapter 10. 2. Problem statement Par‚ Inc. has produced a new type of golf ball
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conclusion on the 95% confidence interval estimate of p1—p2. Will all three approaches always result in the same conclusion? Explain. As long as the test is two tailed (so that a confidence interval can be used) and since α = .05 and percent confidence = 1 - .05 = .95‚ then yes‚ the results will NEARLY ALWAYS be the same between traditional approach and confidence interval approach. Also it will NEARLY ALWAYS be the same between the p-value approach and the confidence interval approach. The reason
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Transportation Survey Sample Calculation The confidence interval (also called margin of error) is the plus-or-minus figure usually reported in newspaper or television opinion poll results. For example‚ if you use a confidence interval of 4 and 47% percent of your sample picks an answer you can be "sure" that if you had asked the question of the entire relevant population between 43% (47-4) and 51% (47+4) would have picked that answer. The confidence level tells you how sure you can be. It is expressed
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