malfunction. The problem is to compute the 95% confidence interval on π‚ the proportion that malfunction in the population. Solution: The value of p is 12/40 = 0.30. The estimated value of σp is = 0.072. A z table can be used to determine that the z for a 95% confidence interval is 1.96. The limits of the confidence interval are therefore: Lower limit = .30 - (1.96)(0.072) = .16 Upper limit = .30 + (1.96)(0.072) = .44. The confidence interval is: 0.16 ≤ π ≤ .44. Q2. A manager at a power
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Practice Problems for Confidence Intervals X ± Z σ/n ; X ± t s/n ; p ± Z (p(1-p)/n) 1. A press release issued by our university claims that West Chester students study at least as much as the national average for students at four year universities. Across the nation‚ 73 percent of all students at four year universities study at least four hours per week. Seventy percent of one hundred randomly selected West Chester students surveyed claimed to study more than four hours per week.
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Confidence Intervals Consider the following question: someone takes a sample from a population and finds both the sample mean and the sample standard deviation. What can he learn from this sample mean about the population mean? This is an important problem and is addressed by the Central Limit Theorem. For now‚ let us not bother about what this theorem states but we will look at how it could help us in answering our question. The Central Limit Theorem tells us that if we take very many
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Confidence is the belief that one will perform in a correct‚ proper‚ or effective way. This belief‚ in my opinion‚ is the key to succeeding in many things we do. I can recall several circumstances in which the possession of confidence was the deciding factor between my success and failure Taking tests is one of the most prominent instances in which confidence is the key to success. I reThe reason I performed well on the exam is because of the confidence I had in my knowledge of the test material
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Statistics for Managers using Microsoft Excel 6th Edition Module 4 Sampling & Confidence Interval Estimation Copyright ©2012 Pearson Education Chap 8-1 Chapter Outline Confidence Intervals for the Population Mean‚ μ when Population Standard Deviation σ is Known when Population Standard Deviation σ is Unknown Confidence Intervals for the Population Proportion‚ p Determining the Required Sample Size Copyright ©2012 Pearson Education Chap 8-2 Introduction Copyright ©2012 Pearson
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Sample sizes and confidence intervals for proportions Chong Chun Wie Ext: 2768 ChongChunWie@imu.edu.my Content • Sampling distribution of sample means (SDSM) • Normality Test • Estimating a population mean: σ known • Estimating a population mean: σ unknown • Standard deviation of proportion • Confidence interval of proportion • Hypothesis testing with proportion Population and Sample Samples Populations Sampling distribution of sample means (SDSM) Sampling distribution • Example – Select
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Beowulf’s Confidence Beowulf was written in the earliest age of English poetry. Back in the Anglo-Saxon times‚ in order to make a name for themselves‚ warriors had to fight in battles. They believe that you should fight until death with absolutely no retreating. Beowulf‚ a young Geatish warrior‚ comes to Hrothgar’s kingdom to return a favor to him. While Beowulf is there‚ he fights in two battles; the battle with Grendel and the battle with Grendel’s mother. Much later in the poem‚ he fights
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34:337–347 DOI 10.1007/s10979-009-9192-x ORIGINAL ARTICLE The Effect of Retention Interval on the Confidence–Accuracy Relationship for Eyewitness Identification James Sauer Æ Neil Brewer Æ Tick Zweck Æ Nathan Weber Published online: 22 July 2009 Ó American Psychology-Law Society/Division 41 of the American Psychological Association 2009 Abstract Recent research using a calibration approach indicates that eyewitness confidence assessments obtained immediately after a positive identification decision provide
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calculated in order to obtain a point estimate of the mean overpayment. The estimated mean is then extrapolated to the overpayment amount to the population of all 1‚000 claims. http://pages.wustl.edu/montgomery/lecture-7 Point Estimate vs. Interval Estimate To estimate population parameters‚ statisticians use sample statistics. For example‚ we use sample means to estimate population means and we use sample proportions to estimate population proportions. An estimate of a population parameter
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Confidence intervals and prediction intervals from simple linear regression The managers of an outdoor coffee stand in Coast City are examining the relationship between coffee sales and daily temperature. They have bivariate data detailing the stand ’s coffee sales (denoted by [pic]‚ in dollars) and the maximum temperature (denoted by [pic]‚ in degrees Fahrenheit) for each of [pic] randomly selected days during the past year. The least-squares regression equation computed from their data
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