Confidence interval

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

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 samples

what is the relationship between confidence interval, point estimate, and margin of error for poll results, and (b) how one would design a poll to make the margin of error smaller. The information given is the confidence interval and the sample size. Solve the problem: (a) given a confidence interval, determine the point estimate and the margin of error. Confidence interval is symmetric, so the point estimate has to be the midpoint of the interval. Confidence interval is 46.4% to 59.2%, point estimate

Sqrt[p(1-p)/n] = Sqrt[0.06364*(1-0.06364)/220] = 0.01646 The z- score for 99% confidence is z = 2.576 The 99 percent confidence interval for the proportion of applicants that fail the test is given by (p – z*SE, p – z*SE) = (0.06364 – 2.576*0.01646, 0.06364 + 2.576*0.01646) =(0.06364 – 0.04239, 0.06364 + 0.04239) =(0.02124, 0.10603) =(2.12%, 10.6%) Since 10% falls within the 99% confidence interval but near the upper limit of 10.6%, it may not be reasonable to conclude that more

BUS 308 WK 4 DQ1 - Confidence Intervals As pointed out in the course text, point estimates only provide information about the difference or association between groups. It is not possible to determine the level of accuracy of these estimates because bias may occur in the estimation. In particular, errors may arise in research due to sampling, an inadequate sampling frame, improperly designed research instruments or non-response. While a researcher can minimize bias in research by enhancing the design

in a stable environment (my home). Confidence Intervals Confidence intervals allow us to pinpoint data to a degree of confidence. The intervals are used to estimate the reliability of an estimate. Usually, the confidence levels that are calculated are 90%, 95%, and 99%. The confidence intervals for my particular situation are as follows: |Confidence Intervals |Lower Confidence Interval (mins.) |Upper Confidence Interval (mins.) |

Introduction to Confidence Intervals (page 248) In chapter 7 we discussed how to make inferences about a population parameter based on a sample statistic. While this can be useful, it has severe limitations. In Chapter 8, we expand our toolbox to include Confidence Intervals. Instead of basing our inference on a single value, a point estimate, a Confidence Interval provides a range of values, an interval, which – at a certain level of confidence (90%, 95%, etc.) – contains the true population

large enough sample size over the two sites to confirm this. Males on the pat are larger on both instances compared to males off the pat but due to overlapping of error bars, it cannot be stated with confidence that they are indeed more successful. The only statement that can be made with confidence is that paired males on the pat are considerably larger than solo males off the pat, this can be stated as the error bars do not overlap. With only one sample of paired males off the pat, there is no

Statistical Process Control OPS/571 Over the past five weeks, data has been collected from the process of getting my daughter, Sophie, ready for daycare in the morning. I have tracked six key areas, or steps, in the process: The time it takes to wake her up, The time it takes to get her to go to the bathroom, The time it takes to get her stuff ready, The time it takes to get her dressed, The time it takes to brush her teeth and hair, and The time it takes to get her into the car. In this

distribution (of number of hrs reading newspaper) is approximately normal. a) What will be a 99% confidence interval of the population mean (number of hours a B-school student read newspapers/week)? b) Suppose you perform a similar survey at IIMA with 24 randomly selected students; the sample mean and the sample standard deviation were 4.5 and 2.8 respectively. What will be a 99% confidence interval of the population mean