Level Confidence Increases Margin Error Decreases
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a confidence interval estimate of a population mean: sample size, variability in the population, and confidence level. For each of these quantities separately, explain briefly what happens how does increasing the level of confidence affect the size of the margin of error to the margin of error as that quantity increases. Answer: As sample why does increasing the confidence level result in a larger margin of error size increases, the margin of error decreases. As the variability in the population increases, the margin of error increases. does margin of error increase with confidence level As the confidence level increases, the margin of error increases. Incidentally, population variability is not something we can usually control, but more meticulous collection of data can reduce the variability in
How Does Increasing The Level Of Confidence Affect The Size Of The Margin Of Error, E?
our measurements. The third of these--the relationship between confidence level and margin of error seems contradictory to many students because they are confusing accuracy (confidence level) and precision (margin of error). If you want to be surer of hitting a target with a spotlight, then you make your spotlight bigger. 2. A survey of 1000 Californians finds reports that 48% are excited by margin of error sample size calculator the annual visit of INSPIRE participants to their fair state. Construct a 95% confidence interval on the true proportion of Californians who are excited to be visited by these Statistics teachers. Answer: We first check that the sample size is large enough to apply the normal approximation. The true value of p is unknown, so we can't check that np > 10 and n(1-p) > 10, but we can check this for p-hat, our estimate of p. 1000*.48 = 480 > 10 and 1000*.52 > 10. This means the normal approximation will be good, and we can apply them to calculate a confidence interval for p. .48 +/- 1.96*sqrt(.48*.52/1000) .48 +/- .03096552 (that mysterious 3% margin of error!) (.45, .51) is a 95% CI for the true proportion of all Californians who are excited about the Stats teachers' visit. 3. Since your interval contains values above 50% and therefore does finds that it is plausible that more than half of the state feels this way, there remains a big question mark in your mind. Suppose you decide that you want to refine your estimate of the population
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If The Margin Of Error Increases The Confidence Interval
Size Affects the Margin of Error How Sample Size Affects the Margin of Error Related Book Statistics For Dummies, 2nd Edition By Deborah J. Rumsey In statistics, the two most important ideas regarding http://inspire.stat.ucla.edu/unit_10/solutions.php sample size and margin of error are, first, sample size and margin of error have an inverse relationship; and second, after a point, increasing the sample size beyond what you already have gives you a diminished return because the increased accuracy will be negligible. The relationship between margin of error and sample size is simple: As the sample size increases, the margin of error decreases. This http://www.dummies.com/education/math/statistics/how-sample-size-affects-the-margin-of-error/ relationship is called an inverse because the two move in opposite directions. If you think about it, it makes sense that the more information you have, the more accurate your results are going to be (in other words, the smaller your margin of error will get). (That assumes, of course, that the data were collected and handled properly.) Suppose that the Gallup Organization's latest poll sampled 1,000 people from the United States, and the results show that 520 people (52%) think the president is doing a good job, compared to 48% who don't think so. First, assume you want a 95% level of confidence, so you find z* using the following table. z*-Values for Selected (Percentage) Confidence Levels Percentage Confidence z*-Value 80 1.28 90 1.645 95 1.96 98 2.33 99 2.58 From the table, you find that z* = 1.96. The number of Americans in the sample who said they approve of the president was found to be 520. This means that the sample proportion, is 520 / 1,000 = 0.52. (The sample size, n, was 1,000.) The margin of error for this polling question is calculated in the following way: According to this data, you conclude wi
a confidence interval estimate of a population mean: sample size, variability in the population, and confidence level. For each of these quantities separately, explain briefly what happens http://inspire.stat.ucla.edu/unit_10/solutions.php to the margin of error as that quantity increases. Answer: As sample size increases, the margin of error decreases. As the variability in the population increases, the margin of error increases. As the confidence level increases, the margin of error increases. Incidentally, population variability is not something we can usually control, but more meticulous collection of data can reduce the variability in our margin of measurements. The third of these--the relationship between confidence level and margin of error seems contradictory to many students because they are confusing accuracy (confidence level) and precision (margin of error). If you want to be surer of hitting a target with a spotlight, then you make your spotlight bigger. 2. A survey of 1000 Californians finds reports that 48% are excited by the margin of error annual visit of INSPIRE participants to their fair state. Construct a 95% confidence interval on the true proportion of Californians who are excited to be visited by these Statistics teachers. Answer: We first check that the sample size is large enough to apply the normal approximation. The true value of p is unknown, so we can't check that np > 10 and n(1-p) > 10, but we can check this for p-hat, our estimate of p. 1000*.48 = 480 > 10 and 1000*.52 > 10. This means the normal approximation will be good, and we can apply them to calculate a confidence interval for p. .48 +/- 1.96*sqrt(.48*.52/1000) .48 +/- .03096552 (that mysterious 3% margin of error!) (.45, .51) is a 95% CI for the true proportion of all Californians who are excited about the Stats teachers' visit. 3. Since your interval contains values above 50% and therefore does finds that it is plausible that more than half of the state feels this way, there remains a big question mark in your mind. Suppose you decide that you want to refine your estimate of the population pro