2017Unpublished venueRequires access

Homing in on the Population Mean II

Jeffrey E Kottemann

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Abstract

This chapter explores how strongly, on average, members of one particular community agree or disagree with a new proposed policy. It surveys 100 random members and records their responses. Since the true population variance in this scenario is unknown, as is usually the case in practice, the sample variance is used instead. By plugging in the statistical scenario numbers we get a 95% confidence interval. Using the sample variance as an estimate of the population variance introduces additional uncertainty. The hypothesis that the true population mean could be 4.0. √ s2/n is the estimate for the standard error of a sample mean involving the sample variance s2 and the sample size n. It is an estimate of standard error because we are using the sample variance rather that the population variance, and the sample variance is an estimate of the population variance.

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What this paper is about

This chapter explores how strongly, on average, members of one particular community agree or disagree with a new proposed policy. It surveys 100 random members and records their responses. Since the true population variance in this scenario is unknown, as is usually the case in practice, the sample variance is used instead. By plugging in the statistical scenario numbers we get a 95% confidence interval. Using the sample variance as an estimate of the population variance introduces additional uncertainty. The hypothesis that the true population mean could be 4.0. √ s2/n is the estimate for the standard error of a sample mean involving the sample variance s2 and the sample size n. It is an estimate of standard error because we are using the sample variance rather that the population variance, and the sample variance is an estimate of the population variance.

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Available abstract

This chapter explores how strongly, on average, members of one particular community agree or disagree with a new proposed policy. It surveys 100 random members and records their responses. Since the true population variance in this scenario is unknown, as is usually the case in practice, the sample variance is used instead. By plugging in the statistical scenario numbers we get a 95% confidence interval. Using the sample variance as an estimate of the population variance introduces additional uncertainty. The hypothesis that the true population mean could be 4.0. √ s2/n is the estimate for the standard error of a sample mean involving the sample variance s2 and the sample size n. It is an estimate of standard error because we are using the sample variance rather that the population variance, and the sample variance is an estimate of the population variance.

Key concepts: Population variance, Variance (accounting), Sample variance, Statistics, Sample (material), Population, Law of total variance, Confidence interval

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