AP Statistics Curriculum 2007 Estim Proportion

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=== Estimating a Population Proportion===
=== Estimating a Population Proportion===
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Example on how to attach images to Wiki documents in included below (this needs to be replaced by an appropriate figure for this section)!
 
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<center>[[Image:AP_Statistics_Curriculum_2007_IntroVar_Dinov_061407_Fig1.png|500px]]</center>
 
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===Approach===
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When the sample size is large, the sampling distribution of the sample proportion <math>\hat{p}</math> is approximately Normal, by [[AP_Statistics_Curriculum_2007_Limits_CLT |CLT]], as the sample proportion may be presented as a [[AP_Statistics_Curriculum_2007_Limits_Norm2Bin |sample average or Bernoulli random variables]]. When the sample size is small, the normal approximation may be inadequate. To accommodate this we will modify <math>\hat{p}</math> slightly
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Models & strategies for solving the problem, data understanding & inference.  
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: <math>\hat{p}={y\over n} \longrightarrow \tilde{y}={y+0.5z_{\alpha \over 2}^2 \over n+z_{\alpha \over 2}^2},</math>
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where [[AP_Statistics_Curriculum_2007_Normal_Critical | <math>z_{\alpha \over 2}</math> is the normal critical value we saw earlier]].
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* TBD
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The standard error of <math>\hat{p}</math> also needs a slight modification
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: <math>SE_{\hat{p}} =  \sqrt{\hat{p}(1-\hat{p})\over n} \longrightarrow SE_{\tilde{p}} =  \sqrt{\tilde{p}(1-\tilde{p})\over n+z_{\alpha \over 2}^2}.</math>
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===Confidence intervals for proportions===
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The confidence intervals for the sample proportion <math>\hat{p}</math> and the corrected-sample-proportion <math>\tilde{p}</math> are given by
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: <math>\hat{p}\pm z_{\alpha\over 2} SE_{\hat{p}}</math>
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:<math>\tilde{p}\pm z_{\alpha\over 2} SE_{\tilde{p}}</math>
===Model Validation===
===Model Validation===

Revision as of 05:11, 4 February 2008

Contents

General Advance-Placement (AP) Statistics Curriculum - Estimating a Population Proportion

Estimating a Population Proportion

When the sample size is large, the sampling distribution of the sample proportion \hat{p} is approximately Normal, by CLT, as the sample proportion may be presented as a sample average or Bernoulli random variables. When the sample size is small, the normal approximation may be inadequate. To accommodate this we will modify \hat{p} slightly

\hat{p}={y\over n} \longrightarrow \tilde{y}={y+0.5z_{\alpha \over 2}^2 \over n+z_{\alpha \over 2}^2},

where z_{\alpha \over 2} is the normal critical value we saw earlier.

The standard error of \hat{p} also needs a slight modification

SE_{\hat{p}} = \sqrt{\hat{p}(1-\hat{p})\over n} \longrightarrow SE_{\tilde{p}} = \sqrt{\tilde{p}(1-\tilde{p})\over n+z_{\alpha \over 2}^2}.


Confidence intervals for proportions

The confidence intervals for the sample proportion \hat{p} and the corrected-sample-proportion \tilde{p} are given by

\hat{p}\pm z_{\alpha\over 2} SE_{\hat{p}}
\tilde{p}\pm z_{\alpha\over 2} SE_{\tilde{p}}

Model Validation

Checking/affirming underlying assumptions.

  • TBD

Computational Resources: Internet-based SOCR Tools

  • TBD

Examples

Computer simulations and real observed data.

  • TBD

Hands-on activities

Step-by-step practice problems.

  • TBD

References

  • TBD

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