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Introductory to Applied Statistics

by: Angela Meador

Introductory to Applied Statistics STA 215

Marketplace > Grand Valley State University > Statistics > STA 215 > Introductory to Applied Statistics
Angela Meador

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Introductory Applied Statistics
Robert H. Pearson
Class Notes
applied statistics, introductory
25 ?




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This 1 page Class Notes was uploaded by Angela Meador on Saturday September 24, 2016. The Class Notes belongs to STA 215 at Grand Valley State University taught by Robert H. Pearson in Fall 2016. Since its upload, it has received 5 views. For similar materials see Introductory Applied Statistics in Statistics at Grand Valley State University.


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Date Created: 09/24/16
Sampling Distribution of P hat 1. Center­ P= mean of p hat 2. Spread Standard deviation of p hat = Square root over all (P(1­P)/n)  3. Shape­ p hat is “normal” meaning n multiplied by p or n(1­p) has to be greater or equal to ten. Should be bell­shaped. General Margin of error: Confidence level multiplier multiplied by standard error Hoping that the statistic is not wrong by more than the margin of  error guessed Statistic: Guessing the parameter. Never know how wrong you might guess Standard error: approximation of standard deviation of p hat P hat = square root over all (p hat (1­p hate)/n) Confidence level population proportion 1. Statistic­ p hat­  number of successes over n 2. Find Standard error of p hat 3. Use Z* found on table in book  4. multiply standard error by Z* to equal Margin of Error 5. State inference Include: trait, population, confidence level, and Upper and Lower Limits Hypothesis Attempts Alternative hypothesis Parameter usually comes from a research question, there IS a difference in change and NOT equal to some value. Null Hypothesis Parameter is equal to the value and there is NO difference of change.  ALWAYS the same.


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