1 / 17

Chapter 12 Inference for Proportions

Chapter 12 Inference for Proportions. AP Statistics 12.1 – Inference for a Population Proportion. Conditions for Inference of Step II: (z – procedures). Ch 9: The sample proportion is an unbiased estimator of the true population proportion p. = p

raya-anderson
Télécharger la présentation

Chapter 12 Inference for Proportions

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Chapter 12Inference for Proportions AP Statistics 12.1 – Inference for a Population Proportion

  2. Conditions for Inference of Step II: (z – procedures) • Ch 9: The sample proportion is an unbiased estimator of the true population proportion p. = p • Ch 9: Standard deviation of • The data are Randomly and Independently selected from the population of interest.

  3. Conditions for Inference of (z – procedures) • The population size is at least ten times the sample  allows us to use the formula for standard error.N≥10n • theThe sample is sufficiently large to insure Normality of the sampling distribution of • Confidence Intervals: Use • Tests of Significance: Use

  4. Cautions for Proportions • Often proportions use surveys . . . • Many different biases can be introduced: • Undercoverage bias • Non-response bias • Lack or Realism bias – lying, uncomfortable • More likely that sample proportions are overestimates or underestimates of the true population proportion.

  5. Z – procedures: Step III • Confidence Intervals: (statistic) ± (critical value) SE(statistic) • Tests of Significance: • where is the initial pop. Claim P-value = normalcdf(z(low), z(high))

  6. How about a 95% confidence interval?

  7. Choosing the Sample Size • Trying to find the value of n • Recall that • But we don’t know so we will guess • 1. Use a guess based on previous studies • 2. Use = 0.5 as the guess . . . Why? • Sample size for a desired margin of error:

  8. Chavez (take 2) • What if we only want a 2.5% ME? • What if we only want a 2% ME? • Note: Smaller ME’s require larger sample sizes!

More Related