1 / 16

Chris Morgan, MATH G160 csmorgan@purdue.edu March 19 , 2011 Lecture 23

Chris Morgan, MATH G160 csmorgan@purdue.edu March 19 , 2011 Lecture 23. Chapter 7.3, 7.4, & 7.5: Point Estimation, Sampling Distribution of x-bar and p-bar . Sampling Distribution of.

lavender
Télécharger la présentation

Chris Morgan, MATH G160 csmorgan@purdue.edu March 19 , 2011 Lecture 23

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. Chris Morgan, MATH G160 csmorgan@purdue.edu March 19, 2011 Lecture 23 Chapter 7.3, 7.4, & 7.5: Point Estimation, Sampling Distribution of x-bar and p-bar

  2. Sampling Distribution of •The sampling proportion of is the point estimator of the population proportion p. The formula for computing the sample proportion is: x= the number of elements in the sample that possess the characteristic of interest n = the sample size

  3. Sampling Distribution of The sampling distribution of is the probability distribution of all possible values of the sample proportion . To determine how close the sample proportion is to the population proportion p, we need to understand the properties of the sampling distribution of : 1)Expected Value 2)Standard Deviation 3)Form of the Sampling Distribution

  4. Expected Value and Standard Deviation

  5. Form of the Sampling Distribution For a simple random sample from a large population, the value of x is a binomial random variable indicating the number of “successes”. Because n is a constant, the probability of x/n is the same as the binomial probability of x, which means that the sampling distribution of is also a discrete probability distribution and the probability for each value of x/n is the same as the probability of x.

  6. Form of the Sampling Distribution Hopefully this sounds a lot like the normal approximation to the binomial. Thus, we would like to satisfy: AND Assuming these two conditions are satisfied, the probability distribution of x in the sample proportion can be approximated by a normal distribution.

  7. Form of the Sampling Distribution This is like the Normal approximation to the Binomial, but there are two differences: 1.We do not necessarily have to sample from a binomial distribution. 2.We do not use the continuity correction.

  8. Finite Population Correction Factors Finite Population (x) use when n/N > 0.05 Infinite Population (x) use when n/N ≤ 0.05 Finite Population (p) use when n/N > 0.05 Infinite Population (p) use when n/N ≤ 0.05

  9. Example #1a The Grocery Manufacturers of America reported that 76% of consumers read the ingredients listed on a product's label. Assume the population proportion is p = 0.76 and a sample of 400 consumers is selected from the population. a) Find the sampling distribution of the sample proportion of consumers who read the ingredients labels.

  10. Example #1b b) What is the probability that the sample proportion will be within ±0.03 of the population proportion? c) Repeat (b) for 750 consumers.

  11. Example #2a Skittles have 5 colors, and at the factory they make the same proportion of each color. You get a bag of skittles with 70 candies in it. Let R be the proportion of red skittles in your bag. a) What is the approximate distribution R? b) What is the probability that the sample proportion of red skittles is below .2?

  12. Example #2b c) 70% of all sample proportions will fall below what value? d) We want the probability that we get less than 25% red skittles to be .80. If all bags are independent and have 70 skittles in them, how many bags do we need to purchase?

  13. Example #3a The president of Doerman Distributors, Inc., believes that 30% of the firm's orders come from first-time customers. A random sample of 100 orders will be used to estimate the proportion of first-time customers. a) Assume that the president is correct and p = 0.3. What is the approximate distribution of for this study?

  14. Example #3b b) What is the probability that the sample proportion will be between 0.2 and 0.4? c) What is the probability that the sample proportion will be between 0.25 and 0.35?

  15. Example #4a People end up tossing 12% of what they buy at the grocery store (Reader's Digest, March, 2009). Assume this is the true population proportion and that you plan to take a sample survey of 540 grocery shoppers to further investigate their behavior. a) Identify the sampling distribution of , the proportion of groceries thrown out by your sample respondents.

  16. Example #4b b) What is the probability that your survey will provide a sample proportion within ±0.03 of the population proportion? c) What is the probability that your survey will provide a sample proportion within ±0.015 of the population mean?

More Related