1 / 8

Math 145

Math 145. September 3, 2014. Statistics. is the science of collecting, analyzing, interpreting, and presenting data . Two kinds of Statistics: Descriptive Statistics. Inferential Statistics.

steview
Télécharger la présentation

Math 145

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. Math 145 September 3, 2014

  2. Statistics is the science of collecting, analyzing, interpreting, and presenting data. Two kinds of Statistics: • Descriptive Statistics. • Inferential Statistics. A statistical inference is an estimate, prediction, or some other generalization about a population based on information contained in the sample.  Use arepresentative sample.

  3. Sampling Designs • Simple Random Sampling. • Systematic Random Sampling. • Cluster Sampling. • Stratified Random Sampling with Proportional Allocation.

  4. Simple Random Sampling • A sampling procedure for which each possible sample of a given size has the same chance of being selected. • Population of 5 objects: {A, B, C, D, E} • Take a sample of size 2. • Possible samples: {(A,B), (A,C), (A,D), (A,E), (B,C), (B,D), (B,E), (C,D), (C,E), (D,E)} • Random number generators

  5. Systematic Random Sampling • Step 1. Divide the population size by the sample size and round the result down to the nearest number, m. • Step 2. Use a random-number generator to obtain a number k, between 1 and m. • Step 3. Select for the sample those numbers of the population that are numbered k, k+m, k+2m, … • Expected number of customers = 1000 • Sample size of 30  m = 1000/30 = 33.33  33 • Suppose k = 5. Then select {5, 5+33, 5+66, …}

  6. Cluster Sampling • Step 1. Divide the population into groups (clusters). • Step 2. Obtain a simple random sample of clusters. • Step 3. Use all the members of the clusters in step 2 as the sample.

  7. Stratified Random Sampling with Proportional Allocation • Step 1. Divide the population into subpopulations (strata). • Step 2. From each stratum, obtain a simple random sample of size proportional to the size of the stratum. • Step 3. Use all the members obtained in Step 2 as the sample. • Population of 10,000 with 60% females and 40% males • Sample of size 80.  48 females (from 6,000) and 32 males (from 4,000).

  8. Homework • Answer # 1, 2, 5, 7, 10. on page 18.

More Related