1 / 12

Chapter 2 Samples and Populations

Chapter 2 Samples and Populations. Sample vs. Population Design Methods Construction Errors. Sample vs. Population. Population – the totality of subjects under consideration Target Population – consists of all subjects considered in the study

dyre
Download Presentation

Chapter 2 Samples and Populations

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 2 Samples and Populations Sample vs. Population Design Methods Construction Errors

  2. Sample vs. Population Population – the totality of subjects under consideration Target Population – consists of all subjects considered in the study Sample – a portion or a subset of the population for data collection and analysis Population/Target Population Sample

  3. Sample vs. Population Population Sample Target Population Kalamazoo Young-adults and older House -holds

  4. Census vs. Sample Survey Census – collection of data using all subjects in the population Sample Survey – collection of data from a representative sample of the population Population/ Target Population Sample Note: Random Samples should be representative of the population

  5. Study Design or Protocol Design Steps involved in solving problems How do I solve this problem? ? ? Study design is done prior to data collection. It involves methods in data collection, analysis of the data and conclusions to be made.

  6. Probability vs. Non-Probability Sampling Probability Sampling – subjects are chosen by chance Non-probability Sampling – can be used for informal and less scientific studies Note: Non-probability sampling tend to be less representative of the target population

  7. Methods in Probability Sampling Simple Random Sampling (SRS) – samples are randomly selected from the population K-in-1 Systematic Sampling – Every kth subject is chosen Stratified Random Sampling – population is divided into subgroups called strata and SRS chosen from each strata Cluster sampling – population is divided into subgroups called clusters and clusters are randomly chosen as samples.

  8. Example: Household Expenditures in Michigan Target Population : Households in Michigan Simple Random Sampling – randomly selecting the sample from a list of households Systematic Sampling – every 10th household Stratified Sampling – take samples from each county Cluster Sampling – selecting counties in Michigan

  9. Factors to be considered in a Survey Money Time Content/Information

  10. Types of Surveys

  11. Construction of Questionnaire Is the question understandable? Are you gathering knowledge or attitude? Are the questions loaded? Do the questions ask for sensitive information? Note: An accurate answer leads to a good study and it starts from asking important questions correctly.

  12. Types of Survey Errors Coverage errors – sampling frame excludes some segments of the target population Non-response errors – can cause bias in survey results Measurement errors – occurs when respondents answer ‘incorrectly’

More Related