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**Chapter 2 Samples and Populations**

Sample vs. Population Design Methods Construction Errors

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**Population/Target Population**

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

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**Young-adults and older**

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

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**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

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**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.

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**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

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**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.

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**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

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**Factors to be considered in a Survey**

Money Time Content/Information

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**Types of Surveys Type of Survey Advantages Disadvantages**

Face-to-face Interview Explain questions, explore issues, make observations, use visual aids Expensive, need interviewer training - at home or work Accuracy, better sampling Expensive - in public areas Cheaper, more people in less time Less representative sample Telephone Interview Accurate, cheap No personal observation Written Questionnaire Cheapest per respondent Bias from low response rate - by mail Allows anonymity Slow - by Cheaper, quicker results - web survey Quicker data processing Need computing expertise

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**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.

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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’

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