Source of data & sampling
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You begin every statistical analysis by identifying the source of the data. Among the important sources of data are published sources, experiments, and surveys.
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This document discusses different types of statistics used in research. Descriptive statistics are used to organize and summarize data using tables, graphs, and measures. Inferential statistics allow inferences about populations based on samples through techniques like surveys and polls. The key difference is that descriptive statistics describe samples while inferential statistics allow conclusions about populations beyond the current data.
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The document discusses different sampling techniques used in research. It describes probability sampling methods like simple random sampling, systematic sampling, stratified random sampling, and multistage cluster sampling which ensure that each population element has a known chance of selection. It also covers non-probability sampling which uses arbitrary selection. Key advantages of probability sampling include controlling for bias and representing the population, while non-probability sampling has lower costs. Sample size is based on desired precision, population variability, and confidence level.
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Source of data & sampling
- 1. Welcome To Presentation A.S.M Yeasser Arafat
- 3. Published Sources CONCEPT Data available in print, electronic, Internet websites. Primary data, Secondary data. EXAMPLE Many U.S. federal agencies are publish primary data in internet website. Business news sections of daily newspapers… Why we need to use? Possible bias of the publisher and whether the data contain all the necessary and relevant variables
- 4. Experiments CONCEPT A study that examines the effect on a variable of varying the value(s) of another variables. A typical experiment contains both a treatment group and a control group. EXAMPLE Pharmaceutical companies use experiments to determine whether a new drug is effective. Why we need to use? Proper experiments are either single-blind or double blind.
- 5. Surveys Concept A process that uses questionnaires or similar means Example likely voters, a website instant poll or “question of the day.” Why Needed? open to anyone who wants to participate targeted, specific group
- 6. Sampling Concepts calculating statistics for a sample is the most common activity because collecting population data is usually impractical
- 7. Frame Concept all items in the population from which the sample Example Voter registration lists, municipal real estate records Why we need to use? Frames influence the results of an analysis, and using different frames
- 8. Sampling Concept The process by which members of a population are selected for a sample Examples Choosing every fifth voter who leaves a polling place to interview Why we need to use? Some sampling techniques, such as an “instant poll” found on a web page, are naturally suspect as such techniques do not depend on a well-defined frame.
- 9. Probability Sampling Concept A sampling process that considers the chance of selection of each item. Examples the patients selected to fill out a patient-satisfaction questionnaire Why we need to use? You should use probability sampling whenever possible, because only this type of sampling enables you to apply inferential statistical methods to the data you collect.
- 10. Simple Random Sampling Concept Every individual or item from a population has the same chance of selection as every other individual or item. Examples Selecting a playing card from a shuffled deck or using a statistical device, such as a table of random numbers. Why we need to use? •where not much information is available about the population . •an unbiased surveying technique
- 12. Sampling with Replacement Concept each selected item is returned to the frame Examples Selecting items from a fishbowl and returning each item to it after the selection is made. Why we need to use? •the two sample values are independent •what we get on the first one doesn't affect what we get on the second
- 13. Sampling Without Replacement Concept each selected item is not returned to the frame from which it was selected. Examples Selecting numbers in state lottery games, selecting cards Why we need to use? •the two sample values aren't independent •this means that what we got on the for the first one affects what we can get for the second one.