Welcome To Presentation

A.S.M Yeasser Arafat

Sources of Data

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

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.

Surveys

ConceptA process that uses questionnaires or similar means

Examplelikely voters, a website instant poll or “question of the day.”

Why Needed?open to anyone who wants to participate targeted, specific group

Sampling Concepts

calculating statistics for a sample is the most common activity because collecting population data is usually impractical

Frame

Conceptall items in the population from which the sampleExampleVoter registration lists, municipal real estate recordsWhy we need to use?Frames influence the results of an analysis, and using different frames

Sampling

ConceptThe process by which members of a population are selected for a sample

ExamplesChoosing 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.

Probability Sampling

ConceptA sampling process that considers the chance of selection of each item.

Examplesthe 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.

Simple Random Sampling

ConceptEvery individual or item from a population has the same chance of selection as every other individual or item.

ExamplesSelecting 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

Sample Selection Methods

Sampling with Replacement

Concepteach selected item is returned to the frame

ExamplesSelecting 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

Sampling Without Replacement

Concepteach selected item is not returned to the frame from which it was selected.

ExamplesSelecting 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.