# 6-What is sample.pptx

30 de May de 2023
1 de 11

### 6-What is sample.pptx

• 1. What is a sample?  A sample is a finite part of a statistical population whose properties are studied to gain information about the whole population (e.g. people) set of respondents selected from a larger pop.  A population is a group of individuals persons, objects, or items from which samples are taken for measurement (e.g. a population of professors, or students or books).
• 2. What is sampling  Sampling is the act, process, or technique of selecting a suitable sample, or a representative part of a population for the purpose of determining parameters or characteristics of the whole population.
• 3. What is the purpose of sampling  To draw conclusions about populations.... to determine characteristics.....  We obtain a sample rather than a complete enumeration (a census ) of the population for many reasons…..but we should prepare ourselves to cope with the dangers of using samples.  There are various kinds of sampling procedures. Some are better than others but all may yield samples that are inaccurate and unreliable.
• 4. Reasons for selecting sample 1. Economy: financial constraints allow you to select a smaller sample size. 2. Timeliness: allowed time period in which the research has to be completed 3. The large size of many populations: you cannot sample the whole population, (only in census one goes door to door for information) 4. Inaccessibility of some of the pop: some population areas are hard to reach; 5. Destructiveness of the observation: quality control 6. Accuracy: smaller size of sample would have more accuracy than a larger and unmanageable sample.
• 5. Bias and Error in sampling  Sampling error: is the diff. b/w Sample n pop that are due solely to a particular units that happen to have been selected  Two basic causes of Error:  1. Chance occurs because of bad luck, unusual units in a pop do exist and there is always a possibility that an abnormally large number of them will be chosen. For e.g. 50 households were selected and information was collected about the number of household members, now normally there are 5 to 6 members but in this sample there were two households that had 15 to 22 members, this would affect the overall average.
• 6. Condt.  2 . Bias sampling bias is a tendency to favour the of unit to have particular characteristics. It results due to poor sampling plan. For e.g. a mail questionnaire was sent to 100 randomly selected graduate students to find out the level of stress they are going through. Only 52 responded and showed that students were not under stress whereas other 48 students who did not responded because they were busy in preparation for the up coming exam. Here another impt. Issue is that a lot of money was spent on this study now it all wasted. Clearly it shows NON-RESPONSE  Non sampling error: solely from the manner in which the observations are made. E.g. measurement due malfunctioning of instrument or poor procedure.. For e.g human weights.. Measuring BP, etc.
• 7. Bias and Error in sampling  The interviewer’s effect:  Manner in which question is formulated  Individuals tend to provide false answers to a particular question for example age  The respondent’s effect:  To impress the interviewer, ask men and women about the harvest of the last season you will get different reply, men always tend to lie, so it is most difficult to prevent. “psychological factors” induce incorrect reposses..  Knowing the study purpose: why is the study is being conducted may create incorrect answers for e.g study on find income of household..  What is your income , if govt. agency is asking you will get different answer …. May be to dodge Income Tax..  Induced bias:  Personal prejudices.. Designer or data collector would ask questions as they want to have the answer.
• 8. Sampling methods  Can be classified as either:  1. Probability  2. Non-probability Probability: each member of the population has a probability of being selected..e.g. random, systematic, stratified sampling Non-Probability: members are selected from the pop. In some non-random manner..e.g. convenience, judgment, quota sampling.
• 9. Types of Samples  There are three primary kinds of samples:  the convenience,  the judgment sample, and  the random sample. They differ in the manner in which the elementary units are chosen
• 10. Types of Samples contd  The convenient sample  A convenience sample results when the more convenient elementary units are chosen from a population for observation.  The judgment sample  A judgment sample is obtained according to the discretion of someone who is familiar with the relevant characteristics of the population.  The random sample  This may be the most important type of sample. A random sample allows a known probability that each elementary unit will be chosen. For this reason, it is sometimes referred to as a probability sample.
• 11. TYPES OF RANDOM SAMPLES  A simple random sample: Each unit has equal chance of being selected  A systematic random sample: Selecting one unit on a random basis and choosing additional units at evenly spaced intervals..e.g 100 students…20 to be selected  A stratified sample: simple random sample from each stratum..e.g.SES , education, income etc  A cluster sample: Clusters from the population on the basis of simple random selection.. e.g.State..Schools..teachers…opinions