Assignment...

1. ‘Generalizability’ in Sampling:

A sample should be as large as the researcher can obtain a reasonable expenditure of time and energy as large as they reasonably can.

2. Distinguish sample from population:

A sample is a small proportion of a population selected for observation and analysis. By observing the characteristics of the sample, one can make certain inferences about the characteristics of the population from which it is drawn. But a population is any group of individuals that have one or more characteristics in common that are of interest to the researcher.

3. meaning of the term “representative sample”:

A subset of a statistical population that accurately reflects the members of the entire population. A representative sample should be an unbiased indication of what the population is like. In a classroom of 30 students in which half the students are male and half are female, a representative sample might include six students: three males and three females.

4.Explain how a target population differs from an accessible population.

Target population (universe):

The entire group of people or objects to which the researcher wishes to generalize the study findings

Meet set of criteria of interest to researcher

Examples

All institutionalized elderly with Alzheimer's

All people with AIDS

Accessible population:

the portion of the population to which the researcher has reasonable access; may be a subset of the target population

May be limited to region, state, city, county, or institution

Examples

All institutionalized elderly with Alzheimer's in St. Louis county nursing homes

All people with AIDS in the metropolitan St. Louis area.

5. What is meant by randomization? Explain ‘random selection’ and ‘random assignment’ in  sampling?

In this sampling technique, the researcher must guarantee that every individual has an equal opportunity for selection and this can be achieved if the researcher utilizes randomization.

Random selection is how you draw the sample of people for your study from a population. 

Randomassignment is how you assign the sample that you draw to different groups or treatments in your study.

6. Three ways of obtaining  Random Sampling:

Simple random sampling:

Simple random sampling means that every member of the sample is selected from the total population in such a manner that all members of the population have essentially the same probability of being selected.

Incidental sampling:

It applies to those group which are used chiefly because they are easily or readily constituted radon, sample of any definable population. 

Purposive sampling:

It can be considered a form of stratified sampling in that the selection of cases is governed by some criterion acting as a secondary control.

7. What are the situations in which a researcher goes for non-random sampling?

Non-random sampling is useful when time is limited, a sampling frame is not available, the research budget is very tight or when detailed accuracy is not important.

A researcher may not be able to obtain a random or stratified sample, or it may be too expensive. A researcher may not care about generalizing to a larger population. The validity of non-probability samples can be increased by trying to approximate random selection, and by eliminating as many sources of bias as possible, in that situation a researcher goes for non-random sampling.

8. Explain non-random sampling techniques with examples.

Forms of sampling that do not adhere to probability methods. Probability methods choose samples using random selection and every member of the population has an equal chance of selection. Some types of nonrandom sampling still aim to achieve a degree of representativeness without using random methods. Several different techniques are associated with this approach, for example accidental or convenience sampling; snowball sampling; volunteer sampling; quota sampling, and theoretical sampling. Convenience samples are also known as accidental or opportunity samples. The problem with all of these types of samples is that there is no evidence that they are representative of the populations to which the researchers wish to generalize. 

9.  What does a table of random numbers mean?

A table of numbers generated in an unpredictable, haphazard sequence. Tables of random numbers are used to create a random samples. A random number table is therefore also called a random sample table. A random number table is a list of numbers, composed of the digits 0, 1, 2, 3, 4, 5, 6, 7, 8, and 9. Numbers in the list are arranged so that each digit has no predictable relationship to the digits that preceded it or to the digits that followed it.

10. Explain what is meant by the term ‘ external validity’.

This refers to the extent to which the results of a study can be generalized or extended to others. For example, if a study on a drug is only conducted on white, middle aged, overweight, women with diabetes, can the results of the study be generalized to the rest of the population? Are the results only valid to the population studied? Researchers go to great lengths to select a group of people for the study (a sample) that is representative enough that the results can be extended to lots of people.

11. Explain ‘population generalizability’ and  ‘ ecological generalizability’.

Population generalizability:  It refers to the degree to which a sample represents the population of interest.

Ecological generalizability:  The degree to which results of a study can be extended to other settings of the condition or settings other than those that prevalent in a particular study.

12.Write briefly on ‘sample size’ and ‘sampling ratio’.

Sample size: The determination of sample size is a common task for many organizational researchers. Inappropriate, inadequate, or excessive sample sizes continue to influence the quality and accuracy of research. 

Sample ratio:Sampling ratio is size of sample divided by size of population.

13. What does sampling error mean? Explain.

Sampling error is simply the difference between the value of parameter and that of corresponding statistic or the difference between population value and sample value.