OUTLINESAMPLING.

SAMPLING PROCESS.

SAMPLING TYPES.

SAMPLING ERROR.

SAMPLE SIZE

SAMPLINGThe process of obtaining information from a sample of a larger group (population).

A sample is “a smaller (but hopefully representative) collection of units from a population used to determine truths about that population”.

SAMPLING

Characteristics of Good Samples

Representative

Accessible

Low cost

SAMPLING PROCESS1. Define the population :

The Element ..... individualsfamiliesseminar groups

Sampling Unit…. individuals over 20families with 2 kidsseminar groups at ”new” university

Extent ............ individuals who have bought “one”families who eat fast foodseminar groups doing MR

Timing ......... bought over the last seven days

SAMPLING PROCESS2. Identify the sampling frame :

Select “sample units”

Individuals

Household

Streets

Telephone numbers

Companies

SAMPLING PROCESS1. Select a sampling design or procedure :

PROBABILITY NON- PROBABILITY

2. Determine the sample size.

3. Draw the sample.

SAMPLING PROCESS

SAMPLING TYPESProbability sampling - equal chance of being included in the sample (random)◦ -simple random sampling

◦ -systematic sampling

◦ -stratified sampling

◦ -cluster sampling

Non-probability sampling - unequal chance of being included in the sample (non-random)◦ -convenience sampling

◦ -judgment sampling

◦ -snowball sampling

◦ -quota sampling

Probability sampling

SIMPLE RANDOM SAMPLINGA sampling procedure in which every element in the population has a known and equal chance of being selected as a subject (e.g., drawing names out of a hat).

SYSTEMATIC SAMPLINGIf a sample size of n is desired from a population containing N elements, we might sample one element for every n/N elements in the population.

STRATIFIED SAMPLINGPopulation is divided on the basis of characteristic of interest in the population e.g. male and female may have different consumption patterns.

Cluster or Area Random SamplingClusters of population units are selected at random by dividing the population into clusters (usually along geographic boundaries) and then all or some randomly chosen units in the selected clusters are studied.

Non-probability sampling

CONVENIENCE SAMPLINGSometimes known as grab or opportunity sampling or accidental or haphazard sampling.

A type of non probability sampling which involves the sample being drawn from that part of the population which is close to hand. That is, readily available and convenient.

JUDGMENTAL SAMPLING

The researcher chooses the sample based on who they think would be appropriate for the study.

This is used primarily when there is a limited number of people that have expertise in the area being researched.

SNOWBALL SAMPLING Selection of additional respondents is based on referrals from the initial respondents.

◦ - friends of friends

Used to sample from low incidence or rare populations.

QUOTA SAMPLINGQuota sampling is a method for selecting survey participants.

In quota sampling, a population is first segmented into mutually exclusive sub-groups, just as in stratified sampling.

Then judgment is used to select the subjects or units from each segment based on a specified proportion.

For example, an interviewer may be told to sample 200 females and 300 males between the age of 45 and 60.

This means that individuals can put a demand on who they want to sample (targeting).

SAMPLING ERROR

Random Sampling Error Random error- the sample selected is not representative of the population due to chance.

The level of it is controlled by sample size.

A larger sample size leads to a smaller sampling error.

Non-sampling ErrorSystematic Error

◦

The level of it is not controlled by sample size.

The basic types of non-sampling error A non-response error occurs when units selected as part of the sampling procedure do not respond in whole or in part .

A response or data error is any systematic bias that occurs during data collection, analysis or interpretation, like:

◦ Respondent error (e.g., lying, forgetting, etc.).

◦ Interviewer bias.

◦ Recording errors.

◦ Poorly designed questionnaires

Probability Vs. Non-Probability Sampling Non-probability sampling is less time consuming and less expensive.

The probability of selecting one element over another is not known and therefore the estimates cannot be projected to the population with any specified level of confidence.

SAMPLE SIZESize of sample should be determined by a researcher keeping in view:

1. Nature of universe: homo (small sample)

hetero (large sample).

2. No. of classes proposed: directly proportional to the sample size .

3. Nature of study: general (large)

intensive (small).

4. Type of sampling: small random sample is better than a large but bad one.

SAMPLE SIZE5. Standard of accuracy: high level of precision large sample.

6. Availability of finance: sample size =amount of money available.

7. Other considerations: size of population,

size of questionnaire,

nature of units,

conditions.