Data Collection

Objectives:At the end of this lesson, the student should be able to: 1. recognize the importance of data gathering; 2. distinguish primary from secondary data sources; 3. define population and sampling; 4. define census and sample; 5. identify the various data collection techniques and

sources of data; 6. describe the various instruments for data gathering; 7. cite the advantages of the use of such instruments; 8. recognize the limitations of certain research

instruments;

Sources of Data1. Primary sources of data - are those that

provide information that are collected for the first time as part of a research project.

- - are

tangible materials that provide a description of a historical event and were produced shortly after the event took place.

Example: Newspaper stories, personal letters, public documents, eyewitness, verbal accounts, court decisions, and personal diaries

2. Secondary sources - are those that provide data which have been collected previously and reported by some individual other than the present researcher

- borrowed knowledge from other sources.

Sampling - refers to the processes whereby a sub-group is picked out from a larger group and then use this sub-group as a basis for making judgments about the larger group.

Sub-group - called a sample

Larger group - referred to as population

Terms to Understand Population - is a well - defined set of elements or

cases whether individuals, animals, objects, or events that conform to specific criteria and to which one intend to generalize the results of the research (McMillan, 1998; Wood & Haber, 1998).

A census is a study that collects data from all members of the population.

Target population is the group or set of items or individuals from which or about which representative information is originally desired.

Sampling population is the population from which a sample is actually drawn.

A sample is a set of elements, or a single element, from which data are obtained

Why Do Sampling?

Researchers generally use sampling because of budget, time, and manpower constraints. Such constraints prevent them from undertaking a complete study of the total target population.

Listed below are the four purposes of sampling:1. Reduced cost

2. Greater speed

3. Greater scope

4. Greater accuracy

Probability Sampling Method

A probability sampling method - is any method of sampling that utilizes some form of random selection.

In order to have a random selection method, you must set up some process or procedure that assures that the different units in your population have equal probabilities of being chosen.

Types of Probability Sampling:

1. Simple random sampling - is a process of selecting a sample from a set of all sampling units, giving each unit in the frame an equal chance of being included in the sample.

Two ways of randomly selecting samples: - lottery method

- using table of random numbers - contains columns of digits that have been mechanically generated, usually by a computer, to assume a random order.

2. Systematic sampling - refers to the process of selecting every kth sampling unit of the population after the first sampling unit is selected at random from the first k sampling units

3. Stratified sampling - involves dividing the population into two or more strata and then taking either a simple random (stratified random sampling) or a systematic sample (stratified systematic sampling) from each stratum.

4. Cluster sampling - is a method of selecting a sample of distinct groups of clusters of smaller units called elements.

- A cluster refers to any intact group of similar characteristics.

5. Multistage sampling -is a complex form of cluster sampling. Cluster sampling is a type of sampling which involves dividing the population into groups (or clusters).

- Using all the sample elements in all the selected clusters may be prohibitively expensive or not necessary.

- the researcher randomly selects elements from each cluster.

Two stages of Multistage sampling First stage - Constructing the clusters Second stage - Deciding what elements within the

cluster to use.

The technique is used frequently when a complete list of all members of the population does not exist and is inappropriate.

Nonprobability Sampling Method

Despite the accepted superiority of probability sampling designs, the researcher is sometimes faced with the problem of whether he would use nonprobability sampling or not.

This is especially true when probability sampling becomes expensive or when precise representatives are not necessary.

Types of Nonprobability Sampling:

1. Convenience sampling - is selecting sampling units that are easily (conveniently) available to the researcher.

- It is used in exploratory research where the researcher is interested in getting an inexpensive approximation of the truth.

- used during preliminary research efforts to get a gross estimate of the results, without incurring the cost or time required to select a random sample.

2. Judgment sampling or purposive sampling - is selecting units to be observed on the basis of our judgment about which one will be useful or representative. The researcher selects the sample based on judgment.

3. Quota sampling - is selecting samples on the basis of pre-specified characteristics, so that the total sample will have the same distribution of characteristics as assumed to exist in the population being studied. The researcher first identifies the stratums and their proportions as they are represented in the population.

4. Dimensional sampling - is a multi-dimensional extension of quota sampling.

- In this sampling procedure, instead of a large size, a small size is selected. It is emphasized that all areas of interest should cover at least one case.

5. Voluntary sampling - is a special type of sampling in which subjects/cases are informed about the subject matter willingly or voluntarily participate in the study. This sampling is useful especially if one dealing with information on sensitive or delicate issues.

6. Snowball sampling or sometimes called networking sampling - researcher first identifies few individuals for the sample and uses them as informants. On the basis of their information, the researcher collects the name of more persons bearing similar characteristics.

Useful when one wants to consider possible respondents who are not normally visible.

Used when the desired sample characteristic is rare For example, study of drug addicts in a university, or a study of socio-

economic conditions of teacher-retirees, or a study of patients with AIDS

Data Collection Methods

1. Questionnaire - is often referred to as a “lazy man’s way of gaining information”. It is also said that it is the most used and abused of data-gathering devices. However, a carefully prepared questionnaire can yield better data.

2. Interview Method - is one of the data-gathering techniques in research. It is defined as a face-to-face interaction between two persons. The one who asks questions is called the interviewer and the one who supplies the information asked for is called the interviewee or respondent.

There are three basic types of interviews. scheduled-structured interview, nonscheduled-structured interview nonscheduled interview

3. Opinionnaire - is an instrument that attempts to obtain the measured attitude or belief of an individual. The opinionnaire is usually used to infer attitude-expressed opinion of an individual.

This may be done by: directly asking how one feels about the subject In asking an individual directly how one feels about the subject, we

may use either semantic differential scale or the Likert scale.

4. Projective methods - involve some sort of imaginative activity on the part of the individual in interpreting ambiguous stimuli.

Projective methods were first used by psychologists wherein tests administered provide a comprehensive picture of an individual’s personality structure, emotional needs, conflicts and other feelings. In these tests, responses of the individual are not taken on face value but are based on some pre-established psychological conceptualization. The use of pictures, verbal techniques, and play techniques are mostly used in projective methods

5. Observation - is a process whereby the researcher watches the research situation.

This data-collecting technique is mostly used when the respondents are unwillingly to express themselves verbally.

Observation may be natural or contrived; disguised or undisguised; structured or unstructured; direct or indirect.