Lesson 2: Data Collecting Techniques

Data

is various kinds of information formatted in a particular way

Data collection

is the process of gathering, measuring, and analyzing accurate data from a variety of relevant sources to find afind answers to research problems, answer questions, evaluate outcomes, and forecast trends and probabilities.

1. Primary Data

2. Secondary Data

Sources of Data

Primary data

is original information collected firsthand by a researcher specifically to address a current research question or objective.

Primary data

refers to information gathered directly from the source for a specific study or research purpose, rather than relying on previously collected or published data. It is original, fresh, and tailored to the research objectives, ensuring high relevance and specificity to the study at hand. Unlike secondary data, which is pre-existing and collected for other purposes, primary data is generated to answer the current research question, making it more precise and directly applicable to the investigation.

• Collected firsthand from the source

• Can be qualitative, quantitative, or mixed

• Generated through direct interaction, observation, or measurement

• Tailored to the specific objectives of the research

• Requires ethical safeguards, quality control, and valid sampling to ensure reliability

Key Characteristics of Primary Data

Secondary data

is pre-existing information reused for a research purpose different from, or additional to, the purpose for which it was originally collected.

• Existed before the current analysis

• Their original purpose may differ from the new purpose

• The current researcher has limited control over their creation

• Require contextual documentation

• Quality is purpose - dependent

Key Characteristics of Secondary Data

Primary Data

Source: Collected firsthand by researcher

Primary Data

Purpose: Specific to current research

Primary Data

Time: Takes longer to collect

Secondary data

Source: Collected by others

Secondary data

Purpose: May have different original purpose

Secondary data

Time: Quickly available

1. Case studies

2. Digsite

3. Oral Histories

4. Questionnaire

5. Documents and Records

6. Interviews

7. Observations

8. Polls

9. Experiments

10. Focus Groups

Primary Data Collection Methods

1. Literature Review

2. Online Database WBS

3. Government Reports and Statistics

4. Industry Reports and Market Research

5. Historical Records

6. Previous Research Studies

Secondary Data Collection Methods

1. Indirect Method

2. Direct Method

Methods of Data Collection

Direct method

involves collecting data straight from the source, providing firsthand, original information. This method is often used to obtain primary data and ensures high accuracy and reliability.

Indirect method

involves collecting data through intermediaries or existing sources, rather than directly from the original subject. This method often uses secondary data or relies on third-party information.

Structured

• Collects quantitative data

• Set of standardized closed-ended questions

• Example: Demographic census questionnaire

Unstructured

• Collects qualitative data

• Set of standardized open-ended questionnaire

• Example: Target audience questionnaire

The Difference between a Structured and Unstructured Questionnaire

Simple Random Sampling

In this technique, every item in the population has an equal and likely chance of being selected in the sample. Since the item selection entirely depends on the chance, this method is known as “Method of chance Selection”. As the sample size is large, and the item is chosen randomly, it is known as “Representative Sampling”

Systematic Sampling

In this method, the items are selected from the target population by selecting the random selection point and selecting the other methods after a fixed sample interval. It is calculated by dividing the total population size by the desired population size

Stratified Sampling

In this method, the total population is divided into smaller groups to complete the sampling process. The small group is formed based on a few characteristics in the population. After separating the population into a smaller group, the statisticians randomly select the sample

Clustered Sampling

In tthis method, the cluster or group of people are formed from the population set. The group has similar significatory characteristics. Also, they have an equal chance of being a part of the sample. This method uses simple random sampling for the cluster of population.

1. Nature of the Research Study

2. Objective of the Study

3. Population Characteristics

4. Sample Size

5. Accuracy and Precision Requirements

6. Available Resources

7. Accessibility of the Population

8. Ethical Considerations

9. Level of Bias Acceptable

10. Statistical Requirements

11. Need for Comparisons or Subgroup Analysis

12. Generalizability of the Results

Criteria for Choice of Sampling Technique

Slovin’s Formula

98.76 or 99

A group of student researchers is conducting a survey to find out the opinion of the residents of a particular barangay regarding the Pax Silica Initiative. If there are 8,000 residents in that barangay and the student researchers decided to use a sample with 10% margin of error, what should be the sample size?

381

Suppose in the first situation, the student researchers would like to use only a 5% margin of error, what should the sample size be?

14%

From a population of 800, a researcher of limited resources decided to use only a sample of 50 respondents, estimate the measure of margin of error?