Chapter 2: Collection of Data

COLLECTION OF DATA

A process of obtaining

numerical

measurements

process of gathering and measuring

information on variables of interest, in an established systematic fashion that enables one to answer stated research questions, test hypotheses, and evaluate outcomes

TWO SOURCES OF DATA

1. Documentary Sources

Published or unpublished

reports, statistics, Internet,

letters, magazines,

newspapers, diaries, etc

a. Primary Data

Data gathered are original

b. Secondary Data

Data is taken from an original source which is computed and compiled.

2. Field Sources

Individuals who have sufficient knowledge and experience regarding the study under investigation.

METHODS USED IN DATA

COLLECTION

1. The Direct Method

referred as interview method

face to face encounter

2. The Indirect Method

questionnaire methodquestionnaire-lists of questions

3. The Registration Method

utilizing the existing data/fact/info which is kept systemized by the office concerned

4. The Observation Method

used to collect data pertaining attitudes, behaviour, values, and cultural patterns of the samples under investigation

5. The Experiment Method

cause and effect relationship

used in making a scientific inquiry

PLANNING THE STUDY

1. Estimate the number of items in the population.

2. Assess resources such as time and money

3. Determine the sample size using the Slovin’s formula

n = N 1 + Ne2

see table 1: Sample size for a Specified Margin of Error on page 21

n = sample sizeN = population sizee = margin of error

4. Pick the sample by using the appropriate sampling technique.

5. Prepare the questions to be asked in the interview or in the questionnaire.

TYPES OF QUESTIONS

1. Structured Question

one way or few alternativesclear, simple, objective and easy to answer and tabulate

2. Open-ended Questions

can be answered in many ways-probing or questions w/c elicit reasons

FEATURES OF A GOOD

QUESTIONNAIRE

short and clearavoid leading questionsalways state the precise units

can be answered y checking slots or stating simple names or brands

arrangement of questions should e carefully planned

limit questions to essential information

Two Major Ways of Selecting Sample

Units from a Population

known as simple random sampling

picking things at random means picking things without bias or any predetermined choice

A. Probability Sampling

Ways of Drawing Sample Units at

Random

numbers assigned to each member of the population

1. Lottery Sampling

the selection of each member of the population is left adequately to chance, and every member of the population has an equal chance of being chosen

2. Table of Random Numbers

used when there are only few sample units to be selected

a. Direct Selection Method

Two Ways of Conducting the Remainder Method:

b. Remainder Method

1. When the number taken from the table of random numbers is subtracted from the upper limit within which this number falls, the remainder is the sample unit.

b. Remainder Method

2. When the upper limit of the set is subtracted from the number taken from the random tables and yields a number equal or less than N, the remainder is the sample unit.

b. Remainder Method

used when the population is too large to handle

B. Restricted Random Sampling

TYPES OF RESTRICTED RANDOM

SAMPLING

units are obtained by drawing every nth element of the population

1. Systematic Sampling

nth = Total no. of elements in the population Desired Sample Sizenth = N n

ex: population 50,000; sample size 100; margin of error 10%. Determine the nth term

nth = N n

= 50,000/100= 500

a. Stratified Sampling the population is divided into groups based on homogeneity

the distribution of units is proportional to the total number of units in each stratum

Types of Systematic Sampling

1) Identify N and its different strata

2) Divide the members of the population into percent shares

3) multiply each percent share by n sample units to get the actual number of sample units for each stratum

steps:

Example

population is 50,000sample units is 100margin of error is 10 %25,000 belong to high income group10,000 belong to middle income group15,000 belong to low income group

strata

STRATA NUMBER OF POPULATION

High-income group 25,000Middle-income group 10,000

Low-income group 15,000TOTAL 50,000

DISTRIBUTION OF POPULATION

STRATA NUMBER OF POPULATION

PERCENT SHARE(N/n)

High-income group

25,000/50,000

Middle-income group

10,000/50,000

Low-income group

15,000/50,000

TOTAL 50,000

PERCENT SHARE OF EACH STRATUM

0.5 or 50%

0.2 or 20%

0.3 or 30%

100%

STRATA Sample size times the percent share

Number of Sample Units

High-income group

100 x 0.5

Middle-income group

100 x 0.2

Low-income group

100 x 0.3

TOTAL

DISTRIBUTION OF SAMPLE UNITS

50

20

30

100

b. Cluster Sampling an area sample: geographical basis

districts or blocksheterogeneous groups

Types of Systematic Sampling

c. Multi-Stage Sampling uses several stages in getting the samples from the general population

useful in conducting a nationwide survey

Types of Systematic Sampling

not all members of the population are given equal chances: sample

non-probability samplingchooses its sampleused in market research or employment department

2. Non-Random Sampling

a. Purposive Sampling choosing samples based on a criteria and rules by the researcher

Types of Non-Random Sampling

b. Quota Sampling the researcher limits the number of his samples based on the required number of subject under investigation

Types of Non-Random Sampling

c. Convenience Sampling the researcher conducts a study at his convenient time, preferred place or venue

Types of Non-Random Sampling