Sample Design And Collection Of Data Flashcards
those which are collected afresh and for the first time, and thus happen to be original in character
primary data
(i) observation method,
(ii) interview method,
(iii) through questionnaires,
(iv) through schedules,
(a) warranty cards
(b) distributor audits
(c) pantry audits
(d) consumer panels
(e) using mechanical devices
(f) through projective techniques
(g) depth interviews
(h) content analysis
primary data collection
those which have already been collected by someone else and which have already been passed through the statistical process
secondary data
(a) various publications of the central, state are local governments
(b) various publications of foreign governments or of international bodies and their subsidiary organizations
(c) technical and trade journals
(d) books, magazines and newspapers
(e) reports and publications of various associations connected with business and industry, banks, stock exchanges, etc
(f) reports prepared by research scholars, universities, economists, etc. in different fields
(g) public records and statistics, historical documents, and other sources of published information
Published secondary data collection
found in diaries, letters, unpublished biographies and autobiographies
available with scholars and research workers, trade associations, labour bureaus and other public/ private individuals and organisations
Unpublished secondary data collection
Data is gathered indirectly
Questionnaire Method
No face to face contact between two
Questionnaire Method
Interviewer should have the general knowledge of the topic
Questionnaire Method
Interviewee will hesitate to write it
Questionnaire Method
get written information only
Questionnaire Method
Data is gathered directly
Interview Method
There is face to face contact between interviewer and interviewee
Interview Method
Skillful interviewer is needed
Interview Method
Some confidential information can also be obtained
Interview Method
get written and oral both type of information
Interview Method
also known as deliberate sampling, purposive sampling and judgement sampling
Non-probability sampling
items for the sample are selected deliberately by the researcher; his choice concerning the items remains supreme
Non-probability sampling
The investigator may select a sample which shall yield results favourable to his point of view
Non-probability sampling
there is always the danger of bias entering into this type of sampling technique
Non-probability sampling
There is no assurance that every element has some specifiable chance of being included
Non-probability sampling
Sampling error in this type of sampling cannot be estimated and the element of bias, great or small, is always there
Non-probability sampling
Conveniences ambling
Consecutive sampling
Quota sampling
Judgmental or Purposive sampling
Snowball sampling
Non probability sampling
also known as ‘random sampling’ or ‘chance sampling’
Probability sampling
every item of the universe has an equal chance of inclusion in
the sample
Probability sampling
method of sample selection which gives each possible sample combination an equal probability of being picked up and each item in the entire population to have an equal chance of being included in the sample
Probability sampling
Simple random sampling
Systematic sampling
Stratified random sampling
Multistage sampling
Multiphase sampling
Probability sampling
for homogenous population by lottery method, random number tables
Simple random sampling
for large, scattered and non homogenous population
Systematic sampling
for non homogenous population
Stratified random sampling
method of sampling which gives the probability that a sample is representative of population
Probability Sampling
generally used in fundamental research in which the purpose is to generalize the results
Probability Sampling
refers from the sample as well as the population
Probability Sampling
Every individual of the population has equal probability to be taken into the sample
Probability Sampling
representative of the population
Probability Sampling
observations (data) are used for the inferential purpose
Probability Sampling
Inferential or parametric statistics are used
Probability Sampling
absence of any idea of probability the method of sampling
Non-probability Sampling
generally used in action researches in which one studies a class without any generalization purpose
Non-probability Sampling
There is no idea of population
Non-probability Sampling
There is no probability of selecting any individual
Non-probability Sampling
has free distribution
Non-probability Sampling
observations are not used for generalization purpose
Non-probability Sampling
Non-inferential or non-parametric statistics are used
Non-probability Sampling
results from errors in the sampling procedures, and it cannot be reduced or eliminated by increasing the sample size
systematic bias
- Inappropriate sampling frame
- Defective measuring device
- Non-respondents
- Indeterminancy principle: Sometimes we find that individuals act differently when kept under observation than do when kept in non-observed situations
- Natural bias in the reporting of data
Causes of systematic bias
random variations in the sample estimates around the true population parameters
Sampling errors
occur randomly and are equally likely to be in either direction, their nature happens to be of compensatory type and the expected value of such errors happens to be equal to zero
Sampling errors
decreases with the increase in the size of the sample, and it happens to be of a smaller magnitude in case of homogeneous population
Sampling error
