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Business Research Methods
EMBA-1
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Business Research Methods
EMBA-1
Lecture – 7
Sample Design and Sampling Procedure
Determination of Sample Size: A review of Statistical theory
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Business Research Methods
EMBA-1
Sample Design and Sampling Procedure
Business Research Methods
EMBA-1
Pragmatic reasons
Accurate and reliable results
Destruction of test units
Why Sampling
Budget and time constraints. Often,
Not be possible to contact the whole population
Samples are accurate only when researchers have taken care.
A sample may be more accurate than a census.
In a census there is greater likelihood of non-sampling errors.
A small, well-trained, closely supervised group may do a more accurate job
At times testing require the destruction
If all tested that way, there would be no product left after testing.
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Business Research Methods
EMBA-1Stages in Sample Selection
Define the target population
Select a sample frame
Determine if a probability or non probability sample will be chosen
Plan procedure for selecting sampling units
Determine sample size
Select actual sampling units
Conduct fieldwork
Business Research Methods
EMBA-1Types of Sampling
Non Probability Sampling
Probability Sampling
Business Research Methods
EMBA-1
Convenience sampling
Judgment sampling
Quota sampling
Snowball sampling
Non Probability Sampling
Business Research Methods
EMBA-1
Simple random sampling
Systematic sampling
Stratified sampling
Proportional versus disproportional strata
Cluster sampling
Probability Sampling
Business Research Methods
EMBA-1Internet Sampling
Internet surveys allow researchers to rapidly reach a large sample. This is both an advantage and a disadvantage.
Sample size requirements can be met overnight or in some cases almost instantaneously.
A major disadvantage of Internet surveys is the lack of computer ownership and Internet access among certain segments of the population.
Business Research Methods
EMBA-1
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Business Research Methods
EMBA-1
Determination of Sample Size: A review of Statistical theory
Business Research Methods
EMBA-1
Descriptive Statistics
Inferential statistics
Sample Statistics
Population parameters
Basic Terminology
Statistics used to describe or summarize information about population or sample
Statistics used to make inferences or judgments about a population on the basis of a sample
Variables in a population or measured characteristics of a population
Variables in a sample or measures computed from sample data
Business Research Methods
EMBA-1
Frequency Distribution
Percentage distribution
Central Tendency
Measure of Dispersion
Normal Distribution
Making the Data Useable
Business Research Methods
EMBA-1
Frequency Distribution
Percentage distribution
Central Tendency
Measure of Dispersion
Normal Distribution
Making the Data Useable
Business Research Methods
EMBA-1
Frequency Distribution
Percentage distribution
Central Tendency
Measure of Dispersion
Normal Distribution
Making the Data Useable
Mean
Median
Mode
Business Research Methods
EMBA-1
Frequency Distribution
Percentage distribution
Central Tendency
Measure of Dispersion
Normal Distribution
Making the Data Useable
Range
Deviation Scores
Variance
Standard Deviation
Business Research Methods
EMBA-1
Frequency Distribution
Percentage distribution
Central Tendency
Measure of Dispersion
Normal Distribution
Making the Data Useable
Z =Value of X – Mean
Standard Deviation
X
MeanZ
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Business Research Methods
EMBA-1
error sampling small aX
Some Formula
Xcl SZ ERRORSAMPLING SMALL
XclSZ E E X2
Ezs
nn
SSx
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Business Research Methods
EMBA-1Factors of Sample Size
• Variance (standard deviation)
• Magnitude of error
• Confidence level
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Business Research Methods
EMBA-1
Sample Size Formula - Example
Suppose a survey researcher, studying expenditures on lipstick, wishes to have a 95 percent confident level (Z) and a range of error (E) of less than $2.00. The estimate of the standard deviation is $29.00.
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Business Research Methods
EMBA-1
2
E
zsn
2
00.2
00.2996.1
2
00.2
84.56
242.28 808
Sample Size Formula - Example
Suppose a survey researcher, studying expenditures on lipstick, wishes to have a 95 percent confident level (Z) and a range of error (E) of less than $2.00. The estimate of the standard deviation is $29.00.
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Business Research Methods
EMBA-1
Suppose, in the same example as the one before, the range of error (E) is acceptable at $4.00, sample size is reduced.
Sample Size Formula - Example
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Business Research Methods
EMBA-1
2
E
zsn
2
00.4
00.2996.1
2
00.4
84.56
221.14 202
Sample Size Formula - Example
Suppose, in the same example as the one before, the range of error (E) is acceptable at $4.00, sample size is reduced.
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Business Research Methods
EMBA-1
99% Confidence
Calculating Sample Size
1389
265.372
253.74
2
2)29)(57.2(n
2
347 6325.18 2
453.74
2
4)29)(57.2(n
2
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Business Research Methods
EMBA-1
npp
or
npq
ps
)1(
Standard Error of the Proportion
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Business Research Methods
EMBA-1
pclSZp
Confidence Interval for a Proportion
2
2
EpqZ
n
Confidence Interval
XclSZ E
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Business Research Methods
EMBA-1
2
2
Epqz
n
Where: n = Number of items in samples
Z2 = The square of the confidence interval in standard error units.
p = Estimated proportion of success
q = (1-p) or estimated the proportion of failures
E2 = The square of the maximum allowance for error between the true proportion and sample proportion or zsp squared.
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Business Research Methods
EMBA-1
Calculating Sample Size at the 95% Confidence Level
753001225.
922.
001225
)24)(.8416.3(
)035( .)4)(.6(.)96 1. (
n4.q
6.p2
2
As given:
Suppose a simple random sample shows 60% of the respondents (p) recognize the name. Researcher wishes to estimate with 95% confidence (I.e., Z=1.96) that the allowance for sampling error is not more that 3.5% (E).
Solution:
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Business Research Methods
EMBA-1
? Any Question?
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Business Research Methods
EMBA-1
Thanks for your
contribution
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Business Research Methods
EMBA-1Assignment
Gp Assignment
Case-23: Business Forum Industry
Submission date is 17th Jul
Submission time: 0630 p.m.
Selected person will present for 10 mins
Discussion to focus, how the data were analyzed
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Business Research Methods
EMBA-1
See You Next Week
Business Research Methods
EMBA-1Stages in Sampling
What is the relevant population? In many cases this is not a difficult question, but in other cases, the decision may be a difficult one.
Answering questions about the crucial characteristics of the population is the usual technique for defining the target population. The question “Whom do we want to talk to?” must be answered.
Target population
Sample frame
Sampling Method Choice
Procedure for sampling units
Determine sample size
Actual sampling units
Conduct fieldwork
Business Research Methods
EMBA-1Stages in Sampling
A sampling frame is a list of elements from which the sample may be drawn.
The sampling frame is also called the working population, because it provides the list that can be operationally worked with.
Target population
Sample frame
Sampling Method Choice
Procedure for sampling units
Determine sample size
Actual sampling units
Conduct fieldwork
Business Research Methods
EMBA-1Stages in Sampling
Probability or Non probability sample
Target population
Sample frame
Sampling Method Choice
Procedure for sampling units
Determine sample size
Actual sampling units
Conduct fieldwork
In probability sampling every element in the population has a known nonzero probability of selection; each member of the population has an equal probability of being selected.
In nonprobability sampling, the probability of any particular member of the population being chosen is unknown. Nevertheless, there are occasions when the nonprobability samples are best suited for the researcher’s purpose.
Business Research Methods
EMBA-1Stages in Sampling
The sampling unit is a single element or group of elements subject to selection in the sample.
If the target population has been divided into stages, the term primary sampling unit (PSU), secondary sampling units, or tertiary sampling units is used .
When there is no list of population elements, the sampling unit is generally something other than the population element. For example, in a random digit dialing study the sampling unit will be telephone numbers.
Target population
Sample frame
Sampling Method Choice
Procedure for sampling units
Determine sample size
Actual sampling units
Conduct fieldwork
Business Research Methods
EMBA-1
Convenience sampling
Judgment sampling
Quota sampling
Snowball sampling
Non Probability Sampling
Researchers generally use convenience samples to obtain a large number of completed questionnaires quickly and economically
Convenience samples are best utilized for exploratory research when additional research will subsequently be conducted with a probability sample
Business Research Methods
EMBA-1
Convenience sampling
Judgment sampling
Quota sampling
Snowball sampling
Non Probability Sampling
Judgment or purposive sampling is a nonprobability technique in which an experienced individual selects the sample upon his or her judgment about some appropriate characteristic required of the sample members
Business Research Methods
EMBA-1
Convenience sampling
Judgment sampling
Quota sampling
Snowball sampling
Non Probability Sampling
The purpose of quota sampling is to ensure that the various subgroups in a population are represented on pertinent sample characteristics to the exact extent that the investigators desire
Business Research Methods
EMBA-1
Convenience sampling
Judgment sampling
Quota sampling
Snowball sampling
Non Probability Sampling
Snowball sampling refers to a variety of procedures in which initial respondents are selected by probability methods, but additional respondents are then obtained from information provided by the initial respondents. This technique is used to locate members of rare populations by referrals.
Business Research Methods
EMBA-1
Simple random sampling
Systematic sampling
Stratified sampling
Proportional versus disproportional strata
Cluster sampling
Probability Sampling
A simple random sample is a sampling procedure that assures that each element in the population will have an equal chance of being included in the sample
Business Research Methods
EMBA-1
Simple random sampling
Systematic sampling
Stratified sampling
Proportional versus disproportional strata
Cluster sampling
Probability Sampling
Systematic sampling is extremely simple: An initial starting point is selected by a random process; then every nth number on the list is selected.
Business Research Methods
EMBA-1
Simple random sampling
Systematic sampling
Stratified sampling
Proportional versus disproportional strata
Cluster sampling
Probability Sampling
In stratified sampling, a subsample is drawn utilizing a simple random sample within each stratum. The reason for taking a stratified sample is to have a more efficient sample than could be taken on the basis of simple random sampling
Business Research Methods
EMBA-1
Simple random sampling
Systematic sampling Stratified sampling Proportional versus
disproportional strata
Cluster sampling
Probability Sampling
If the number of sampling units from each stratum is in proportion to the relative population size of the stratum, the sample is a proportional stratified sample.
Business Research Methods
EMBA-1
Simple random sampling
Systematic sampling
Stratified sampling
Proportional versus disproportional strata
Cluster sampling
Probability Sampling
The purpose of cluster sampling is to sample economically while retaining the characteristics of a probability sample. In a cluster sample, the primary sampling unit is no, longer the individual element in the population (for example, grocery stores) but a larger cluster of elements located in proximity to one another (for example, cities). The area sample is the most popular type of cluster sample.