Marketing Research Aaker, Kumar, Day Ninth Edition Instructor’s Presentation Slides
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Transcript Marketing Research Aaker, Kumar, Day Ninth Edition Instructor’s Presentation Slides
Marketing Research
Aaker, Kumar, Day
Ninth Edition
Instructor’s Presentation Slides
1
Chapter Fifteen
Sample Size and Statistical
Theory
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Determining the Sample Size
Ad Hoc Methods
Used when a person knows from experience what sample size to
adopt
Used when budgetary constraints dictate the size of the sample
Rule of Thumb
Sample should be large enough, so that when divided into groups,
each group will have a minimum sample size of 100 or more
If analysis involves comparison between subgroups, sample size
in each subgroup should be 20 to 50
Use disproportionate sampling if one of groups of population is
relatively small
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Determining the Sample Size (contd.)
Budget Constraints
Researcher must decide whether sample size dictated by budget
constraints allows a worthwhile study to be conducted
Comparative Studies
Find similar studies and use their sample sizes as a guide
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Factors Determining Sample Size
Number of groups and subgroups within the sample
Value of information in the study
Accuracy level required in results
Cost of sample
Variability of the population
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Population Characteristics/Parameters
Population Mean
Normally unknown
Determine value as closely as possible by taking a sample from
population
Population Variance
Measure of population dispersion
Based on degree to which a response differs from population average
response
The difference of each value from its mean is squared and averaged
across all responses
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Population Characteristics/ parameters
The population opinion on symphony starting time (7:30 P.M. on weekdays)
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Sample Characteristics/Statistics
Sample mean ( X ) is used to estimate the unknown population
mean
Example: A sample of symphony season-ticket holders
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Sample Characteristics/Statistics
(contd.)
Sample mean
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Sample Reliability
X will vary from sample to sample
As sample size (n) increases, variation in X will decrease
standard error of
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decreases as the sample size gets larger
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Sampling Distribution
Indicates probability of getting a particular sample mean
The normal distribution of X
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Sampling Distribution (contd.)
The effect of increasing sample size on the normal distribution of X
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Interval Estimation
X
varies from sample to sample
The difference between the sample mean ( X ) and the
population mean is the sampling error
Interval size depends on the confidence level the researcher
wants for the interval to contain the true population mean
If the population standard deviation is not known, it is
necessary to estimate it with the sample standard deviation
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Interval Estimation
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Interval Estimation (contd.)
Size of Interval Estimate depends on:
Confidence level
Population standard deviation
Sample size
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Sample Size Question
Size of the sampling error that is desired
Confidence level
Expected variance
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Determining the Population Standard Deviation
Options:
Use a sample standard deviation obtained from a previous
comparable survey or from a pilot survey
Estimate the sample standard deviation (s) subjectively
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Proportions
Population variance,
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Proportions (contd.)
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Sample Size Formulas
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Coefficient of Variation
Researcher may require the sample estimate be within plus
or minus G percentage points of the population value
Therefore,
D = Gm
The sample size formula may be written as:
C
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coefficient of variation
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Stratified Sampling
Useful when:
The population standard deviation differs by strata
The interview cost differs by strata
Optimal allocation of sampling budget to various strata:
Neyman’s solution
where
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Allocating Sample Size to Strata
where
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