MKT 3340 (Marketing Research) Exam #2
Final Exam Review
Population - Answers -A population is all cases that meet designated specifications for
membership in the group
Census - Answers -A census is defined as an accounting of everyone in the population.
Defining the Target Population - Answers -Researchers must be very clear and precise
in defining the target population
Example: Households in the city limits of Richardson, TX, with one or more children
under the age of 18 living at home
Sample - Answers -A sample is a subset of the population that should represent the
population.
Sampling Error - Answers -The sampling error is any error in a survey that occurs
because a sample is used
- usually caused by method of sample selection or sample size
The difference between results obtained from a sample and results that would have
been obtained had information been gathered from or about every member of the
population
- sampling error is decreased by increasing sample size
0 can be estimated (assuming probability sample)
Sample frame - Answers -A sample frame is some master list of all the members of the
population
Parameter - Answers -A characteristic or measure of a population
If it were possible to take measures from all members of a population without error, a
true value of a parameter could be determined
Statistic - Answers -A characteristic or measure of a sample
Statistics are calculated from sample data and used to estimate population parameters
Why use samples? - Answers -Marketing researchers, when collecting primary data,
typically rely on a sample because:
- taking a census of everyone in a market is time consuming
- very costly
, - and often leads to measurement errors
Using a sample can generate results that generalize the entire population
How to select a representative sample - Answers -How we draw a sample (the sample
plan), determines whether a sample is representative
There are two major types of sampling plans: probability and nonprobability sampling
plans
Probability Sampling Methods - Answers -A random sample is one in which every
member of the population has an equal chance, or probability, of being selected into the
sample
Sample methods that embody random sampling are often termed probability sampling
methods, because the chance of selection can be expressed as a probability
There are four probability sampling methods:
- simple random sampling
- systematic sampling
- stratified sampling
- cluster sampling
Simple Random Sampling - Answers -Used when the population is small and can easily
be counted or even when the population is large but is contained in an electronic
database which can automatically "draw" a random sample
Probability of selection = sample size/population size
With simple random sampling the probability of being selected into the sample is
"known" and equal for all members of the population
Example: put all names into a "hat" and stir them and blindly draw names out
Procedures for drawing simple random samples - Answers -1. Select a suitable
sampling frame
2. Assign each element a number from 1 to N (population size)
3. Generate n (sample size) different random numbers between 1 and N. This can be
done using a software package or using a table of simple random numbers
4. The numbers generated denote the elements that should be included in the sample
Members selected should be representative of all the members of the population.
Randomly Selecting Samples - Answers -Random Digit Dialing (RDD) is a method of
randomly generating numbers to represent telephone numbers
- this approach is used in telephone surveys to overcome the problems of unlisted and
new telephone numbesr
Final Exam Review
Population - Answers -A population is all cases that meet designated specifications for
membership in the group
Census - Answers -A census is defined as an accounting of everyone in the population.
Defining the Target Population - Answers -Researchers must be very clear and precise
in defining the target population
Example: Households in the city limits of Richardson, TX, with one or more children
under the age of 18 living at home
Sample - Answers -A sample is a subset of the population that should represent the
population.
Sampling Error - Answers -The sampling error is any error in a survey that occurs
because a sample is used
- usually caused by method of sample selection or sample size
The difference between results obtained from a sample and results that would have
been obtained had information been gathered from or about every member of the
population
- sampling error is decreased by increasing sample size
0 can be estimated (assuming probability sample)
Sample frame - Answers -A sample frame is some master list of all the members of the
population
Parameter - Answers -A characteristic or measure of a population
If it were possible to take measures from all members of a population without error, a
true value of a parameter could be determined
Statistic - Answers -A characteristic or measure of a sample
Statistics are calculated from sample data and used to estimate population parameters
Why use samples? - Answers -Marketing researchers, when collecting primary data,
typically rely on a sample because:
- taking a census of everyone in a market is time consuming
- very costly
, - and often leads to measurement errors
Using a sample can generate results that generalize the entire population
How to select a representative sample - Answers -How we draw a sample (the sample
plan), determines whether a sample is representative
There are two major types of sampling plans: probability and nonprobability sampling
plans
Probability Sampling Methods - Answers -A random sample is one in which every
member of the population has an equal chance, or probability, of being selected into the
sample
Sample methods that embody random sampling are often termed probability sampling
methods, because the chance of selection can be expressed as a probability
There are four probability sampling methods:
- simple random sampling
- systematic sampling
- stratified sampling
- cluster sampling
Simple Random Sampling - Answers -Used when the population is small and can easily
be counted or even when the population is large but is contained in an electronic
database which can automatically "draw" a random sample
Probability of selection = sample size/population size
With simple random sampling the probability of being selected into the sample is
"known" and equal for all members of the population
Example: put all names into a "hat" and stir them and blindly draw names out
Procedures for drawing simple random samples - Answers -1. Select a suitable
sampling frame
2. Assign each element a number from 1 to N (population size)
3. Generate n (sample size) different random numbers between 1 and N. This can be
done using a software package or using a table of simple random numbers
4. The numbers generated denote the elements that should be included in the sample
Members selected should be representative of all the members of the population.
Randomly Selecting Samples - Answers -Random Digit Dialing (RDD) is a method of
randomly generating numbers to represent telephone numbers
- this approach is used in telephone surveys to overcome the problems of unlisted and
new telephone numbesr
