Marketing Research Ch. 6

Steps in Developing a Sampling Plan

-A sampling plan is the blueprint ensuring the data is representative of the defined population: •Step 1: Define the target population •Step 2: Select the data collection method •Step 3: Identify the sampling frame(s) needed •Step 4: Select the appropriate sampling method •Step 5: Determine necessary sample size and overall contact rates •Step 6: Create an operating plan for selecting the sampling units •Step 7: Execute the operational plan

Sampling error

-Any bias resulting from mistakes in either the selection process for the prospective sampling units, or in determining the sample size -Random sampling error occurs as chance variations in the selection of sampling units •Sampling units are only reliable estimates of the target population -Sampling error can be reduced by increasing the size of the sample

Central Limit Theorem (CLT)

-Describes the theoretical characteristics of a sample population •The sampling distribution of the mean (¯x) or the percentage value (p) derived from a simple random sample will be normally distributed, if the sample size is sufficiently large - when n is > or = 30 •The (¯x) of the random sample fluctuates around the true population mean (µ) with a standard error of σ∕√n and a normal sampling distribution •There is a high probability the mean of any sample (¯x) taken from the target population will be a close approximation of the true target population mean (µ), as you increase the size of the sample (n) -states that the sampling distribution derived from a simple random sample will be approximately normally distributed

Cluster sampling

-Divides sampling units into mutually exclusive and collectively exhaustive subpopulations called clusters •The sampling units are selected using either simple random sampling or a census within a defined cluster

Convenience Sampling

-Draws samples at the convenience of the researcher -Convenience sampling enables many respondents be interviewed in a short time period •Commonly used in the early stages of research and pretesting of questionnaires -Using convenience samples to develop constructs and scales are risky -The data is not generalizable to the defined target population -The representativeness of the sample cannot be measured because sampling error estimates cannot be calculated

Probability sampling

-Each sampling unit in the defined target population has a known probability of being selected for the sample -Rules ensure the following: •Unbiased selection of the sampling units •Proper sample representation of the defined target population -Results using probability sampling designs can be generalized to the target population within a specified margin of error

Determining Nonprobability Sample Sizes

-Formulas cannot be used for nonprobability samples •Usually a subjective, intuitive judgment by the research •Sampling units should not be used to make statistical inferences about the true population parameters -Sample sizes are often determined using fewer formal approaches •Such as budget or previous studies' results •Consideration is given to the number of subgroups examined and the minimum sample size per subgroup needed to draw conclusions -Decisions on approach, or combination of approaches, requires judgment of both research experts and managers to select the best alternative

Quota Sampling

-Involves the selection of prospective participants according to pre-specified quotas -The purpose is to assure that pre-specified subgroups are represented -Research panel samples are considered quota sampling -Major advantages are the sample contains subgroups in the proportions desired by the researchers and reduces selection bias by field workers -A limitation is that the success of the study is dependent on subjective decisions made by researchers

Identify the features of nonsampling error

-It can occur at any stage of the research process -It occurs due to incorrect question/scale measurements

Which of the following are advantages of quota sampling?

-It ensures the identification and inclusion of appropriate subgroups in a survey -The sample generated consists of specific subgroups in the proportions desired by researchers

Which of the following tasks can be performed by a researcher who understands the basics of the central limit theorem (CLT)?

-Obtaining sample statistics from a random sample that work as accurate estimates of the target population's parameters -Drawing representative samples from any target population

Nonsampling error

-Occurs regardless of whether a sample or census is used •For example, the target population may be inaccurately defined causing population frame error -The broader the study, the greater the chance for nonsampling errors -There is no way to assess the impact of nonsampling errors on data quality -Nonsampling errors are related to the accuracy of the data, sampling errors relate to the representativeness of the sample to the defined target population

Judgment Sampling

-Or purposive sampling, respondents are selected because the researcher believes they meet the requirements of the study -If the researcher judgment is correct, the sample generated by judgment sampling will be better than one generated by convenience sampling -However, the representativeness of the sample cannot be measured

Snowball Sampling

-Or referral sampling, a set of respondents is chosen, and they help the researcher identify additional respondents -Snowball sampling is typically used when: •The defined target population is small and unique •Or, when compiling a complete list of sampling units is very difficult -This method identifies respondents who are members of small, uniquely defined, hard to reach target populations -Most useful in qualitative research -Snowball sampling allows bias to enter the study

Systematic random sampling

-Requires the target population be ordered in some way - inexpensive and can be done quickly •Step 1: Obtain a list of potential sampling units containing an acceptable frame of the target population elements •Step 2: Determine the total number of sampling units making up the list of the defined target population's elements and the desired sample size •Step 3: Compute the needed skip interval by dividing the number of potential sampling units on the list by the desired sample size •Step 4: Using a random number generation system, randomly determine the starting point to sample the list of names •Step 5: With a name as the first sample unit, apply the skip interval to determine the remaining names that should be included in the sample

Value of Sampling

-Sampling is the selection of a small number of elements from a larger defined target group of elements -Sampling is often used when it is impossible or unreasonable to conduct a census -Sampling is less time consuming and less costly than a census

Stratified random sampling

-Separates the target population into strata and selects samples from each strata - requires three basic steps: •Step 1: Divide the target population into homogenous subgroups or strata •Step 2: Draw random samples from each stratum •Step 3: Combine the samples into a single sample of the target population

Sampling units

-Target population elements available to be used during the sampling process •For example, Mazda includes the elements of adult purchases of automobiles and a sampling unit of new Mazda purchasers from January to September 2021

Identify the true statements about the factors that play an important role in determining sample sizes with probability designs

-The higher the level of confidence desired, the larger the sample size required -The greater the variability in the data being estimated, the larger the sample size required

Sample Size and Accuracy

-The larger the random sample is, the more accurate it is, meaning the less margin of sample error it has -There is a relationship between sample size and accuracy of the sample

Which of the following are factors that play a significant role in determining sample sizes with probability designs?

-The level of confidence desired in the sample estimate -The population variance -The degree of precision desired in estimating the population characteristic

Nonprobability Sampling

-The probability of selecting each sampling unit in not known -Selection of the sampling unit is based on researcher judgment and may or may not represent the target population •Depends on the sampling approach and how well the researcher executes the selection activities

Identify the tasks that can be performed by a researcher who understands the basics of the central limit theorem (CLT)

-The researcher can more accurately assess the validity and reliability of scale measurements and constructs -The researcher can draw one random sample, instead of many samples, and thus reduce data collection costs

Sampling Frame

-The researcher develops a list of all eligible sampling units, referred to as a sampling frame -Common sources of sampling frames are lists of registered voters and customers lists from magazine publishers or credit card companies -There are also specialized commercial companies that sell databases of potential population elements -Regardless of the source, it is often difficult and expensive to obtain accurate, representative, and current sampling frames

Identify true statements about research panel samples

-They are quota samples drawn based on behavioral patterns, demographic quotas, and similar information -They are nonprobability samples but are considered representative of the target population

When is snowball sampling typically used?

-When the defined target population is unique and small -When it is very difficult to compile a complete list of sampling units

Arrange the steps involved in drawing a stratified random sample in the order of their occurrence (From first to last)

1. Segregating a target population into homogeneous subgroups or strata 2. Deriving random samples from each stratum 3. Merging the samples from each stratum into a single sample of the target population

A researcher wants to use systematic random sampling to draw a sample of 300 from a target population of 1,500. In this scenario, the skip interval will be _______

5

Identify a difficulty associated with detecting sampling errors in a research study

A census is rarely conducted in survey research

Which of the following is an example of convenience sampling?

A consumer psychology professor interviews his students to measure the success of a new advertising campaign

Identify an advantage of convenience sampling

A large number of respondents can be interviewed in a relatively short time

Factors Underlying Sampling Theory

A major goal of researching small, representative samples is that the results will help estimate what true population parameters are within a certain degree of confidence

Identify a true statement about determining the sample size for nonprobability samples

A researcher makes subjective, intuitive judgments based on either past studies or the amount of resources available when deriving samples

Which of the following is an example of area sampling?

A researcher segregates participants into subgroups based on where they live and then interviews participants from each subgroup

In systematic random sampling, sampling units are selected _____

According to their position using a skip interval

In systematic random sampling, sampling units are selected ________

According to their position using a skip interval

A true statement about sampling frames is that _____

Accurate, representative, and current sampling frames are difficult and expensive to obtain

A true statement about sampling frames is that _______

Accurate, representative, and current sampling frames are difficult and expensive to obtain

Population

An identifiable group of elements of interest to the researcher and pertinent to the information problem

A form of cluster sampling in which the clusters are formed by geographic designations is called _______

Area sampling

n

Calculated sample size determined by the formula used to calculate the sample size for a large population

A research study that includes data about every member of a defined target population is called a _______

Census

A probability sampling method in which the sampling units are divided into mutually exclusive and collectively exhaustive subpopulations is called _______

Cluster sampling

Area sampling

Clusters are formed by geographic regions

Sampling is often used when _______

Conducting a census is impossible or unreasonable

A nonprobability sampling method in which samples are drawn at the convenience of the researcher is called ______

Convenience sampling

The complete set of elements identified for investigation based on the objectives of a research project is called a _________

Defined target population

The primary difficulty researchers encounter when using stratified sampling is _____

Determining the basis for stratifying the target population

Proportionately stratified sampling

Each stratum is dependent on its relative size to the population

Disproportionately stratified sampling

Each stratum is independent on its relative size of the population

Proportionately stratified sampling

Each stratum's sample size is dependent on that stratum's size relative to the defined target population

Disproportionately stratified sampling

Each stratum's sample size is independent of that stratum's proportion of the total defined target population

True or false: Changing respondent behaviors disallow multisource sampling

False

True or false: Nonprobability sampling results are often used by researchers to make statistical inferences about the true population parameters

False

True or false: The basic logic underlying optimal allocation is that the greater the heterogeneity of a stratum, the fewer the units that would be selected to accurately estimate the true population parameter for that subgroup

False

Proportionately stratified sampling

In this sampling method, the strata that make up a larger percentage of the target population are sampled more heavily

Systematic random sampling has become a popular method of drawing samples in research practices because _____

It can be done relatively quickly and is less expensive than simple random sampling

Systematic random sampling has become a popular method of drawing samples in research practices because ______

It can be done relatively quickly and is less expensive than simple random sampling

Which of the following is a disadvantage of systematic random sampling?

It involves the possibility of hidden patterns in the list of prospective participants' names that create bias

The population variance

It is a measure of the dispersion of the population, and its square root, referred to as the population standard deviation

Systematic random sampling is frequently used because ______

It is a relatively easy way to draw a sample while ensuring randomness

Identify a disadvantage of simple random sampling

It is difficult to obtain a precise and complete listing of the target population elements

Identify a true statement about cluster sampling

It is easy to implement and is cost-effective

Identify a disadvantage of a census

It is more time-consuming and expensive than sampling

Which of the following is an advantage of simple random sampling?

It produces unbiased estimates of the characteristics of the target population

The degree of precision desired in estimating the population characteristic

It refers to the acceptable amount of error in a sample estimate

The confidence level desired in an estimate

It refers to the certainty that the true value of the data being estimated falls within the precision range that has been selected

A nonprobability sampling method in which participants are selected according to a researcher's belief that they will meet the requirements of a study are called ______

Judgement or purposive sampling

The selection of sampling units in nonprobability sampling is based on the ______

Knowledge or intuitive judgment of a researcher

________ is sometimes used in stratified random sampling when no single source can generate a large or low incidence sample

Multisource sampling

Sampling designs in which the probability of selection of each sampling unit is not known are called ______

Nonprobability sampling

A bias that occurs in a research study regardless of whether a sample or census is used is called ______

Nonsampling error

In _______ method, consideration is given to the relative size of the stratum as well as the variability within the stratum to determine the necessary sample size of each stratum

Optimal allocation sampling

An identifiable set of elements of interest to a researcher and pertinent to the information problem is called a _______

Population

N

Population size

In ______, each sampling unit in the defined target population has a known possibility of being selected for the sample

Probability sampling

A nonprobability sampling method in which participants are selected according to prespecified quotas regarding demographics, attitudes, behaviors, or some other criteria is called ______

Quota sampling

Research panel samples are most often considered _____

Quota sampling

In the context of stratified random sampling, which of the following is true of dividing a target population into homogeneous strata?

Researchers have the opportunity to study each stratum and compare strata

_________ refers to the selection of a small number of elements from a larger defined target group of elements and expecting that the information gathered from the small group will allow judgments to be made about the larger group

Sampling

Any type of bias that is attributable to mistakes in either drawing a sample or determining the sample size is called ________

Sampling error

Which of the following is true of detecting sampling errors in a research study?

Sampling error determination can be done only after a sample is drawn and data collection is completed

A list of all eligible sampling units that are developed by a researcher is called a ________

Sampling frame

The target population elements available for selection during the sampling process are called ______

Sampling units

Unlike stratified random sampling, the sampling units in cluster sampling are _____

Segregated into mutually exclusive and collectively exhaustive subpopulations

Unlike stratified random sampling, the sampling units in cluster sampling are ______

Segregated into mutually exclusive and collectively exhaustive subpopulations

A marketing researcher wants to draw a sample of 30 participants out of the 100 potential participants who are present. The researcher writes each participant's name on a separate, identical piece of paper and places all the names in a bowl. She then proceeds to pick names arbitrarily until she picks 30 participants. The scenario given above is an example of ______

Simple random sampling

A probability sampling procedure in which every sampling unit has a known and equal chance of being selected is called _______

Simple random sampling

_______ or referral sampling is a nonprobability sampling method in which a set of respondents is chosen by a researcher, and they help the researcher identify additional people to be included in the study

Snowball sampling

______ involves the separation of the target population into different groups and the selection of samples from each group

Stratified random sampling

In ______, a defined target population is ordered in some way, usually in the form of a taxpayer roll, customer list, or membership roster, and selected systematically

Systematic random sampling

Defined target population

The complete set of elements identified for investigation based on the objectives of the research project

Which of the following is true of convenience sampling?

The data are not generalizable to the members of the defined target population

Which of the following is true of cluster sampling?

The homogeneous nature of clusters leads to less precise sample estimates

A marketing researcher hired by an electronics company wants to identify the impact of the new features of the company's toasters on its sales. She identifies the names of the people who bought the toasters from January 2013 to January 2014 and sends them a survey. The sampling unit in the scenario given above is ________

The people who bought the toasters

Which of the following is a feature of judgment sampling?

The representativeness of the sample cannot be measured

Identify a rule that is followed when selecting members from a population for the inclusion in probability sampling

The selection of the sampling units should be unbiased

An inherent limitation of quota sampling is that _____

The success of a study is dependent on subjective decisions made by researchers

Random sampling error occurs because ______

There can be chance variations in the selection of sampling units

Disproportionately stratified sampling

This sampling method is used when stratification of the target population produces sample sizes for subgroups that differ from their relative importance to a study

Sample Size Formula

To calculate the proper size for a survey, only three items are required: 1.The variability believed to be in the population, 2.The acceptable margin of sample error, and 3.The level of confidence required in your estimates of the population values

Identify a purpose of quota sampling

To ensure the representation of prespecified subgroups of the population

Given X = Defined target population list size, and Y = Desired sample size, identify the formula for skip interval that is used in systematic random sampling

X/Y

Disadvantages of Cluster Sampling

•A primary disadvantage is that the clusters often are homogeneous, resulting in less precise sample estimates •Another concern is the appropriateness of the designated cluster factor used to identify the sampling units within clusters •Caution must be used in selecting the factor to determine clusters in area sampling situations

Advantages of Stratified Random Sampling

•Assures representativeness in the sample •Provides an opportunity to study stratum and make comparisons between strata •Allows the ability to make estimates for the target population •With the expectation of greater precision and less error

Advantages of Cluster Sampling

•Cluster sampling is widely used due to cost-effectiveness and ease of implementation

Advantages of Systematic Random Sampling

•Frequently used as an easy way to draw a sample while ensuring randomness •The availability of lists and the shorter time required to draw a sample makes this an attractive, economical method

Determining the Appropriate Sampling Design

•Research Objectives •Degree of Accuracy •Resources •Time Frame •Knowledge of Target Population •Scope of Research •Statistical Analysis Needed

Disadvantages of Systematic Random Sampling

•The greatest weakness is the possibility of hidden patterns in the list of names, creating bias •The number of sampling units in the target population must be known •When the size of the target population is large or unknown, identifying the number of units is difficult, and estimates may not be accurate

Disadvantages of Stratified Random Sampling

•The primary difficulty encountered is determining the basis for stratifying •Inclusion of irrelevant strata will waste time and money without providing meaningful results

Disadvantages of Simple Random Sampling

•The primary disadvantage is the difficulty of obtaining a complete and accurate listing of the target population elements •Simple random sampling requires all sampling units be identified •This works best for small populations where accurate lists are available

Advantages of Simple Random Sampling

•The technique is easily understood •Results are generalized with margin of error •They produce unbiased estimates of the population's characteristics •This method results in a valid representation of the defined target population