Business Research Methods Summary Chapter 6, 7, 12, 13, 14 (Course: Research Methodology)
135 views 6 purchases
Course
Research Methodology for IB
Institution
Rijksuniversiteit Groningen (RuG)
Business Research Methods Summary Chapter 6, 7, 12, 13, 14.
Book by Blumberg, Cooper and Schindler.
International Business
Course: Research Methodology
Research Methodology
Summary
Chapter 6, 7, 12, 13, 14
6.1. Unit of analysis
- Unit of analysis: describes the level at which the research is performed and which objects
are researched.
- Choosing work groups as unit of analysis is likely to have the following implications:
o Depending on the number of work groups and applied pay systems in a firm, we may
still need to investigate more than one organization to achieve a sufficient number
of work groups.
o To obtain a sound measurement of job satisfaction, it may be necessary to question
individual employees in each work group selected.
- Choice of unit of analysis is related to:
o What is our research problem and what do we really want to answer?
o What do we need to measure to answer our research problem?
o What do we want to do with the results of the study? To whom do we address it in
our conclusions?
6.2. The nature of sampling
- Population element: subject on which measurement is being taken. Unit of analysis.
- Population: total collection of elements about which we wish to make inferences.
- Census: count of all elements in a population.
Why sample?
- Lower cost.
- Greater accuracy of results.
- Greater speed of data collection.
- Availability of population elements.
6.3. Sample versus census
- Two conditions are appropriate for a census study:
o Feasible when the population is small.
o Necessary when the elements are quite different from each other.
What makes a good sample?
- Accuracy: degree to which bias is absent from the sample.
o Accurate sample has no systematic variance: the variation in measures due to
influences that cause the scores to lean in one direction.
o Non-response can be systematic.
- Precision.
o Sampling error: influence of chance in drawing sampling members.
6.4. Types of sample design
Representation
- Probability sampling: based on the concept of random selection. Each element has a known
non-zero chance of selection.
- Non-probability sampling: arbitrary and subjective.
1
,Element selection
- Unrestricted sample: each sample element is drawn individually from the population at
large.
- Restricting sample: all other forms of sampling.
Probability sampling
- Simple random sample: simplest form of probability sampling, each population element has
a known and equal chance of selection.
6.5. Steps in sampling design
1. What is the relevant population?
- Without knowing the target market, the appropriate sampling population is not obvious.
2. What are the parameters of interest?
- Population parameters: summary descriptors of variables of interest in population.
- Sample statistics: descriptors of the relevant variables computed from sample data.
- Population proportion of incidence: equal to the number of elements in the population
belonging to the category of interest, divided by the total number of elements in the
population.
3. What is the sampling frame?
- Sampling frame: list of elements from which the sample is drawn.
- Often differs from theoretical population.
4. What is the type of sample?
- Interviewers or others should not be able to modify the selections made.
- Only those selected elements from the original sampling frame are included.
- Substitutions are excluded except as clearly specified and controlled according to
predetermined decision rules.
5. What sample size is needed?
- The greater the dispersion of variance within the population, the larger the sample must be
to provide estimation precision.
- The greater the desired precision of the estimate, the larger the sample must be.
- The greater the number of sub-groups of interest within a sample, the greater the sample
size; each sub-group must meet minimum sample size requirements.
- If the calculated sample size exceeds 5% of the population, sample size may be reduced
without sacrificing precision.
- Precision is measured by:
o Interval range in which they would expect to find the parameter estimate.
o Degree of confidence they wish to have in that estimate.
- Finite adjustment factor: size of the probability sample is only affected by the size of the
population when the sample size is large compared with the population.
6. How much will it cost?
- Cost considerations influence decisions about the size and type of sample, and also the data-
collection methods.
6.6. Complex probability sampling
- Simple random sampling is often impractical:
2
, o It requires a population list / sampling frame that is often not available.
o It fails to use all the information about a population, thus resulting in a design that
may be wasteful.
o It may be expensive to implement in terms of both time and money.
- Standard error of the mean: precision.
Systematic sampling
- Every kth element in the population is sampled.
1. Identify total number of elements in the population.
2. Identify sampling ratio (k = population size / sample size).
3. Identify random start.
4. Draw sample by choosing every kth entry.
- Possible periodicity in the population that parallels the sampling ratio.
- Monotonic trend in population elements, deal with this by:
o Randomizing the population before sampling.
o Changing the random start serval times in the sampling process.
o Replicating a selection of different samples.
Stratified sampling
- Stratified random sampling: the process by which the sample is constrained to include
elements from every segment.
- Three reasons why a researcher chooses a stratified random sample:
o Increase sample’s statistical efficiency.
o Provide adequate data for analyzing various sub-populations.
o Enable different research methods and procedures to be used in different strata.
- Ideal stratification would be based on primary variable under investigation.
- We will have done a good stratifying job if the stratification base maximizes the difference
among strata means and minimizes the within-stratum variances for the variables of major
concern.
- Size of strata samples is calculated with two pieces of information:
o How large the total sample should be.
o How the total sample should be allocated among strata.
- Proportionate stratified sampling: each stratum is properly represented so that the sample
drawn from it is proportionate to the stratum’s share of the total population:
o Higher statistical efficiency than simple random sample.
o Easier to carry out than other stratifying methods.
o Provides self-weighting sample; population mean or proportion can be estimated by
calculating mean or proportion of all sample cases, eliminating the weighting of
responses.
o Gain little in statistical efficiency if the strata measures and their variances are
similar for the major variables under study.
- Disproportionate stratified sampling: any stratification that departs from proportionate
relationship.
o In a given stratum, take a larger sample if the stratum is larger than other strata; the
stratum is more variable internally, and sampling is cheaper.
o If the differences in sampling costs of variances among strata are large,
disproportionate sampling is desirable.
- Process for drawing a stratified sample:
1. Determine variables to use for stratification.
2. Determine proportions of stratification variables in the population.
3
The benefits of buying summaries with Stuvia:
Guaranteed quality through customer reviews
Stuvia customers have reviewed more than 700,000 summaries. This how you know that you are buying the best documents.
Quick and easy check-out
You can quickly pay through EFT, credit card or Stuvia-credit for the summaries. There is no membership needed.
Focus on what matters
Your fellow students write the study notes themselves, which is why the documents are always reliable and up-to-date. This ensures you quickly get to the core!
Frequently asked questions
What do I get when I buy this document?
You get a PDF, available immediately after your purchase. The purchased document is accessible anytime, anywhere and indefinitely through your profile.
Satisfaction guarantee: how does it work?
Our satisfaction guarantee ensures that you always find a study document that suits you well. You fill out a form, and our customer service team takes care of the rest.
Who am I buying this summary from?
Stuvia is a marketplace, so you are not buying this document from us, but from seller AnnedC. Stuvia facilitates payment to the seller.
Will I be stuck with a subscription?
No, you only buy this summary for R88,46. You're not tied to anything after your purchase.
