Marketing Research Bangor Transfer Abroad Programme Week Three Review.

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Week ThreeWeek Three

ReviewReview



SURVEY RESEARCH



Based on simple idea:

“”… the best way to find out what consumers think is to ask them.”

Zikmund



Survey Research

A method of collecting primary data by communicating with a representative sample of people



Properly conducted Surveys can be:

•Quick•Inexpensive•Efficient•Accurate•Flexible



Problems with Surveys come from:

•Nonresponse error•Response bias•Administrative error



Types of Sampling:

•Personal Interviews•Intercepts•Telephone interviews•Self administered questions•Mail questionnaires•Email



SAMPLING

(Zikmund, Chapter 12)



Examine a Part of the Whole

In most surveys access to the entire population is near impossible,

The results from a survey with a carefully selected sample will reflect extremely closely those that would have been obtained had the population provided the data.



There are essentiality two types of sampling:

•probability •non-probability

sampling.



Randomisation

- Individuals are randomly selected.

- No one group should be over-represented.

- Sampling randomly gets rid of bias.

Random samples rely on the absolute objectivity of random numbers.



Four basic types of random sampling techniques:

•Simple Random Sampling•Systematic Sampling•Stratified Sampling•Cluster or Multi-stage Sampling



Simple Random Sampling

This is the ideal choice as it is a ‘perfect’ random method.

Using this method, individuals are randomly selected from a list of the population and every single individual has an equal chance of selection.



Cluster or Multi-stage Sampling

Is particularly useful in situations for which no list of the elements within a population is available and therefore cannot be selected directly.

As this form of sampling is conducted by randomly selecting subgroups of the population, possibly in several stages, it should produce results equivalent to a simple random sample



Cluster samples are generally used if:

- No list of the population exists.

- Well-defined clusters, which will often be geographic areas,exist.

- A reasonable estimate of the number of elements in each level of clustering can be made.

- Often the total sample size must be fairly large to enable cluster sampling to be used effectively.



Non-probability Sampling Methods

Non-probability sampling procedures are much less desirable, as they will almost certainly contain sampling biases. Unfortunately, in some circumstances such methods are unavoidable.

In Marketing Research the most frequently-adopted form of non-probability sampling is known as quota sampling.



Calculating a Sample Size:

Calculation of an appropriate sample size depends upon a number of factors unique to each survey and it is down to the researcher to make decisions regarding these factors. The three most important are:

- How accurate you wish to be- How confident you are in the results- What budget you have available



The required formula is:

s = (z / e)2

Where:s = the sample size

z = a number relating to the degree of confidence you wish to have in the result. 95% confidence* is most frequently used and accepted. The value of ‘z’ should be 2.58 for 99% confidence, 1.96 for 95% confidence, 1.64 for 90% confidence and 1.28 for 80% confidence.

e = the error you are prepared to accept, measured as a proportion of the standard deviation (accuracy)

Marketing Research Bangor Transfer Abroad Programme Week Three Review.

Documents

programme types of sampling

programme sampling zikmund

cluster sampling

multistage sampling

zikmund slide

programme week

form of sampling

programme problems