Statistical Analysis in Marketing Research

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Table of Contents

Summary
Key learning points
Critical analysis
Practical implications
Works Cited

Summary

In market research, the method used to analyze any given piece of information is as weighty as the method used to gather data. Failure to use the right data collection method would mislead a researcher into assembling irrelevant data. Likewise, using the wrong data analysis method would result into wrong results and unwarranted conclusions even in situations where a researcher has the right data (Diamantopoulos 77). This article is a presentation on factors that usually influence a researcher’s choice of statistical analysis method to apply in analyzing a set of data (Diamantopoulos 87). The paper presents pertinent considerations that guide a researcher’s choice between parametric and non-parametric analysis techniques.

Key learning points

Diamantopoulos’ article has the following key learning points:

A market researcher should not leave the selection of the appropriate analytical method to his or her computer software, instead
1. The researcher should carefully consider his or her analysis objectives, that is, what s/he is attempting to accomplish
2. The researcher should think carefully about the nature of data s/he is working with; that is, data characteristics
The computer is a device that makes work efficient and can do only what it is instructed to do. Bear in mind that the reliability and accuracy of the results it produces rely on the quality of data fed into it and expertise with which it is instructed to analyze it (Diamantopoulos 78).

Critical analysis

Setting analysis objectives is a decisive step in the analysis process because it lays out the path towards getting the correct results which forms the basis for making relevant conclusions that are a true picture of the reality (Zikmund and Babin 68). A focused researcher should bear in mind the three main roles that coming up with clear analysis objectives play. This includes ensuring that the researcher undertakes only relevant analysis (Diamantopoulos 78; McDaniel and Gates 18).

It is pertinent to note that if the analysis undertaken does not contribute directly towards answering the research topics of interest, then it is not relevant. Secondly, setting analysis objectives enables the researcher to ensure comprehensiveness of the process (Diamantopoulos 78). The Depth of the analysis process ensures that the researcher has fully used the information potential in a set of data. In other words, analyzing data on just some variables makes your analysis incomprehensive even though it may be relevant. Third, setting analysis objectives enables a researcher to shun redundancy (Diamantopoulos 78).

Having analysis objectives ensures that, the only relevant thing is done, and it is done adequately without repetition (Diamantopoulos 78). This can be likened to having a clear roadmap with signposts that warn a traveller against dangerous and unnecessarily long routes as s/he moves toward his or her destiny.

Different parts of a research study should be properly related because; each part determines how successful the researcher is, in getting correct results that are a true reflection of reality. For instance, the research objectives form the point of departure for coming up with analysis objectives. Therefore, the link between research objectives and the analysis objectives should be clear (Diamantopoulos 79; Hair, Bush, and Ortinau 49).

This means that developing analysis objectives should start with a thorough reassessment of the research objectives. In any case, the researcher should always have the research objectives on his or her fingertips throughout the study. Otherwise, conducting a research study whose objectives are not clear to the researcher is not worthy doing let alone doing it well. Right from the beginning the research objectives should be short, succinct and realistic. Such research objectives will in turn ensure that appropriate analysis objectives are developed when the researcher sets out to analyze the collected data (Diamantopoulos 79). Two kinds of decisions inform the process of deriving analysis objectives from the research objectives. The first decision relates to the content of the analysis which encompasses choosing of variables to be used in actual analysis (Diamantopoulos 79).

The second decision involves considering the focus of the analysis in terms of analytical orientation to be used. The selected orientation could be an assessment of relationships between variables of the study or an ordinary description.

Considering the above mentioned momentous decision is followed by a selection of one of the three fundamental forms of focus of the analysis namely description, hypothesis- testing and estimation (Diamantopoulos 80). In particular, description has appropriate matching statistical techniques that a researcher can use to conduct an analysis known as descriptive statistics. Once again at this juncture, the choice of the preferred form of focus of analysis is informed by the set analysis objectives. Data characteristics are also as powerful as the content and focus of the analysis in ensuring a fruitful and meaningful analysis. Therefore, it should be considered carefully (Diamantopoulos 81). The choice of data analysis is critical to the fruitful use of well assembled set of data. As such, it is significant to answering research questions and the ultimate achievement of the research objectives. It enables the researcher to unearth reality beneath the ordinary business as usual activities.

Practical implications

The value of Diamantopoulos’ article to my profession in reality can not be underestimated. Market research is the informative eyes through which marketers seek to understand the target audience for their products and services, as well as, other factors shaping the general economic behaviour of the society during different times. It, usually, involves data collection and data analysis in order to arrive at results that can help a marketer make correct conclusions about the market with the least margin of uncertainty. Therefore, the subject matter of this article can help me in ensuring that I do not assign the role of choosing an analysis method to my preferred computer software. It can help me to look at the computer always as a device whose main role is to make my work efficient.

For this reason, in reality this article can help me ensure that I feed my computer with the relevant data so as to ensure reliability and accuracy of the information it generates. This article is a wake up call for me to the challenge of the need to hone my data entry and data analysis skills continuously, which are critical in making sure that I am competent in handling data meaningfully. I can also apply the subject matter of this article in establishing clear links between research objectives of a typical research study and the setting of analysis objectives. This is critical because the starting point of setting analysis objectives is re-examination of the research objectives.

The derived analysis objectives in turn ensures that the data gathered is used in a relevant way, adequately and without redundancy. This would enable me to increase chances of getting the right results and thus make reliable conclusions about a given phenomenon of interest. In a nutshell, this article can be particularly useful to me in a real business situation.

Works Cited

Diamantopoulos, Adamantios. “Getting started with data analysis: Choosing the right method.” The Marketing Review, 2000. Web.

Hair, Joseph, Bush, Robert, and Ortinau, David. Marketing research: within a changing information environment. London: McGraw-Hill/Irwin, 2005. Print.

McDaniel, Carl, and Gates, Roger. Marketing research essentials. New York, NY: John Wiley, 2005. Print.

Zikmund, William, and Babin, Barry. Exploring marketing research. New York, NY: Cengage Learning, 2006. Print.

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Statistical Analysis in Marketing Research

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