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Marketing Research Ethical Guidelines & Data Collection Plan

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Why is it critical to use the correct statistical procedure when analyzing data?

What are examples of good ethical guidelines for marketing research?

Why is the final report the most important part of a marketing research study?

Why is it critical to have a good data collection plan when do a marketing research study?

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A solution of over 2,000 words with references answering the following questions:

Why is it critical to use the correct statistical procedure when analyzing data?

What are examples of good ethical guidelines for marketing research?

Why is the final report the most important part of a marketing research study?

Why is it critical to have a good data collection plan when do a marketing research study?

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Why is it critical to use the correct statistical procedure when analyzing data?
It is critical to use the correct statistical procedure when analyzing data to provide the best and most applicable results to the study. Understanding statistics and which procedure to use is required in almost any academic discipline or study (Introduction to Statistics, 2008). "The main objective of business statistics is to make inferences (e.g., prediction, making decisions) about certain characteristics of a population based on information contained in a random sample from the entire population" (Arsham, 1994). In the business field understanding which statistical procedure to use will give the individual or organization an idea of how to reduce costs, cater to customer's needs, and find new innovative ways to maximize profits, and shareholders wealth. "Business Statistics is the science of good decision making in the face of uncertainty and is used in many disciplines, such as financial analysis, econometrics, auditing, production and operations, and marketing research" (Arsham, 1994). In marketing research choosing the right statistical procedures allows for an individual or organization to create a plan that includes a favorable marketing mix (McDaniel & Gates, 2006). In choosing a correct sample and statistical procedure this will allow the organization to study and depict the true overall nature of the population. Many companies spend millions of dollars each year marketing their product and it is imperative that they study and listen to their consumers needs, wants, and cater a plan geared toward them. Without an effective or correct statistical procedure organizations do not have an accurate plan to effectively market their product. One of the basic ideas over any academic discipline is that a correct statistical procedure when analyzing data gives the individual a basis to make correct decisions. Quantitative data in any industry is important in the decision-making process to effectively give themselves the appropriate information necessary to succeed in the future. The Merriam-Webster Dictionary (2010) defines sampling as "the act, process, or technique of selecting a suitable sample; specifically: the act, process, or technique of selecting a representative part of a population for the purpose of determining parameters or characteristics of the whole population" (para. 1). It is important organizations take sampling very seriously as an important part of the statistical procedures because it provides the basis for the statistical test and the analyzing the correct information (Introduction to Statistics, 2008). If an error is made in the sampling process then the test would not be based on quantitative data rather erroneous information. A correct statistical procedure that yields and effective result serves to simplify the decision-making process. From the statistical analysis decision-making models can be drawn and tested. In some cases, statistical processes can be repeated in certain situations to simplify the decision-making process and make informed decisions more quickly and accurately. Providing the correct statistical procedure it will give the decision-maker the quantitative data to make a more appropriate choice.

References
Agresti, A. & Franklin, C. (2009). Statistics. The Art and Science of Learning from Data. (2nd ed.). Prentice Hall.
Arsham, H. (1994). Statistical Thinking ...

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