Term Paper on "Starbucks Business Research Methods III"

Quoted Instructions for "Starbucks Business Research Methods III" Assignment:

Each one of the bullet points need to be talked about individually.

Must include Introduction and conclusion

I will be sending our Starbucks Questionnaire survey and the Business Research Methods Part II

-Discuss the statistical analysis of your data from the Business Research Methods, Part II assignment.

-Discuss potential challenges to validity and reliability of your research question, data, and analysis.

-Outline steps needed to minimize these challenges.

-Present your data in one of the appropriate general response types.

-Classify your findings in order of power.

Here is a sample paper to use for the paper.

Business Research Methods III

Accurate statistical analysis is essential when analyzing numerical data pertaining to groups of individuals or experiments. In the case of Wal-Mart, the statistical analysis will serve to determine the recessionary economic impact of Wal-Mart Stores, Inc. and how it has affected consumers. Within the context of the required statistical analysis, there are numerous challenges to both the validity and reliability of the actual research question, data, and analysis. As such, steps need to be taken in order to minimize such challenges from occurring. This paper will provide detailed information about the aforementioned concepts as it related to Wal-Mart’s inquiry. Additionally, the data will be presented in one of the appropriate general response types and the findings will be classified in order of power.

Statistical Analysis

In order to determine the recessionary economic impact of Wal-Mart Stores, Inc. and how it has affected consumers, simple random sampling was deemed as the best design to supply adequate data. Simple random sampling incorporates an unrestricted element selection and the representation basis is factored on probability sampling (Cooper, 2006). This method was selected since the probability of the sample population being included within a given sample would be equal (Cooper, 2006). As such, the sample was going to be a fair representation of the population and therefore valid. Wal-Mart’s customer base is especially diverse, and as such, the sampling method had to account for this.

When it comes to statistical analysis in this capacity, the survey data that will be obtained will come from units chosen with an intricate sample design; this had to be accounted for in the survey analysis. The variances within the survey estimates need to be calculated in a manner that is reflective of the sample design. Modeling techniques will be integral in the survey data analysis, and the underlying assumptions will certainly have to be accounted for. After examining the relationships between the survey variables, it should become easier to identify the associations among key response variables, among other factors. These modeling techniques will additionally provide a sense of direction pertaining to the interpretation of the results.

Validity and Reliability Challenges of the Research Question, Data, and Analysis

Validity is the extent to which a test measures what we actually wish to measure (Cooper, 2006). The research question was set to learn how the economy influences Wal-Mart’s consumers. This is considered a valid question because of the degree to which the predictor is adequate in capturing the relevant aspects of the criterion. The instrument chosen was a self-administered questionnaire to learn more about the shopping habits of the visitors to Wal-Mart.

The content validity of a measuring instrument is the extent to which it provides adequate coverage of the investigative questions guiding the study. If the instrument contains a representative sample of the universe of subject matter of interest, then content validity is good (Cooper, 2006). However, the validity of the research findings and statistical data is further limited due to the ability of a research instrument to measure what it is needed to measure (Cooper, 2006).

Reliability has to do with the accuracy and precision of a measurement procedure (Cooper, 2006). The reliability of the question is tougher to measure because consumers may choose to shop at Wal-Mart no matter what stage the business cycle is currently in. Reliability is a necessary contributor to validity but is not a sufficient condition for validity (Cooper, 2006). The questionnaire is a perspective on reliability and considers how much error may be introduced by different observations or different samples of items being studied. The results could be skewed through unreliable measurements, questionnaire participants or statistical data.

Steps Needed to Minimize these Challenges

Despite the potential challenges with regard to the validity and reliability of a research question, it is vital the researcher seek to mitigate these challenges in order to gather rich and robust data. The first challenge mentioned is the possibility of an unfocused instrument development. Inadequate instrument development directly impacts the external validity of the research data. In order to develop an appropriate instrument, the instrument should be tested in pre-test or pilot program prior to full implementation. Quality assurance should be implemented should be implemented for each instrument to enhance internal validity of the research data. Poor internal validity is the result of â€A"performing the testing in the same way in treatment and control groups or if confounding variables were not accounted for in the study design or analysis” (Handley, 2008, p. 1).

Moreover, another possible challenge is that the results could be skewed through unreliable measurement, questionnaire participants, or statistical data. In order to ensure reliability, the data collection team needs to be appropriately trained as this will increase inter-rater reliability. In order to reduce response bias, the research staff could develop parallel forms of the questionnaires by producing a Form A and Form B.

Threats to the study validity and reliability exist throughout the study process but through collaboration throughout the research process, especially prior to full roll-out of the project can help minimize these challenges. Moreover, sufficient pre-planning will better allow researchers address unexpected challenges to both validity and reliability.

General Response Types

Measurement scales fall into one of four general types: rating, ranking, categorization, and sorting (Cooper & Schindler, 2006). The information collected using the Wal-Mart questionnaire employed several different types of rating scales. These scales were used to measure the participants’ attitude toward shopping at Wal-Mart.

The simple category scale was used to gather information from question one in the survey. This question was important to determine if household shoppers were members of the Wal-Mart brand name stores. The multiple rating list scale was used to solicit information in questions 2, 3, 4, 5, and 10, whereas the multiple-choice, single-response scale was used for question 7. These rating scales were important in assessing the demographics and habits of shoppers and the frequency in which the population groups shopped at Wal-Mart.

The likert scale was used to collect information in question six and the multiple-choice, multiple-response scale was used for question eight. These questions investigated the direct impact the recession has caused on shopping patterns and trends. The graphic rating scale was used in question nine to distinguish between different reasons household shoppers have cut back on spending. These scales provided valuable feedback to determine how the economy and unknown variables may have affected household shoppers.

Classification of Findings

Nominal and ordinal measurement scales can also be referred to as categorical data, allowing researchers to group collected information. Using this rationale, the nominal scale data depicts primary household shoppers who do and do not shop at Wal-Mart. The survey reported approximately 9 out of 10 primary households have shopped at Wal-Mart. This indicates consumer confidence is strong and Wal-Mart should continue to grow services and product lines.

Ordinal measurement scales allow the data to be categorized by market type of household. Based on the information collected, all three groups routinely shop at Wal-Mart with the highest percentage of shoppers in the middle market group. More important, the two highest groups who shopped at Wal-Mart were the down and middle markets. With concern for the recession, this indicates Wal-Mart will remain strong during times of economic downturn. Wal-Mart should continue focusing on low prices to capture the largest possible percentage of shoppers.

Both interval and ratio measurement scales can be classified as continuous data. The interval scales incorporate the concept of equality of interval (Cooper & Schindler, 2006). To determine current shopping trends, data for shoppers within the past month was evaluated. Again, the two highest groups were the down and middle market households. It can be concluded that shoppers’ demands for bargain prices can influence spending at anytime, anywhere, and anyplace for anything (Retail Forward, 2006). Finally, ratio scales provide a look at the actual type of products consumers are buying. Based on the high percentage of seasonal products purchased among all three shopping groups, Wal-Mart needs to plan for cyclical spending increases. It will be important for management to identify and recognize the impact seasonal variables may have on consumer spending.

Conclusion

Based on the information above, it is now clear how accurate statistical analysis is essential when analyzing numerical data pertaining to Wal-Mart’s inquiry as to the recessionary economic impact of its company and how it has affected its consumers. There are many challenges to both the validity and reliability of this inquiry, in addition to the data and analysis. As such, appropriate steps need to be taken in order to minimize these challenges from occurring. The data in which Wal-Mart collected was employed through the utilization of a questionnaire through numerous kinds of rating scales in order to measure the participants’ overall attitude toward shopping at Wal-Mart. Lastly, according to the findings, consumer confidence is strong, and Wal-Mart should continue to grow its services and product lines. Additionally, Wal-Mart should remain strong through times of economic downturn. As such, the company should continue to focus on low prices to capture the largest possible percentage of shoppers.