Individual Case Study Review Paper

Individual Case Study Review Paper.


Individual Case Study – Instructions

Pages: 3

Deadline: 12hrs

Review the practice activity on descriptive modeling (identifying the relationships between variables), and practice calculation of correlations and building scatter plots using this data file Magic Foods. Pattern Recognition. Data (student).xlsx .

Follow the instructions in the Individual Case Study Instructions 2019.docx to analyze the case.

Prepare a business memo to report and discuss your findings on this case and answer the case questions. You will use the same rubric as for your individual project (also attached here ). Follow APA 6 style to prepare the report, and include NSU Cover Sheet and the rubric at the beginning of the report. Submit the Case for grading before due date.

Individual Case Study

Part 1

The leadership of magic food manufacturers has centralized their production operations in manufacturing pickles, spices pastes, and also instant mixes. Magic sales managers have been quick in disseminating organized data indicating the number of sales relating to stores, population, number of territories, and the type of brand. The stakeholders are interested to understand the originality of the issues impacting the magic foods organization. Therefore as an attempt to generate and informed study over the same, they drafted a problem statement as stated below. The stakeholders are interested to know if the population is one of the factors driving sales and also if there are other determinants of sales and in particular which ought to be focused on.

Part 2

Before the commencement of the calculations, some assumptions were brought to the table as an approach to enhance uniformity. First, the variable to be utilized in the experiment were assumed to exhibit a uniform distribution. Also, the data was deemed to poise some editing linearity regardless of the direction and strength. Finally, the variance was assumed to exhibit homogeneity in different sample groups.

Descriptive modeling is an approach utilized in describing real-world events and the real correlation between factors responsible for fro their occurrence. In most cases, organizations driven by consumers tend to implement the approach during advertisement efforts and target marketing. After executing some spreadsheet calculations over the same using the provided data; It was found out that the mean average outcome of the sale was $ 26 million. Also, the median was calculated for the magic food firm. After an accurate evaluation of the data, the median was found out to be $ 22.6 million. The variation of the two figures poised query on how data was evenly the long run, mean is not advocated for since outliers tend to influence the technique of measuring data. Dually, the median is settled for as the best option to utilize when dealing with skewed data. Arguably, the median is most preferred when calculating the central tendency of data, especially when dealing with large data sets.

After the execution of well-monitored calculations, the standard deviation of the data was found to be $ 17.6 million. The stakeholders may find it reasonable to utilize standard deviation since it assists in evaluating the spread of the data sets offered. The figure can assist in determining how close the outcome is to the average. Thus it is a prudent approach to introduce the measurement of deviation as a technique to evaluate the data spread. Further, after the calculation of the standard posed by the total population was 97200. Moreover, the average value attained from the number of stores was 1157. The strength of the correlation between the number of sales to that of the population was 0.975. Conversely, the correlation value between the number of transactions to that of the total stores was 0.914. Finally, the model of all the brand categories was evaluated to 13.

Discuss the results of your analysis, implications for future data analysis.

The given data was analyzed using scatter plots, coefficient of correlation, and the pivot plots. Scatter plots were mostly preferred in the descriptive technique. The scenarios are essential in analyzing data since the focus on two variables. One of the variables must be dependent while the next is independent. A relationship between the population, sales, and the stores were established using the scatter plots. When preparing the technique to implement in the analyses of data, it was discovered that the market potentials were assessed from the available population. Concerning the obtained data, the correlation coefficient between the community and sales was found to be a strong positive relationship. Both variables were moving in tandem conforming to a similar direction, as indicated therein by the scatter plot. A positive correlation was an indication that one variable was decreasing while the other realizing some drastic increase. In future Magic foods ought to utilize the outlined results to mitigate some limitations realized and also capitalize on the positive impacts attained. For instance, there is a need to understand that increase in market size contributes to the rise in the number of sales that directly relates to the number of stores.


Magic foods organization stakeholders ought to understand that the population is the driving force in sales. Therefore they ought to lopcate their outlet stores in areas with high society. Nevertheless, they must also work on the advertisement since sales walk hand in hand with marketing strategy set in place. The profit margin will increase drastically if tremendous resources are devoted to identifying the target market in populated areas.

Moreover, the number of stores should be directly proportional to the number of sales realized from a specific area. More importantly, they can plan on how to maintain their business open for extended meal periods. The strategy will assist in winning over customers who work on late-night shifts or even early mornings. Finally, magic foods must work out techniques on how to mitigate existing diversities between mean and median values.

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