Case Study A-Carp Corporation
A. Identify Appropriate Family and Reason for Selecting it.
To analyze A-Cap Corporation’s data, I will use measures of central tendency and distribution. Measure of central tendency is a measure used to describe the mean, median, and mode of a particular set of data while measure of distribution shows the skewness, kurtosis, and develops a hypothesis about a particular set of data. The reason I selected these two measures is that they will help analyze the data of A-Carp Corporation accurately.
B. Identify the Categories of Data and their Relationship with the Tools of Data.
The data in the case comprises of mean, standard error, median, mode, standard deviation, variance, skewness, …show more content…
Analyzing the Data
A. Process of Data Analysis
To analyze the data, I would need to first determine the problem at hand. The problem in this case is analyzing the data given for A-Carp Corporation (Kakwani, 1990). Then I would need to find a suitable quantitative method for data collection. In this case, the company has given the data so it is only a matter of observing the data given. I can then conclude how the company is performing by drawing graphs and analyzing the trend of the data. The last step is giving a recommendation of how the company can enhance its financial performance.
B. How the Process Leads to Validity of the Decisions
This process of analyzing data that I will use will lead to valid decisions, as it will elaborate the accuracy, completeness, relevance, and reliability of the data. If the graph I present portrays an upward trend, then the company is performing well and as expected, but if the trend is downward, the company is not performing well and management should formulate decisions to increase the reliability of the data presented (Greasley, …show more content…
On the graph, the mean is increasing at a steady rate but the increment is not visible. The variance on the other hand is quite visible and it is increasing at an increasing rate. This tells us that as the number of years’ increase, there is a higher deviation from the mean, which is not a good sign. The graph of skewness and kurtosis of sales of refrigerators and transformer requirements tells us that the two are positively skewed (White, Kim, & Manganelli, 2008). The transformer requirements are also positively skewed and they have a large kurtosis. A large kurtosis implies that there is a great outlier problem and a researcher should choose a different method of data collection. This also shows that the results are not reliable hence they are not accurate, and complete (Feunou, & Tedongap,