Case Study Data Analysis Example

A case study may have just one objective or it may be an extended analysis of many different topics. The key to successful case study data analysis is to extract the information for all cases.

The raw case study data is often tedious to deal with, even for the best of data analysts. However, the process involves some critical thinking in code that provides for quick and easy reading of all data from which further analyses can be created.

It is extremely important to isolate all data that might change the way data is presented. For example, you may have about 20 persons on the table, but each of them has a different age. The person with the highest age could be representing the person with the most experience, which would not be true.

You may want to use your analysis to find out what the median age is among the adults in the group. The overall median age may be the true median, as well. The “comma” analysis will give you a simple way to read your data without having to worry about string comparisons between values.

You must also analyze the independent variables (the variables of interest) that may impact the data. Some of the independent variables may change over time, such as the employee’s job title. You may want to compare the effects of starting off as a cashier versus starting as a customer service representative.

For people who are just beginning to use case studies as part of their data analysis, there are many things that they should look for and consider when working through the data. Some of these factors include:

These will be the most important factors, but will need to be evaluated very carefully to find the best results. If an employee has a low performance score, this may be due to poor training, poor supervision or lack of individual attention. Each of these things can be looked at separately, but the results may be surprising. Once they are used in combination, a specific analysis method is needed to help determine the exact cause.

In the long run, it may be helpful to analyze this data by doing a logistic regression. The results from this statistical analysis may provide a lot of information about how they performed and their underlying skills, such as self-control, self-motivation, communication skills, etc. This information may help improve management and job performance, and therefore improve the business.

The independent variable can be one of the variables that impacts performance, or it can be a set of variables, such as job title, experience, job responsibilities, training, experience, etc. The purpose of this type of analysis is to find which variables have the greatest effect on the results. This type of analysis can be quite complicated and time consuming.

A case study solution will help by providing a template that can be used for creating a case study. You can also include a template of a well-designed case study that includes the necessary information to create the case study. That information will include:

It is very important to begin the data analysis with a good data management plan, a list of expectations for analyzing and the type of data that will be needed to complete the study. While the actual data will be created later, all the information needed to collect it is necessary at the beginning to ensure that the data is cleaned, organized and easy to read.

A case study solution will provide a template that can be used to organize the data for you to identify the critical issues and then interpret the results in a manner that is easier to understand. In addition, it will provide a valuable example of how to handle the raw data and create a report with it.