/Analysis-of-Santa-Clara-Valley-bank

In this project, I built logistic regression model in RStudio to predict the probability of customers enroll in direct payroll deposit so that the bank can save their money and resources by contacting only customers that exhibit high probability and how best the bank can use my logistic regression model to help them strategize business goals.

Primary LanguageR

[Note: You can preview files that are in CSV and R format by clicking on the file]

Software I used:

RStudio

Description:

  • In this case study, I teamed up with 4 classmates to analyze Santa Clara Valley bank dataset by using logistic regression model. I was primarily in charge of writing codes, formatting PowerPoint slides, delegating tasks, and explaning my codes to my classmates as well as helping my classmates out whenever they struggled on analyzing the dataset.

  • The sample data show the average monthly checking account balance (in hundreds of dollars) and whether the customer contacted signed up for payroll direct deposit (coded 1 if the customer signed up for payroll direct deposit and 0 if not). The data are contained in the data set named HW5_Bank. My task is to develop and fit a logistic regression model in order to predict the probability of customers signing up for direct payroll deposit and to estimate the average monthly balance required to achieve .50 or higher probability of signing up for direct payroll deposit. I also analyzed the estimated odds ratio in order to find out if the odds in favor of signing up for deposit increase for any increase of one-unit, five-unit in customers account balance.

  • The CSV file named newdatabank was made to predict the probability of customers signing up for direct payroll deposit if they have an average monthly balance of $1200 in their checking account.

  • I concluded my analysis of the case study with a PowerPoint presentation. The PowerPoint slides contain output of my R codes and description of the output as well as my conclusion and recomendations. You can preview screenshot of a few of of my PowerPoint slides here: (https://user-images.githubusercontent.com/92205707/170785125-4c7afe28-e3aa-4edf-8f50-5468d6170990.png) (https://user-images.githubusercontent.com/92205707/170785307-447e8144-f114-4760-96bf-8a3ed1c6f2bc.png) (https://user-images.githubusercontent.com/92205707/170785335-cb0164ed-c4ef-4d57-9568-1bd4ac35f010.png)