SagarBansal7

Comic-Center

Statistical Analysis to understand different customer groups and their purchasing behavior using cluster analysis technique in order to improve comic center's business.

Database-Definition-to-Data-Visualization

Northern Lights Technical (NLT) School was founded in 1985 in Pittsfield, MA. It was the first computer software training business in the area and was immediately successful. Over the decade since its inception, NLT has grown steadily and is still the market leader in computer training in the Pittsfield area. The growth of the company has caused bookkeeping problems for the company who, up until the present, have kept all their business records in a series of MS Excel spreadsheets. To address the inadequacy of the current system we were asked to prepare a database system for NLT from the ground up. In addition, we need to answer client's specific questions and make recommendations from our findings.

Employee-Absenteesim

Statistical Analysis to predict whether an employee is likely to abuse the leave policy based on factors such as Age, Current Salary, Employment Type (Full-time/Part-time) and Raise given in last five years (Yes/No) using logistic regression technique.

Graduate-Admission-Prediction

This project aims to evaluate several parameters which are considered important during the application for Masters Programs. When we went through the process of preparing, applying, and collecting required documents for the admission, we were less informed about how and in what percentage the individual documents will contribute to our selection. Here in this study, we will try to find interesting pattern on how different features relate to chances of admit. The results will surely reveal something insightful. In addition, we have emphasized on making this report comprehensible for non-statistical/technical audiences so the results can then be used by the potential students in strengthening their profile accordingly.

House-Price-Investigation

This analysis emphasizes on investigating the different factors that are correlated with the price of a house in ten cities in the state of Washington. The cities that we studied were Seattle, Renton, Bellevue, Redmond, Kirkland, Issaquah, Kent, Auburn, Sammamish and Federal Way. We built a multiple linear regression model with variables such as number of bedrooms, number of bathrooms, square footage of living area, square footage of lot, number of floors, city, and age of the house out of 18 different variables in the beginning. After our analysis, we found that only square footage of lot does not add much to the average natural log of house price values when other features of the house remain same.

Keep-on-Closing

Statistical Analysis to understand the impact of Architecture Style on the relationship between Home Price (in dollars) and Square feet of the property using Multiple Linear Regression technique.

Stroke-and-Health-Status

With the improvements of living standards, people nowadays pay more attention to their health. This report talks about stroke, one of the biggest health problems in the U.S., focusing on the pre-existing health factors that will potentially rise one’s risk of getting a stroke. We investigated relationships between stroke and other factors including age, hypertension, heart disease, average glucose level, body mass index, and smoking status. With the logistic regression model we fitted, it is clear that within the six factors, body mass index is the only factor that has little association with whether a person will get a stroke or not. The cluster analysis model showed that age and average glucose level are important factors that helped conclude the four different groups of people.

Always-Be-Closing

Statistical Analysis to understand the relationship between Home Price (in dollars) and Square feet of the property using linear regression technique.

iOS-Mobile-Application-Analytics

With millions of apps in the market, it is important for app developers to understand the users’ needs as well as the demands of the apps. Most importantly, it is important that app developers understand the success of the applications for further progress in the market. We utilized the Mobile App Statistic data set to analyze and identify trends to support app developers in their efforts to develop successful applications. Recommendations include a prioritized list of industries as well as key aspects driving user downloads to be considered when building an application, to support app developers in their efforts to uncover prospect markets and develop successful applications.

QB_APIs

SagarBansal7/Spark-for-Machine-Learning-and-AI

This provides readers with the facility to understand how Spark can be used in a number of machine learning techniques and what are the steps to utilize it.

SagarBansal7/House-Price-Investigation

This analysis emphasizes on investigating the different factors that are correlated with the price of a house in ten cities in the state of Washington. The cities that we studied were Seattle, Renton, Bellevue, Redmond, Kirkland, Issaquah, Kent, Auburn, Sammamish and Federal Way. We built a multiple linear regression model with variables such as number of bedrooms, number of bathrooms, square footage of living area, square footage of lot, number of floors, city, and age of the house out of 18 different variables in the beginning. After our analysis, we found that only square footage of lot does not add much to the average natural log of house price values when other features of the house remain same.

SagarBansal7/Stroke-and-Health-Status

With the improvements of living standards, people nowadays pay more attention to their health. This report talks about stroke, one of the biggest health problems in the U.S., focusing on the pre-existing health factors that will potentially rise one’s risk of getting a stroke. We investigated relationships between stroke and other factors including age, hypertension, heart disease, average glucose level, body mass index, and smoking status. With the logistic regression model we fitted, it is clear that within the six factors, body mass index is the only factor that has little association with whether a person will get a stroke or not. The cluster analysis model showed that age and average glucose level are important factors that helped conclude the four different groups of people.

SagarBansal7/Database-Definition-to-Data-Visualization

Northern Lights Technical (NLT) School was founded in 1985 in Pittsfield, MA. It was the first computer software training business in the area and was immediately successful. Over the decade since its inception, NLT has grown steadily and is still the market leader in computer training in the Pittsfield area. The growth of the company has caused bookkeeping problems for the company who, up until the present, have kept all their business records in a series of MS Excel spreadsheets. To address the inadequacy of the current system we were asked to prepare a database system for NLT from the ground up. In addition, we need to answer client's specific questions and make recommendations from our findings.

SagarBansal7/sagarbansal7.github.io

SagarBansal7/Comic-Center

Statistical Analysis to understand different customer groups and their purchasing behavior using cluster analysis technique in order to improve comic center's business.

SagarBansal7/Employee-Absenteesim

Statistical Analysis to predict whether an employee is likely to abuse the leave policy based on factors such as Age, Current Salary, Employment Type (Full-time/Part-time) and Raise given in last five years (Yes/No) using logistic regression technique.

SagarBansal7/Always-Be-Closing

Statistical Analysis to understand the relationship between Home Price (in dollars) and Square feet of the property using linear regression technique.

SagarBansal7/Keep-on-Closing

Statistical Analysis to understand the impact of Architecture Style on the relationship between Home Price (in dollars) and Square feet of the property using Multiple Linear Regression technique.

SagarBansal7/Graduate-Admission-Prediction

This project aims to evaluate several parameters which are considered important during the application for Masters Programs. When we went through the process of preparing, applying, and collecting required documents for the admission, we were less informed about how and in what percentage the individual documents will contribute to our selection. Here in this study, we will try to find interesting pattern on how different features relate to chances of admit. The results will surely reveal something insightful. In addition, we have emphasized on making this report comprehensible for non-statistical/technical audiences so the results can then be used by the potential students in strengthening their profile accordingly.

SagarBansal7/iOS-Mobile-Application-Analytics

With millions of apps in the market, it is important for app developers to understand the users’ needs as well as the demands of the apps. Most importantly, it is important that app developers understand the success of the applications for further progress in the market. We utilized the Mobile App Statistic data set to analyze and identify trends to support app developers in their efforts to develop successful applications. Recommendations include a prioritized list of industries as well as key aspects driving user downloads to be considered when building an application, to support app developers in their efforts to uncover prospect markets and develop successful applications.

SagarBansal7/QB_APIs