Semester 1

Title: Predictive Analysis of U.S. House Pricing - A Linear Regression Approach

Synopsis: The main objective is to predict the sale price of a house in the US using the given data. For that, it is required to plot a regression equation using the Sale price as the response variable and the other factors as the predictor or the independent variables. At first, the non numeric data should be converted into categorical data for ease of calculation and then the data needs to be cleansed i.e., the missing values should be replaced and the non numeric columns containing too much missing data must be dropped. Some tests should be carried out to extract some useful conclusions about the data and also to drop some significant predictor variables. At last, when these necessary steps are done, the final regression equation needs to be plotted using sale price as the response variable and the significant predictor variables as the covariates. With help of that regression model, the necessary predictions can be made..

Title: Fact or fiction: An Analytic guidance on book writing.

Synopsis: In our present study we want to find between Fiction and Nonfiction which genre of a book can an author write or a publisher can publish based on our data in hand and using some inferential Analytics tool. We have chosen a dataset that has three parameters i.e. review, user rating, and price of books. Based on these parameters we have tried to define the criteria for a good book. Our criteria is that : 1)The book should belong to a mid-price range. 2)It should have a high user rating and 3)It should have high user reviews.