Our methods include a descriptive and clustering analysis. We wanted to understand how our data could be grouped. We used K-means clustering and our data wa

Our methods include a descriptive and clustering analysis. We wanted to understand how our data could be grouped. We used K-means clustering and our data was grouped into three different clusters, reflecting differences in their installs, reviews, and ratings. Then, we identified the top categories and average price distribution of the apps within each category to find out the optimal price in the google play store. Moreover, we built a regression model between all Install and other independent variables such Category, Genres, Size, to see which variable has a significant effect on the former. Finally, we used our findings from the regression model to create forecasting analysis using K nearest neighbors and regression trees, and compared the performance of both models based on RMSE value.