Bonus (5 points) Analyzing data and presenting the results is an important skill for engineers and scientists. For this problem you will work on reporting basic statistics, fitting simple regression models, and plotting the results for easy visualization You will use a modified version of the Bike Sharing Dataset from data from the article Fanace and Gama (201]), "Event labeling combining ensemble detectors and background knowledge", Progress in Artificial Intelligence. The data can be downloaded from blackboard. This dataset contains two years of information about bike sharing and weather on a daily or hourly basis in Washington D.C. a) Find the mean, standard deviation, and number of observations of "rental bikes" for each attribute (column) in the dataset. Report the results in a table. Are the trends in the number of bike rental expected? (0.5 polm) bj Fit a regression model where rented bikes = as + 3, Feeling Temperature for the entire dataset. Report the coefficients for the model and attach one plot clearly showing the data (scatter) and the fitted model (Line). Are the results expected? (1 points) c) Find the mean, standard deviation, and number of observations of "rental bikes" for each season of the year. Report the results in a table. Are the trends in the number of bike rentals expected? (0.$ point) d) Fit one regression model where Rented bikes = a, + a Feeling Temperature for each season. Report the coefficients for all models and attach one plot clearly showing the data (scatter plot) by season and the fitted models, including the model for the entire dataset. Are the results expected? Below is an example of how your plat should look like. (1 points) Number of hikes named to Winter regression Spring regreson Summer regression Fall mansion Ororal regression In Winter data *: Spring data .on Summer data bus Fall ate -2000 10 30 Feeling Tempepure Hep c) Your boss wants to estimate how many spots to rent in the bike rack each week. Renting space is expensive because there are many competing bike rental companies and there are not many secure blike racks. How can the models you developed earlier in the problem be used to help your boss determine