Recommendation system

With the advent devices such as Jawbone Up, Nike FuelBand, and Fitbit, an increasing number of fitness enthusiasts are beginning to track and monitor their activity levels, with very little bother regarding the quality of the same. This assignment seeks to better understand, quantify and predict the performance of a particular physical activity an individual engages in. The assignment begins with data extraction, storing, cleaning and separation. Soon after, various predictive models were formulated using the training data set. Further on, the accuracies of each of these methods were projected using the test set. From the models created, the one with the highest accuracy was chosen to predict how well were the activities performed for 20 different cases within the testing dataset.

The study is aimed to better understand the factors on which the miles per gallon (MPG) of vehicles depend on. For this purpose, the ‘mtcars’ data set was loaded and studied to aide with the answers to the following questions: 1. Is an automatic or manual transmission better for MPG ? 2. Quantify the MPG difference between automatic and manual transmissions.

In this study, an inferential analysis on the tooth growth data of the R datasets package is conducted. The analysis tries and decodes the effect the supplements and its dosages have on the tooth growth. Using Welch’s Two Sample t test the results, interpretations and conclusions for the same have been recorded.

This study investigates the exponential distribution in R and compares it with the Central Limit Theorem (CLT). The distribution is simulated using the function ‘rexp()’ with the arguments n (sample size) and lambda (rate parameter) taken to be as 40 and 0.2 respectively. The investigation is centered around the distribution of averages of 40 exponentials simulated a thousand times.

Impact Analysis of Storms on Social and Economic Well-Being of the Population between 1950 and 2011