This is the presentation for the final project of the peer graded Coursera Course "Developing Data Products".

Example of plotly using iris dataset.

Report that describes the accuracy of prediction of whether a certain fitness action is performed correctly.

Report that describes the relationship between MPG and transmission type in the mtcars dataset.

The project investigates the exponential distribution in R and compares it with the Central Limit Theorem. The project illustrates via simulation and associated explanatory text the properties of the distribution of the mean of 40 exponentials.

In this analysis we evaluate the effect of vitamin C on tooth growth in guinea pigs using the ToothGrowth dataset. This dataset contains the growth of odontoblasts (teeth) in each of 10 guinea pigs after administration of three different dose levels of Vitamin C (0.5, 1, and 2 mg) with each of two delivery methods, orange juice (OJ) or ascorbic acid (VC).

The National Oceanic and Atmospheric Administration (NOAA) maintains a public database for storm events. The data that is collected here displays information on the type of storm and details like location, date, estimates for damage to property as well as the number of human victims of the storm. In this report we investigate which type of events are the most harmful to the population and economically between the period of 1996 and 2011. From this analysis it is clear that tornadoes have the highest number of victims, causing the highest number of injuries and the second highest number of fatalities, closely following excessive heat events. Besides tornadoes, other major weather types having a high number of victims were excessive heat events and floods. In terms of economic costs however, weather types that occur on a larger scale and have a longer timespan than when compared to tornadoes, seem to have more impact. The leading weather type in terms of costs were floods, having the highest cost in property damage and coming in second in terms of crop damage, being preceded by droughts. Furthermore, it appears that the costs for crop damage do not seem to be a major factor in the total costs of damages caused by weather events, as these are majorly governed by costs for property damage. Besides floods, other major weather types having a high economical impact were hurricanes/typhoons and storm surges.