This dynamic application is created as the final project of Developing Data Products Course, from Coursera. This app is supposedly used for a company to reduce cost on car rental using mtcars dataset included in the R system. The first step is for the company to input the distance of the destination and the price of gasoline at the location. Such information will be used to compute the Gasoline Expenditure for each car brand in the mtcars dataset. Also, the company inputs the maximum amount of money to be spent on gasoline, which is shown on the table depending on cars that can reach a mpg below that amount. The second step is to select the features of desired cars such as cylinders, displacement, horse power and transmission. Accordingly, the table will only show cars that match those features. It is possible to sort the table using a selected variable using the arrows at the top of the table.

To analyze the ToothGrowth data in the R datasets package. Load the ToothGrowth data and perform some basic exploratory data analyses Provide a basic summary of the data. Use confidence intervals and/or hypothesis tests to compare tooth growth by supp and dose. Stated the final conclusions and the assumptions.

Used simulation to explore inference and do some simple inferential data analysis.Compared the sampled values with the theoretical values of the following parameters - 1.Mean 2.Variance 3.Distribution to investigate the exponential distribution in R and compare it with the Central Limit Theorem (CLT).

Storms and other severe weather events can cause both public health and economic problems for communities and municipalities. Many severe events can result in fatalities, injuries, and property damage, and preventing such outcomes to the extent possible is a key concern. This project involves exploring the U.S. National Oceanic and Atmospheric Administration's (NOAA) storm database. This database tracks characteristics of major storms and weather events in the United States, including when and where they occur, as well as estimates of any fatalities, injuries, and property damage.