R Statistics

 Module 3 Assignment This is the output for the data given for Module 3. The results are mainly errors and come from syntactical errors within the code. In the name definition, there is not a comma between Marco or Hillary and the same is present within the ABC political poll results. Additionally, the data has not been organized into a dataframe and is essentially not able to be constructed properly without some extra elements and a dataframe function call.

 Module 3: DUI Fatalities and a Visualized Breakdown In the United States, particularly in the Southeast, there is a problem with fatal drunk driving accidents. The issue is not necessarily the occurrence of it as much as it is the arguments of whether or not the presence of such events happens more frequently for reasons outside just population and the police ability to catch these people.  This visual employs some simple math based on metrics from the Tableau graph and census data to show the differences in frequencies of these fatalities happening relative to the states population. The reason being is because the relative rates in accordance to state populations paint a different picture. Having the same numbers of these accidents in Florida as Iowa would be alarming on Iowa's part if it was as high of a number as Florida. Context and the importance of it was the reason for the per capita breakdown, adding context to visualized data is one of what I feel to be, an essential and

 Module 2: Introduction to Tableau In this module, we discovered different ways of being able to visually represent data using a program called Tableau. I decided to take this assignment 'home' in a manner, and decided to use a dataset found through the Google Data Search from a national database for DUI statistics between the years 2005-2014. This unfortunately hits home for me as I have a few friends of mine who have made some poor choices with drinking and driving and have been hurt. Luckily, none of them have passed from their injuries and have since recovered physically and spiritually to become better individuals. I decided to create two different maps; The first consists of a color coded map at which the hue of each state dictates its metrics intensity. The metrics used for the visualization were the number of occupant deaths in these accident (perpetrator and victim combined) and the impaired driver death rate. The output for the 'heat map' is as follows, and I

 Module 2 Assignment  The overall outcome to this assignment was finding the following: The function in question myMean, is completely functional and correct. The reasoning behind this finding is because upon testing and a re-test that I came up with to ensure its accuracy, all numeric results were identical and equal. I broke the function into its respective parts: length() and sum() and reassigned them to arbitrary variables/objects to create a test to see if the function you had created was indeed viable. The test was a success and thus, the function is viable. My GitHub Repository:  https://github.com/tahousex/RProgramming2023/blob/8a5a6c853338ee18ee0b8287f3ef11e91a8ae2d8/Module%202.R

R Programming First Blog Post Assignment   Repository Location: https://github.com/tahousex/RProgramming2023 I have had you as a professor in previous semesters so my R Studio and R console is all up to date.