In this study we explore the use of statistics concepts and statistical software to visualize the behavior of security prices and apply this in making investment decisions. It was assumed that the distribution of security prices can be described by existing statistical distributions. Stock prices for the Microsoft Corporation from the year 2000 - 2015 was used as sample data to decide which distribution best describes the sample plot. Considering stock prices to be random variables, we used the Dynamic Distribution package in the R software (a package having functions that analyze dynamic probability distributions and their moments) to illustrate our view of the stock prices' sensitivity to changes in certain parameters. From graphs of past price movements, we were then be able to observe the lognormal distribution as the distribution that would best predict future stock prices even though it is high well known fact that stock prices can be very volatile. The Geometric Brownian Motion was also mentioned briefly as a model used for studying the movement of stock prices over time.