Graphing Statistical Distributions in Excel - The Excel Statistical Master (Paperback)

Clear and thorough instructions about how to create interactive graphs in Excel of the eight most popular statistical distributions. These distributions include the Normal Distribution, the t Distribution, the Binomial Distribution, the Chi-Square Distribution, the Poisson Distribution, the Weibull Distribution, the Exponential Distribution, and the Hypergeometric Distribution. You will learn to make interactive graphs in Excel of both the PDF and CDF (Probability Density Function and Cumulative Distribution Function) for most of these statistical distributions. The interactive Excel graphs that you will soon be able to construct will allow you to vary each and every one of the distribution's parameters right on the spreadsheet and watch the distribution's Excel graph instantaneously change shape as a result of the new parameters that you just entered. For example, you will be able to vary either of the Normal Distribution's two parameters, the mean and standard deviation, and then watch how the new parameters instantly change the shape of the graph on the Excel spreadsheet. It is an outstanding way to quickly master all of the distributions and fully understand what effect each parameter has on the shape of the graph of a particular distribution. One entertaining example of this is to watch the Chi-Square Distribution's graph resemble a wave rolling from left to right across the spreadsheet as the Chi-Square Distribution's only parameter, its degrees of freedom, is increased. You'll see exactly how to graph each distribution by simply following the numerous screen shots throughout this manual. The beginning of this manual has a special section which provides detailed instructions about how to create the graph of a generic distribution on a Excel spreadsheet. It is a lot simpler than you might imagine. This manual will make you an Excel Statistical Master at creating user-interactive graphs in Excel of the eight most well-known statistical distributions.