Discrete data may be also ordinal or nominal data (see our post nominal vs ordinal data). For example, Poisson distribution is the commonly known pmf, and normal distribution is the commonly known pdf. Statistics and Exploratory Data Analysis. Classes of Statistical Problems 1 1.2. These distributions in statistical data analysis help us to understand which data falls under which distribution. The use of graphs and summary statistics for understanding data is an important first step in the undertaking of any statistical analysis. Section 4 considers some advanced topics in the statistical design and analysis of discrete-response CV data that are both of practical interest and on the current frontiers of research. In statistics, data is defined as the facts and figures collected together for the purpose of analysis. Examples 3 1.3. Review of Discrete Distributions 14 The value of the chi-square statistic is 49.731, with 5 degrees of free-dom and p = 0.000 (this would be reported as p < 0.001), and thus we reject the null hypothesis of no association and conclude that there is a relationship between crime and drinking status. Good research practices for the statistical analysis of DCE data involve understanding the characteristics of alternative methods and ensuring that interpretation of the results is accurate, taking into account both the assumptions made during the course of the analysis and the strengths and limitations of the analysis method. There are various pdf’s and pmf’s in statistical data analysis. Outliers are extreme Further Thoughts on Experimental Design ... - to see patterns in the data - to find violations of statistical assumptions - to generate hypotheses ... Categorical Quantitative binary nominal ordinal discrete continuous 2 categories more categories order matters numerical uninterrupted. In the data collection and data analysis, statistical tools differ from one data type to another. It is divided into two broad categories, qualitative data, and quantitative data.Further, the qualitative data is cannot be measured in terms of numbers and it is sub-divided into nominal and ordinal data. For example, it is useful for understanding the main features of the data, for detecting outliers, and data which has been recorded incorrectly. Discrete data is graphically displayed by a bar graph. the results after the data have been collected, based on the principles of optimal experimental design. Contents Preface xi 1 Introduction 1 1.1. When the values of the discrete data fit into one of many categories and there is an order or rank to the values, we have ordinal discrete data. The Statistical Analysis of Discrete Data With 30 Illustrations Springer-Verlag New York Berlin Heidelberg London Paris Tokyo Hong Kong . 2. Section 5 offers some brief conclusions. In Table 5.3, we show the statistical results related to the analysis of these data.