Describing Quantitative and Qualitative Data

This chapter introduces the classification of data into various categories, such as qualitative and quantitative, and aims to apply appropriate graphical and numerical techniques to analyze them. It looks at both inferential and descriptive methods applicable to the various types of data. Practitioners applying statistics in a professional environment often become overwhelmed by the large data sets they have collected. Numerical methods provide information about what are commonly known as quantitative or numerical measures. Measures of centrality give us information about the center of the data, whereas measures of dispersion provide information about the variation within the data. The chapter considers four important probability distributions that are useful in the field of statistical quality control. These are the binomial distribution, hypergeometric distribution, Poisson distribution, and normal distribution. Among discrete probability distributions, the binomial distribution is very useful and important.