Introduction to Applied Statistics
Daniel J. Denis · 2020
This chapter gives a concise introduction to the world of applied statistics as they are generally used in scientific research. It provides an understanding the logic of statistical inference, the purpose of statistical modeling, and where statistical inference fits in the era of “Big Data.” Due to the high volumes of data able to be collected in industries, some data sets can be extremely large, and in some cases be near representations of actual populations. The chapter shows how statistical modeling is used in scientific pursuits. The job of an applied statistician is twofold: fit a model to sample data, and calculate how well that model fits the data; and determine whether the sample model generalizes well to the population from which the sample model was built. The chapter also discusses statistical significance testing, and helps to distinguish between point estimates and confidence intervals.