2 Components of Applied Statistics

Let’s first cosnider the central challenges of applied statistics, shown in the following schematic I’ll call the “central dogma of applied statistics”, shown in Figure 2.1

Central Dogma of Statistics

Figure 2.1: Central Dogma of Statistics

2.1 Study Design

An applied statistics project is usually preceded by a scientific question that involves the collection and analysis of data. The design of the data should involve careful application of statistical principles to design which data are to be collected and how the data will be measured. The study design should also be driven by the questions that will be answered and the type of applied statistical analysis techniques will be employed.

Study design is an area that is almost solely studied by statisticians and it is one of the core strengths of the field of statistics. We will be considering study design throughout this book.

2.2 Data Wrangling

Data wrangling is a new terms that refers to the process of convertng raw data, which is often very messy, into data that can be readily analyzed. The importance of this activity has grown substantially in recent years as data sets have becoem larger and more comoplex. Data wrangling

2.3 Data Analysis

2.3.1 Exploratory Data Analysis

2.3.2 Modeling

2.3.3 Inference

2.3.4 Prediciton

2.4 Communication