3 Descriptive Statistics
Descriptive statistics serve as the cornerstone of data exploration. This chapter covers the tools used to summarize and visualize data, including measures of central tendency, dispersion, and shape. We emphasize the importance of choosing appropriate graphical techniques to identify patterns, outliers, and relationships. The chapter also includes procedures for assessing normality and a primer on bivariate analysis, laying the groundwork for later inferential methods. Real-world business examples illustrate how descriptive techniques provide insight and guide further analysis.
When you have an area of interest to research, a problem to solve, or a relationship to investigate, theoretical and empirical processes will help you.
Estimand is defined as “a quantity of scientific interest that can be calculated in the population and does not change its value depending on the data collection design used to measure it (i.e., it does not vary with sample size, survey design, the number of non-respondents, or follow-up efforts).” (Rubin 1996)
Examples of estimands include:
- Population means
- Population variances
- Correlations
- Factor loadings
- Regression coefficients
This chapter is fully available in the published Springer volumes.
The online preview is limited per publisher guidelines.
To access the complete content, purchase the book on Springer:
| Vol. | Title | Link |
|---|---|---|
| 1 | Foundations of Data Analysis | Buy on Springer |
| 2 | Regression Techniques for Data Analysis | Buy on Springer |
| 3 | Advanced Modeling and Data Challenges | Buy on Springer |
| 4 | Experimental Design | Buy on Springer |