What this book covers

Chapter 1, An Introduction to Stata and Data Analytics, gives an overview of Stata programming and the various statistical models that can be built in Stata.

Chapter 2, Stata Programming and Data Management, teaches you how to manage data by changing labels, how to create new variables, and how to replace existing variables and make them better from the modeling perspective. It also discusses how to drop and keep important variables for the analysis, how to summarize the data tables into report formats, and how to append or merge different data files. Finally, it teaches you how to prepare reports and prepare the data for further graphs and modeling assignments.

Chapter 3, Data Visualization, discusses scatter plots, histograms, and various graphing techniques, and the nitty-gritty involved in the visualization of data in Stata. It showcases how to perform visualization in Stata through code and graphical interfaces. Both are equally effective ways to create graphs and visualizations.

Chapter 4, Important Statistical Tests in Stata, discusses how statistical tests, such as t-tests, chi square tests, ANOVA, MANOVA, and Fisher's test, are significant in terms of the model-building exercise. The more tests you conduct on the given data, the better an understanding you will have of the data, and you can check how different variables interact with each other in the data.

Chapter 5, Linear Regression in Stata, teaches you linear regression methods and their assumptions. You also get a review of all the nitty-gritty, such as multicollinearity, homoscedasticity, and so on.

Chapter 6, Logistic Regression in Stata, covers how to build a logistic regression model and what the best business situations in which such a model can be applied are. It also teaches you the theory and application aspects of logistic regression.

Chapter 7, Survey Analysis in Stata, teaches you different sampling concepts and methods. You also learn how to implement these methods in Stata and how to apply statistical modeling concepts, such as regression to the survey data.

Chapter 8, Time Series Analysis in Stata, covers time series concepts, such as seasonality, cyclic behavior of the data, and autoregression and moving averages methods. You also learn how to apply these concepts in Stata and how to conduct various statistical tests to make sure that the time series analysis that you performed is correct.

Chapter 9, Survival Analysis in Stata, teaches survival analysis and different statistical concepts associated with it in detail.