Removing duplicate info and consolidating case study info.

intro.Rmd

@@ -4,7 +4,7 @@ The demand for skilled data science practitioners in industry, academia, and gov
 
 ## Case studies 
 
-Throughout the series, we use motivating case studies. For each of the concepts covered, we start by asking specific questions and answer these through data analysis. We learn the concepts as a means to answer the questions. Examples of the case studies included in the book are:
+Throughout the series, we use motivating case studies. In each case study, we try to realistically mimic a data scientist’s experience. For each of the concepts covered, we start by asking specific questions and answer these through data analysis. We learn the concepts as a means to answer the questions. Examples of the case studies included in the book are:
 
 | Case Study | Concept | 
 | ---- | ---| --- |
@@ -19,8 +19,6 @@ Throughout the series, we use motivating case studies. For each of the concepts
 | MNIST: Image processing hand written digits | Machine Learning |
 | Movie recommendation systems | Machine Learning | 
 
-We use the R software environment for all our analysis. You will learn R, statistical concepts, and data analysis techniques simultaneously. By working through the examples, we gain experience in R and packages such as __dplyr__,  __ggplot2__, and __caret__. In each case study, we try to realistically mimic a data scientist’s experience.
-
 ## Who will find this book useful? 
 
 This book is meant to be a textbook for a first course in Data Science. No previous knowledge of R is necessary, although we do assume some experience with programming. The statistical concepts used to answer the case study questions are only briefly introduced, so a Probability and Statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand all the chapters and complete all the exercises, you will be well positioned to perform basic data analysis tasks and you will be prepared to learn the more advanced concepts and skills needed to become an expert.