Learn Business Analytics in Six Steps Using SAS and R: A Practical, Step-by-Step Guide to Learning Business Analytics - Softcover

Inhaltsangabe

Chapter Description and Details

1 The Process of Analytics: DCOVA and I

1.1 What is analytics?

1.2 The process of Analytics

1.2.1 Define

1.2.2 Collect

1.2.3 Organize

1.2.4 Visualize

1.2.5 Analyze

1.2.6 Insight

2 Accessing SAS and R

2.1 Why SAS and R

2.2 History of SAS and R

2.3 Installing SAS and R

3 Data Manipulation using SAS and R: Collecting and Organizing the Data

3.1 Data flow from ERP to Business Analytics SaaS

3.2 Sanity check on data

3.3 Merging datasets

3.4 Missing values, Duplication , Outliers

3.5 Project datamart

4 Discover basic information about data

4.1 Descriptive statistics , measures of central tendency, measures of variation

4.2 How to generate them using:

4.2.1 SAS

4.2.2 R

5 Visualisation

5.1 Graphs and charts

5.2 How to create effective graphs and charts using:

5.2.1 SAS

5.2.2 R

5.3 Correlation and co-variance

5.4 How to create graphical and numeric outputs for correlation and co-variance using

5.4.1 SAS

5.4.2 R

6 Analyze: Probability and Distributions

6.1 Concepts of probability

6.2 How to generate probability using:

6.2.1 SAS

6.2.2 R

6.3 Concepts of distributions

6.4 Normal distributions

6.5 How to work on distributions using:

6.5.1 SAS

6.5.2 R

7 Analyze: Sampling and Sampling Distributions

7.1 Sampling and sampling distributions

7.2 Hypothesis testing

7.3 How to work on sampling and hypothesis testing using:

7.3.1 SAS

8 Analyze: Confidence Interval

8.1 Concept of confidence interval

8.2 How to work in confidence intervals using

8.2.1 SAS

8.2.2 R

9 Insight Generation

9.1 What type of conclusions can be drawn by the analysis

9.2 Interpreting results generated by:

9.2.1 SAS

9.2.2 R

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.