Interpretation of Data

Statistical tools and Computational tools
Statistical software: SAS

Introduction:

Interpretation of data: Data exploration, summarization and inference, these are the main goals of the statistician.

See chapter 1 and 2 of the textbook. There are several motivating examples.

Software: SAS, R.

Others: MS Excel, SPlus, SPSS, Minitab, Stata, and many others.

Datasets:    Cases by Variables

	Variable 1	Variable 2	Variable 3
Case 1	1	A	2.5
Case 2	2	A	3.1
Case 3	1	B	2.7
.	.	.	.
.	.	.	.
.	.	.	.
Case  n	.	.	.

In SAS (or SPSS) the basic data unit is the case. Data is stored in SAS(or SPSS) data files.

Data Input:

• Import Data Menu or Program Code.
• Text files, Excel.
• Local Relational databases. They can be used in SAS by combining SAS Datasets.
• Network Databases. Suppose you work with data from a large company (and small too). Examples of these are telecom companies, the census bureau, and companies working in Internet applications, Market research and so on.  Data is stored in large databases and you access the data through the Internet or some local area network. This allows for real time applications.
• Internet data capture via software, spider webs...

Software:

· An Introduction to SAS

· An Introduction to R