Session I & II - Group F

Business Analytics Session I & II- SIBM Bangalore

Expectations :-

My expectations from the start were that we will be learning how to analyze data and also how to formulate strategies based on the data analyzed.

The agenda of today's class was a brief introduction into Business Analytics where our professor said - "Output is more important and how to build strategy from it."We learnt the primary difference between analyzing data and processing data, wherein analzying is actually deriving some meaning out of the data and processing is just number crunching. 

Below area the topics covered in class today ( in brief):-

Record= Cases + Variable

Classification of variable:-

   1.  Category variable- must have limited number of values to be considered as a category example- language,     religion, months etc

   2.   Continuous- infinite values example- marks, age, etc

·         Continuous- infinite values including fractions eg- salary

·         Discrete- infinite values with whole numbers eg- age

Measures

•     Nominal- only name sake( where I have the freedom to assign), can give any number eg- gender, player’s jersey numbers, relationship status, mobile number, etc.
•     Ordinal- shows us the order, car number plate, etc
•      Scale- Eg- distance, weight height

   

    Rules for data entry (Some of the rules taught in Sessions I and II today)

•     As far as possible all variables should be numeric variable. For example, Male and Female can be denoted as M-1 and F-0
•      Once u get data, go to variable view and check out the label

Analytical techniques classification

I.

• Univariate technique- use only one variable eg- pie chart and the variable is shown by the size of the slice
• Bivariate- Uses two variables examples correlation, t-test, pie chart can also be used here. But not more than two variables. Better than univarite
•  Multi variate- uses multiple variables example bubble chart(more bubbles more insight into the data). Better than bivaraite

II.

• First level- simple analysis consisting of frequencies, Xtabs, OLAP cubes. Very important       
• Second level- multi-variate techniques

Rules for analysis ( one of the rules done in the Session I and II today)

Null hypotheses in case of cross tabs the two variables chosen will not have any relation.If Significance value is  more than .05 then there is significance difference, therefore the Hypo is rejected i.e., there is a relation between age and gender for marriage.

By 

Beenu Sabharwal

SIBM B

14014