(M)BA - Learning with SPSS : TEAM A

What is Business analytics?

As defined by Wikipedia, “Business analytics (BA) refers to the skills, technologies, applications and practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning.”

In short, it helps people like us to make informed business decisions and may be help automate few business processes.   An excellent data analysis could be an asset for the company which they could leverage it as competitive advantage. A SURE PROMOTION TIP :)

Different BA tools:

1)      Many commercial products available

SAS, Statistica, Minitab, and others

2)      Excel

Widely available (part of MS Office Suite)

Not a statistical software – spreadsheet (Finance, math, and statistics applications)

3)      SPSS

Robust software for sophisticated statistical applications.

SPSS:

What IBM says “With SPSS predictive analytics software, you can predict with confidence what will happen next so that you can make smarter decisions, solve problems and improve outcomes”

SPSS refers to the Statistical Package for the Social Sciences. This package can perform a number of statistical operations and calculations.
SPSS Statistics was developed by Norman H. Nie, C.Hadlai and Dale Bent and released in 1968. This software is widely used by people working in the field of social sciences. Others users of this software are market researchers, survey companies, Government Agencies, health researchers, educational researchers, and marketing organizations.

Unique Features:

1)      User-friendly statistical software.

2)      Store your instructions in the form of syntax.

3)      Important tests such as t-test, f-test, chi-square test and cross-tabulation can be performed.

4)      One can work with missing data

5)      Performs discriminant analysis, analysis of variance, and factor analysis.

Types of Analytics:

1)      Operational analytics

2)      Customer Analytics

Operational Analytics:

How can it help operations?

1)      Streamline operational processes to meet ever-changing customer demands

2)      Optimize your production and distribution channels

3)      Overcome short-term stresses or unexpected marketplace changes

4)      More effectively allocate capital and human resources

DAY 1:

Basics about SPSS:

Variables and Cases:

SPSS uses data organized in rows and columns. The rows are called cases and the columns variables.

The case contains information for one unit of analysis like person, animal etc while variables are the information collected for each case such as age, sex etc.

Variable types

 It includes Dots, Commas, Strings, etc. in the figures.

Width  : This helps us to show the number of characters that can be put in the cell.

Label  : It helps us to provide a detailed description of the variable.

Value  : This is generally used for the items which can be categorised. 

Values can be divided into:

1)    Category - for First level analysis.

It is one whose range is countable.

2)    Continuous -for Second level analysis.

It is one which is not categorical.

The continuous variable can be further categorised into Continuous and Discrete.

There are two views in SPSS :

1)    Data view:

Data View is the view in which we view and edit the actual data. This data can also be populated by importing excel files. Each column depicts a variable.

2)    Variable view:

Variable View can be accessed by using the tab given on the lower left corner. In this view, each variable is represented as a row, and various properties of the variable are represented as columns, allowing us to change the properties of existing variables or establish properties for new variables.

Types of Measures:

1)    Nominal:

 It is simply placing data into categories, without any order or structure.

Examples: A YES/NO scale is  nominal. It has no order and there is no distance between YES and NO.

2)    Ordinal:

In this scale values are given based on an order. An ordinal scale only lets you interpret gross order and not the relative positional distances. Ordinal data would use non-parametric statistics. These would include

3)    Scale:

This scale tells us the difference between variables.  

Types of Analysis :

1)Univariate analysis is the simplest form of quantitative analysis. It is carried out with the description of a single variable and its attributes of the applicable unit of analysis.

2)Bivariate analysis  or multivariate analysis.

Hoping this blog was useful to you.  

Thanks,

Ankur Gopal Chandra Mundra

14009

Team A