Summary of day two:

1. Mohan Raj Pradhan: Overview of SPSS:

- Loading of SPSS generates two windows:

- The data editor (where you input your data and carry out statistical functions)

- And the output window (this is where results of any analysis will appear)

- The various functions of data editor and output windows can be achieved by menu bar and tool bar.

- Among the menu bar, one of the important menus is Help system. This is looked under problems, when something is not working

- Design a coding scheme

We gather data through questionnaire. To analyze data obtained through questionnaire a coding scheme has to be developed.

A coding scheme is a way to associate a particular data code with a questionnaire response.

Coding schemes are arbitrary. It may be alphabetic or numeric. However, it is recommended to use numeric coding scheme.

Mr. Samir K. C.

Editor window:

The data editor window can be divided into two parts: Data view and variable view

In the data view, actual data is entered and in the variable view, properties of a variable are defined.

One of the important properties of variable is value label, described under the heading values. Here name of value and corresponding numeric value defined in the coding scheme of a variable will be entered.

Modifying data values:

Data received from various sources may not always be in the best format for analysis and reporting.

SPSS allows to:

- change data by combining several categories into one category; or

- by changing the coding scheme for a variable.

You can choose to assign the new values to the existing variable or to a new variable.

This action is requested by RECODE procedure.

Mr. Naveen Shrestha

Described about relationship of data and statistics.

Data itself is meaningless but whenever it is processed, which is meaningful to somebody then it becomes information. Statistics helps in processing data in a meaningful way. He also broadly divided the data into two categories:

Quantitative and the other qualitative, which may further be divided into nominal and ordinal for quantitative data and discrete and continuous for qualitative data.