Page 143 - DLIS401_METHODOLOGY_OF_RESEARCH_AND_STATISTICAL_TECHNIQUES

Methodology of Research and Statistical Techniques

Notes

Notes The only difference between the cumulative frequency curve and ogive is that for
cumulative frequency curve, on vertical axis, we take cumulative frequencies, while
in case of ogive we also have to take cumulative percentages.

Self Assessment

Multiple Choice Questions:
1. The most common form of graphical presentation of data is ........................ .

(a) Frequency polygon (b) Histogram
(c) Bar diagram (d) Bar graph.
2. For plotting a ........................ as in case of histogram, the values of the variable are taken
on the horizontal axis of the graph and frequencies are taken on the vertical axis of the
graph.
(a) Histogram (b) Bar graphs

(c) Frequency polygon (d) Pie charts.
3. ........................ are frequently used for pictorial presentation of discrete data.
(a) Bar graphs (b) Pie charts
(c) Histogram (d) Frequency polygon.

9.4 Unvaried and Multivariate Tables

The main use of Tables is to obtain univariate or bivariate frequency tables with optional row,
column and corner percentages and optional univariate and bivariate statistics. Tables of mean
values of a variable can also be obtained.
Both univariate/bivariate tables and bivariate statistics can be output to a file so that can be
used with a report generating program, or can be input to Graph ID or other packages such
as Excel for graphical display.
Univariate Tables: Both univariate frequencies and cumulative univariate frequencies may be
generated for any number of input variables and may also be expressed as percentages of the
weighted or unweighted total frequency. In addition, the mean of a cell variable can be obtained.

Bivariate Tables: Any number of bivariate tables may be generated. In addition to the weighted
and/or unweighted frequencies, a table may contain frequencies expressed as percentages
based on the row marginals, column marginals or table total, and the mean of a cell variable.
These various items may be placed in a single table with a possible six items per cell, or each
may be obtained as a distinct table.
Multivariate

Multivariate Data Analysis refers to any statistical technique used to analyze data that arises
from more than one variable. This essentially models reality where each situation, product, or
decision involves more than a single variable. The information age has resulted in masses of
data in every field. Despite the quantum of data available, the ability to obtain a clear picture
of what is going on and make intelligent decisions is a challenge.

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