The document discusses different techniques for analyzing qualitative and quantitative data. It outlines several types of descriptive statistics that can be used to analyze descriptive research data, including frequencies, central tendencies, and variabilities. Correlational research data can be analyzed using correlations, while experimental research data can be analyzed using t-tests, analysis of variance, chi square tests, and other statistical analyses. Multivariate research makes use of multiple regression, discriminant analysis, and factor analysis to examine relationships between multiple variables. The appropriate analysis depends on the type of research design used.

1. Analyzing the data
Analyzing qualitative research data
The data is usually in the form of
words in oral or written modes and
comes in different forms.
Typical of all qualitative analyses is
that at different stages of the
analysis the researchers identify,
delimit, and sort the relevant
segments of the text according to an
organizing scheme.
Two types of techniques can be
identified in analyzing qualitative
data.
1.- Deriving a set of categories for
dealing with text segments form the text
itself.
2.- An ordering system for the data content.
Analyzing descriptive research data Data obtained from descriptive
research are generally analyzed with
the aid of descriptive statistics.
Descriptive statistics
It refers to a set of procedures which are
used to describe different aspects of the
data. Types of of descriptives statistics
1.- Frequencies
Provide information on how common
certain phenomena are and central
tendencies provide information on the
average behavior of the subjects on
certain tasks.
2.- Central tendencies
Provide information about the average
and the typical behavior of subjects in
respect of a specific phenomenon.
3.- Variabilities
Provide information on the spread of the
behaviors or the phenomena among the
subjects of the research.
Analyzing Correlational research data
Analyzing experimental research data
The t-test
Correlations
It is used to compare the means of two
groups. It helps determine how
confident the researcher can be that the
differences found between two groups
as a result of a treatment are not due to
chance.
One way analysis of variance
It is used to examine the differences in
more than two groups. It specifically
indicates how confident the researcher
can be that the differences observed
among two experimental groups, for
example.
Factorial analysis of variance
It is capable of analyzing data obtained
from experimental research comparing
either two groups or more than two
groups.
Chi square
It is a data analysis procedure which
helps the researcher address questions
about relations between two nominal
variables.
They are used for analyzing data
obtained from descriptive research
which examines existing relationships
between variables, with no manipulation
of variables.
Data analysis and the design of the study
Data analysis
It refers to sifting, organizing,
summarizing, and synthesizing the data
so as to arrive at the results and
conclusions of the research.
The data analysis becomes the product
of all the considerations involved in the
design and planning the research.
Research Designs
Ethnographic
Descriptive
Correlational
Multivariate
Experimental
Analyzing multivariate research data
Multiple Regression
Through multiple regression analysis it
is possible to examine the relationship
and predictive power of or more
independent variables with the
dependent variable.
Discriminant Analysis
It is concerned with the prediction of
membership in one or two independent
variables.
Factor Analysis
It helps the resercher make large sets of
data more manageable by identifying a
factor or factors that underline the data.
Analyzing the data.mmap - 03/11/2014 - Mindjet