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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

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Analyzing the data

  • 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