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HYPOTHESIS TESTING & CHARACTERISTICS:Correlational hypotheses

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Research Methods ­STA630
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Lesson 7
HYPOTHESIS TESTING & CHARACTERISTICS
We have already seen that propositions are statements about variables considered to be true or false. If
the phenomenon under consideration happens to be observable reality then the said statement could be
empirically tested. A proposition that can be verified to determine its reality is a hypothesis. Therefore
one can say that a hypothesis is a verifiable counterpart of a proposition.
A hypothesis may be defined as a logically conjectured relationship between two or more variables,
expressed in the form of a testable statement. Relationship is proposed by using a strong logical
argumentation. This logical relationship may be part of theoretical framework of the study.
Let us look at some of the hypotheses:
1. Officers in my organization have higher than average level of commitment (variable).
2. Level of job commitment of the officers is associated with their level of efficiency.
3. Level of job commitment of the officers is positively associated with their level of efficiency.
4.  The higher the level of job commitment of the officers the lower their level of absenteeism.
These are testable propositions. First hypothesis contains only one variable. The second one has two
variables which have been shown to be associated with each other but the nature of association has not
been specified (non-directional relationship). In the third hypothesis we have gone a step further where
in addition to the relationship between the two variables, the direction of relationship (positive) has also
been given. In the fourth hypothesis level of efficiency has been replaced with level of absenteeism, the
direction of relationship between the two variables has been specified (which is negative). In the
following discussion you will find these hypotheses being quoted as part of the examples.
Types of Hypotheses
i. Descriptive Hypothesis
Descriptive hypothesis contains only one variable thereby it is also called as univariate hypothesis.
Descriptive hypotheses typically state the existence, size, form, or distribution of some variable.
The first hypothesis contains only one variable.  It only shows the distribution of the level of
commitment among the officers of the organization which is higher than average. Such a hypothesis is
an example of a Descriptive Hypothesis.
Researchers usually use research questions rather than descriptive hypothesis. For example a question
can be: What is the level of commitment of the officers in your organization?
ii. Relational Hypothesis
These are the propositions that describe a relationship between two variables. The relationship could be
non-directional or directional, positive or negative, causal or simply correlational.
While stating the relationship between the two variables, if the terms of positive, negative, more than,
or less than are used then such hypotheses are directional because the direction of the relationship
between the variables (positive/negative) has been indicated (see hypotheses 3 and 4).  These
hypotheses are relational as well as directional. The directional hypothesis is the one in which the
direction of the relationship has been specified.
Non-directional hypothesis is the one in which the direction of the association has not been specified.
The relationship may be very strong but whether it is positive or negative has not been postulated (see
hypothesis 2).
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Research Methods ­STA630
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Correlational hypotheses
State merely that the variables occur together in some specified manner without implying that one
causes the other. Such weak claims are often made when we believe that there are more basic causal
forces that affect both variables. For example:
Level of job commitment of the officers is positively associated with their level of efficiency.
Here we do not make any claim that one variable causes the other to change. That will be possible only
if we have control on all other factors that could influence our dependent variable.
Explanatory (causal) hypotheses
Imply the existence of, or a change in, one variable causes or leads to a change in the other variable.
This brings in the notions of independent and the dependent variables. Cause means to "help make
happen." So the independent variable may not be the sole reason for the existence of, or change in the
dependent variable. The researcher may have to identify the other possible causes, and control their
effect in case the causal effect of independent variable has to be determined on the dependent variable.
This may be possible in an experimental design of research.
Different ways to state hypotheses
·
Hi motivation causes hi efficiency.
·
Hi motivation leads to hi efficiency.
·
Hi motivation is related to hi efficiency.
·
Hi motivation influences hi efficiency.
·
Hi motivation is associated with hi efficiency.
·
Hi motivation produces hi efficiency.
·
Hi motivation results in hi efficiency.
·
If hi motivation then hi efficiency.
·
The higher the motivation, the higher the efficiency
iii. Null Hypothesis
It is used for testing the hypothesis formulated by the researcher. Researchers treat evidence that
supports a hypothesis differently from the evidence that opposes it. They give negative evidence more
importance than to the positive one. It is because the negative evidence tarnishes the hypothesis. It
shows that the predictions made by the hypothesis are wrong. The null hypothesis simply states that
there is no relationship between the variables or the relationship between the variables is "zero." That is
how symbolically null hypothesis is denoted as "H0". For example:
H0 = There is no relationship between the level of job commitment and the level of efficiency. Or
H0 = The relationship between level of job commitment and the level of efficiency is zero. Or
The two variables are independent of each other.
It does not take into consideration the direction of association (i.e. H0 is non directional), which may be
a second step in testing the hypothesis. First we look whether or not there is an association then we go
for the direction of association and the strength of association. Experts recommend that we test our
hypothesis indirectly by testing the null hypothesis. In case we have any credibility in our hypothesis
then the research data should reject the null hypothesis. Rejection of the null hypothesis leads to the
acceptance of the alternative hypothesis.
iv. Alternative Hypothesis
The alternative (to the null) hypothesis simply states that there is a relationship between the variables
under study. In our example it could be: there is a relationship between the level of job commitment and
the level of efficiency. Not only there is an association between the two variables under study but also
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Research Methods ­STA630
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the relationship is perfect which is indicated by the number "1". Thereby the alternative hypothesis is
symbolically denoted as "H1". It can be written like this:
H1: There is a relationship between the level of job commitment of the officers and their level of
efficiency.
v. Research Hypothesis
Research hypothesis is the actual hypothesis formulated by the researcher which may also suggest the
nature of relationship i.e. the direction of relationship. In our example it could be:
Level of job commitment of the officers is positively associated with their level of efficiency.
The Role of the Hypothesis
In research, a hypothesis serves several important functions:
1. It guides the direction of the study: Quite frequently one comes across a situation when the
researcher tries to collect all possible information on which he could lay his hands on. Later on
he may find that only part of it he could utilize. Hence there was an unnecessary use of
resources on trivial concerns. In such a situation, hypothesis limits what shall be studied and
what shall not be.
2. It identifies facts that are relevant and those that are not: Who shall be studied (married
couples), in what context they shall be studied (their consumer decision making), and what shall
be studied (their individual perceptions of their roles).
3. It suggests which form of research design is likely to be the most appropriate: Depending
upon the type of hypothesis a decision is made about the relative appropriateness of different
research designs for the study under consideration. The design could be a survey design,
experimental design, content analysis, case study, participation observation study, and/or Focus
Group Discussions.
4. It provides a framework for organizing the conclusions of the findings:
The Characteristics of a Testable Hypothesis
·
Hypothesis must be conceptually clear. The concepts used in the hypothesis should be clearly
defined, operationally if possible. Such definitions should be commonly accepted and easily
communicable among the research scholars.
·
Hypothesis should have empirical referents. The variables contained in the hypothesis should
be empirical realities. In case these are not empirical realities then it will not be possible to
make the observations. Being handicapped by the data collection, it may not be possible to test
the hypothesis. Watch for words like ought, should, bad.
·
Hypothesis must be specific. The hypothesis should not only be specific to a place and
situation but also these should be narrowed down with respect to its operation. Let there be no
global use of concepts whereby the researcher is using such a broad concept which may all
inclusive and may not be able to tell anything. For example somebody may try to propose the
relationship between urbanization and family size. Yes urbanization influences in declining the
size of families. But urbanization is such comprehensive variable which hide the operation of so
many other factor which emerge as part of the urbanization process. These factors could be the
rise in education levels, women's levels of education, women empowerment, emergence of dual
earner families, decline in patriarchy, accessibility to health services, role of mass media, and
could be more. Therefore the global use of the word `urbanization' may not tell much. Hence it
is suggested to that the hypothesis should be specific.
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Research Methods ­STA630
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Hypothesis should be related to available techniques of research. Hypothesis may have
empirical reality; still we are looking for tools and techniques that could be used for the
collection of data. If the techniques are not there then the researcher is handicapped. Therefore,
either the techniques are already available or the researcher is in a position to develop suitable
techniques for the study.
·
Hypothesis should be related to a body of theory. Hypothesis has to be supported by
theoretical argumentation.  For this purpose the research may develop his/her theoretical
framework which could help in the generation of relevant hypothesis. For the development of a
framework the researcher shall depend on the existing body of knowledge. In such an effort a
connection between the study in hand and the existing body of knowledge can be established.
That is how the study could benefit from the existing knowledge and later on through testing the
hypothesis could contribute to the reservoir of knowledge.
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Table of Contents:
  1. INTRODUCTION, DEFINITION & VALUE OF RESEARCH
  2. SCIENTIFIC METHOD OF RESEARCH & ITS SPECIAL FEATURES
  3. CLASSIFICATION OF RESEARCH:Goals of Exploratory Research
  4. THEORY AND RESEARCH:Concepts, Propositions, Role of Theory
  5. CONCEPTS:Concepts are an Abstraction of Reality, Sources of Concepts
  6. VARIABLES AND TYPES OF VARIABLES:Moderating Variables
  7. HYPOTHESIS TESTING & CHARACTERISTICS:Correlational hypotheses
  8. REVIEW OF LITERATURE:Where to find the Research Literature
  9. CONDUCTING A SYSTEMATIC LITERATURE REVIEW:Write the Review
  10. THEORETICAL FRAMEWORK:Make an inventory of variables
  11. PROBLEM DEFINITION AND RESEARCH PROPOSAL:Problem Definition
  12. THE RESEARCH PROCESS:Broad Problem Area, Theoretical Framework
  13. ETHICAL ISSUES IN RESEARCH:Ethical Treatment of Participants
  14. ETHICAL ISSUES IN RESEARCH (Cont):Debriefing, Rights to Privacy
  15. MEASUREMENT OF CONCEPTS:Conceptualization
  16. MEASUREMENT OF CONCEPTS (CONTINUED):Operationalization
  17. MEASUREMENT OF CONCEPTS (CONTINUED):Scales and Indexes
  18. CRITERIA FOR GOOD MEASUREMENT:Convergent Validity
  19. RESEARCH DESIGN:Purpose of the Study, Steps in Conducting a Survey
  20. SURVEY RESEARCH:CHOOSING A COMMUNICATION MEDIA
  21. INTERCEPT INTERVIEWS IN MALLS AND OTHER HIGH-TRAFFIC AREAS
  22. SELF ADMINISTERED QUESTIONNAIRES (CONTINUED):Interesting Questions
  23. TOOLS FOR DATA COLLECTION:Guidelines for Questionnaire Design
  24. PILOT TESTING OF THE QUESTIONNAIRE:Discovering errors in the instrument
  25. INTERVIEWING:The Role of the Interviewer, Terminating the Interview
  26. SAMPLE AND SAMPLING TERMINOLOGY:Saves Cost, Labor, and Time
  27. PROBABILITY AND NON-PROBABILITY SAMPLING:Convenience Sampling
  28. TYPES OF PROBABILITY SAMPLING:Systematic Random Sample
  29. DATA ANALYSIS:Information, Editing, Editing for Consistency
  30. DATA TRANSFROMATION:Indexes and Scales, Scoring and Score Index
  31. DATA PRESENTATION:Bivariate Tables, Constructing Percentage Tables
  32. THE PARTS OF THE TABLE:Reading a percentage Table
  33. EXPERIMENTAL RESEARCH:The Language of Experiments
  34. EXPERIMENTAL RESEARCH (Cont.):True Experimental Designs
  35. EXPERIMENTAL RESEARCH (Cont.):Validity in Experiments
  36. NON-REACTIVE RESEARCH:Recording and Documentation
  37. USE OF SECONDARY DATA:Advantages, Disadvantages, Secondary Survey Data
  38. OBSERVATION STUDIES/FIELD RESEARCH:Logic of Field Research
  39. OBSERVATION STUDIES (Contd.):Ethical Dilemmas of Field research
  40. HISTORICAL COMPARATIVE RESEARCH:Similarities to Field Research
  41. HISTORICAL-COMPARATIVE RESEARCH (Contd.):Locating Evidence
  42. FOCUS GROUP DISCUSSION:The Purpose of FGD, Formal Focus Groups
  43. FOCUS GROUP DISCUSSION (Contd.):Uses of Focus Group Discussions
  44. REPORT WRITING:Conclusions and recommendations, Appended Parts
  45. REFERENCING:Book by a single author, Edited book, Doctoral Dissertation