4. HYPOTHESIS
A supposition or proposed explanation made on the basis of
limited evidence as a starting point for further investigation.
1) NULL HYPOTHESIS
2) ALTERNATIVE HYPOTHESIS (Directional, Non-
directional)
5. NULL HYPOTHESIS
A null hypothesis states that there is no difference between
certain characteristics of a population. It states that there is no
relationship between measured phenomena. If a significant
relationship is found among the variables, the null hypothesis is
rejected and an alternate hypothesis is accepted.
Example - There will not be a significant difference in
emotional intelligence among high and low achievers.
7. Directional hypothesis
A directional hypothesis is a prediction made by a researcher
regarding a positive or negative change , relationship or difference
between two variables of a population. This prediction may be
made on the basis of past research, reasoning, personal
observation etc. It is also known as one-tailed test. A test of
significance to determine whether there is a relationship between
the variables in one direction.Here the direction is predicted.
Example - The emotional intelligence of high achievers will be
higher than low achievers.
8. NON DIRECTIONAL HYPOTHESIS
It states that the independent variable will have an effect on the
dependent variable, but the direction of the effect is not specified.
Also known as two tailed hypothesis.
Example - Emotional intelligence varies among high and low
achievers.
10. TOOLS
They are used for data collection, to understand behaviour and mental
process. They include paper pencil questionnaires, computer assisted
questionnaires, rating scales, interview schedules, checklists, survey
forms, psychological tests, equipments like blood pressure monitors
etc.
In some of the tools as in questionnaires, use different types of
measurement scales to collect data.
11. TYPES OF DATA & MEASUREMENT SCALES
1) NOMINAL SCALE
2) ORDINAL SCALE
3) INTERVAL SCALE
4) RATIO SCALE
12. NOMINAL SCALE
Nominal scale is a qualitative measurement scale. It has no
numerical value, for example – gender, sex, marital status etc.
13. ORDINAL SCALE
In ordinal scale-information is arranged in a
specific order, we rank each parameters or
variables in comparison to one another. But the
value difference between two variables cannot
be calculated. For example the order of size -
small, medium, large, very large. LIKERT SCALE is
a commonly used ordinal scale.
Speaker notes
14. INTERVAL SCALE
It supports statistical test. It not only shows the
order and direction of the variables or parameters
but also the exact difference between the value
points. The difference between each value point will
be equal. For example the difference between 10
degree celsius 20 degree C is the same as that of 30
degree C and 40 degree C. Measurements like
length, IQ test values etc.
15. RATIO SCALE
Ratio scale is almost like interval scale. But it has an
absolute zero characteristic. For eg. height, weight etc. But
not temperature because 0 degree does not mean it is
neither hot nor cold. Does not have negative values. Mean,
median and mode can be calculated using it.
17. RELIABILITY
Reliability is about the consistency of a
measure.It means if we use the same scale
multiple times, we should get almost the same
result each time.
Using it multiple times may be done in different ways.
19. TYPES OF RELIABILITY
INTER RATER RELIABILITY - Same test administered
to different people who belong to the same
population.
TEST RETEST - administered to same sample
during different times.
SPLIT HALF - test items are split into two and given
to the same sample and the result is correlated.
20. TYPES OF RELIABILITY
PARALLEL FORMS - The sample is given another
version of the test and the result is correlated.
Tests that measure the same traits.
INTERNAL CONSISTENCY - it is a correlation
based on the different items on the same test.
Measures whether different items measures the
same construct.
21. VALIDITY
validity is about the accuracy of a measure. A
test is said to be valid if it measures what it
intends to measure.
For eg. A test on IQ should measure IQ and it should not contain
items that intends to measure empathy.
23. CONSTRUCT VALIDITY
A construct is a characteristic that can not be observed
directly. It can be measured through observing the indicators
that are associated with it. It ensures that the method of
measurement is in line with the construct that one want to
measure. The tool should contain only relevant questions that
measure the known indicators of the construct that one want
to measure.
For eg. EI cant be observed directly.. We measure it through the indicators of eI such as
managing relationship, empathy etc. So the tool should contain relevant items that measures
those indicators.
24. CONTENT VALIDITY
It is related to the comprehensiveness in the measurement of
the construct. If some aspects are missing or if some irrelevant
aspects are added the validity is at risk. The measurement
method must contain all relevant indicators of the construct
that you are going to measure.
For eg. If one is measuring IQ, if we leave the reasoning ability or
if we add self-confidence in that-the validity will be at risk.
25. FACE VALIDITY
Face validity considers how suitable the content of a test
seems to be on the surface. It is a more informal and
subjective assessment.
For eg. The items in an IQ test should seem to be measuring
IQ.
26. CRITERION VALIDITY
It evaluates the result of your test with that of another test which
measures the same thing - usually a test which is widely used and an
established one.The validation is done through correlation of both results.
For eg. you prepared an intelligence test and you want to check
criterion validity. Then you correlate the results of your sample with
the result of Wechsler scale using the same sample.
27. INTERNAL AND EXTERNAL VALIDITY
Internal validity refers to the degree of confidence in the causal
relationship being tested is trustworthy. It ensures that it is not
influenced by other variables or a pure coincidence.
External validity is the extent to which the result of a study can be
generalised to other samples, situations, area etc.
28. PROCEDURE
Administration of tools on selected
sample, considering ethical issues,
considering time schedule etc.
Administering intervention module if any.
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Editor's Notes
The alternative hypothesis states that students will recall significantly more information on a Monday morning than on a Friday afternoon. The null hypothesis states that there will be no significant difference in the amount recalled on a Monday morning compared to a Friday afternoon. States that there is a statistical significance between two variables. Non-directional hypothesis predicts that the independent variable will have an effect on the dependent variable, but the direction of the effect is not specified. E.g., there will be a difference in how many numbers are correctly recalled by children and adults. (www.simplypsychology.org)
Strictly speaking likert scales cannot be used for statistical analysis. But it is considered as an interval scale widely for social science research.
strictly speaking, ordinal data has a median and mode only, and nominal data has only a mode. However, a consensus has not been reached among statisticians about whether the mean can be used with ordinal data, and you can often see a mean reported for Likert data in research.