The document discusses various types of errors in educational research, categorizing them into sampling, measurement, statistical, and interpretation errors. It emphasizes the importance of sampling techniques, the influence of measurement errors on individual scores, and the role of statistical methods in analyzing data relationships. Additionally, it highlights the need for clear interpretation of statistical results and decision-making regarding the null hypothesis.

2. Errors in conducting research in education may
be grouped under the following headings:
1)Sampling Errors;
2)Measurement errors;
3)Statistical errors;
4)Interpretation errors

3. Sampling is the part of the strategy of
research.
The process of selecting the fractional
part is called a sampling.
 Sampling Error is governed by
technique of sampling and size of
sample.
 While the technique of sampling is
important for experimental studies
the important in survey type studies.

4. Equivalent Groups
Pre-and Post-Test
Rotational Procedure
Appropriate Sampling Device
Statistical Tests

5. Measurement error influences an
individual scores. In Behavioral
sciences measurement is indirect.
Enumerable Human traits and
variables are measured through the
behavior. A test cannot measure
purely the same trait. Thus, the
standardized tests involve the error
of measurement.

6. Large sample
Proper Tool
Nature of Variable
Selection of a measuring instrument

7. In conducting a research study in
behavioral sciences the statistics is not
a master but a servant.
 Nature of a data decides a
applicability of a statistical technique.
 It depends on a nature of trait
measured: variable or attribute.
 Some traits are measured at nominal
scale by using questionaire,interview
and schedule.

8. Use of Parametric Statistics
Use of Non-Parametric Statistics

9.  Scientific studies analyses the relationship
of different sets of variables, which is of
two types: Descriptive relationship and
Functional relationship.
 Cause-effect relationship is established
while interpreting the data.
 The Interpretation of data means to
verbally communicate the meaning of results
obtained in terms of statistical data, but it
is observed that extrapolation rather than
interpretation of data.

10.  Decision may be taken about the acceptance
and rejection of Null hypothesis.
 Decision may be taken whether there is
relationship between variables or the
difference between the two groups or among
groups is highly significant or not.
 Words used in the interpretation should
have a single meaning.
 In Interpretation and statistical results some
specification made by using other test of
significance(t-test , f-test etc.)

12. ©The Economist
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