This document lists the academic qualifications of Dr. Mohammad Khasro Miah. It includes two post-doctoral degrees in Human Resource Management from Fulbright Commission, Northeastern University and Japan Society for the Promotion of Science at Nagoya University. It also lists a Ph.D. in Human Resource Management from Nagoya University as well as several Master's degrees and a Bachelor's degree, all related to business or management. The qualifications are submitted to Dr. Mohammad Khasro Miah.

1. Submission to:
Dr. Mohammad Khasro Miah
Post-doctoral Degree in Human Resource Management
Awarded by Fulbright Commission, Northeastern University, Boston, USA
Post-doctoral Degree in Human Resource Management
Awarded by Japan Society for the Promotion of Science (JSPS), Nagoya University, Japan
Ph. D. in Human Resource Management, Nagoya University, Japan
Master of Business Administration ( MBA in International HRM) Shiga University, Japan
Master of Business Studies ( Management) Islamic University, Bangladesh
Bachelor of Business Studies (Hons) ( Management) Islamic University, Bangladesh

2. Post-doctoral Degree in Human Resource
Management
Awarded by Fulbright Commission,
Northeastern University, Boston, USA
Post-doctoral Degree in Human Resource
Management
Awarded by Japan Society for the Promotion
of Science (JSPS), Nagoya University, Japan
Ph. D. in Human Resource Management,
Nagoya University, Japan
Master of Business Administration
( MBA in International HRM) Shiga
University, Japan
Master of Business Studies
( Management) Islamic University,
Bangladesh
Bachelor of Business Studies (Hons) (
Management) Islamic University, Bangladesh
Dr. Mohammad Khasro Miah
Submission to:
Dr. Mohammad Khasro Miah
Submission By :
Mirza Shameem Hasan
ID No: 1835026690

3. Submission to:
Dr. Mohammad Khasro Miah
Factor analysis :
is a statistical method used to describe variability among observed, correlated variables in
terms of a potentially lower number of unobserved variables called factors. For example, it
is possible that variations in six observed variables mainly reflect the variations in two
unobserved (underlying) variables. Factor analysis searches for such joint variations in
response to unobserved latent variables. The observed variables are modelled as linear
combinations of the potential factors, plus "error" terms. Factor analysis aims to find
independent latent variables.
HRM Use of Factor Analysis
Factor Analysis. Factor analysis is a technique that is used to reduce a
large number of variables into fewer numbers of factors. This technique
extracts maximum common variance from all variables and puts them
into a common score. As an index of all variables, we can use this score
for further analysis.
Submission to:
Dr. Mohammad Khasro Miah

4. Submission to:
Dr. Mohammad Khasro Miah

5. Z-test
Z-test tests the mean of a distribution in which we already know the
population variance σ2 . Because of the central limit theorem, many test
statistics are approximately normally distributed for large samples. For
each significance level in confidence interval, the Z-test has a single
critical value
Example At an office test are 100 points, and 12
points, respectively. Our interest is in
the scores of 55 candidates in an
particular office who received a mean
score of 96. This office comparable to
a simple random sample of 55
candidates from the region as a whole,
or are their scores surprisingly low?
Submission to:
Dr. Mohammad Khasro Miah

6. Z-test
The Z-test tells us that the 55 candidates have an unusually low mean
test score compared to most simple random samples of similar size
from the population of test-takers.
Submission to:
Dr. Mohammad Khasro Miah

7. Submission to:
Dr. Mohammad Khasro Miah
T Test
The t test tells us how significant the differences between groups are; In
other words it lets you know if those differences. A t-test is used as a
hypothesis testing tool
Formula to calculate the t-score

8. Submission to:
Dr. Mohammad Khasro Miah
Use to find a change in proportion for the paired data.
For example, we can use this test to analyze retrospective case-
control studies, where each department is paired with a HR.
Performance obervatiom
Leave
Or,
attendance
To run a McNemar test,
= 73.63
which is extremely unlikely to form the distribution
implied by the null hypothesis (P < 0.006)

9. The Friedman test is a non-parametric statistical test developed by Milton Friedman.
Similar to the parametric repeated measures ANOVA, it is used to detect differences
in treatments across multiple test attempts. The procedure involves ranking each row
(or block) together, then considering the values of ranks by columns. Applicable
to complete block designs, it is thus a special case of the Durbin test.
Submission to:
Dr. Mohammad Khasro Miah

10. Analysis of variance (ANOVA) is a collection of statistical models and their
associated estimation procedures (such as the "variation" among and between groups)
used to analyze the differences among group means in a sample. ANOVA was
developed by statistician and evolutionary biologist Ronald Fisher. The ANOVA is
based on the law of total variance,
Submission to:
Dr. Mohammad Khasro Miah

11. F-test is any statistical test in which the test statistic has an F-
distribution under the null hypothesis. It is most often used
when comparing statistical models that have been fitted to a data set,
in order to identify the model that best fits the population from which
the data were sampled.
Y = denotes the overall mean of the data,
and K= denotes the number of groups.
Submission to:
Dr. Mohammad Khasro Miah

12. In inferential statistics, the null hypothesis is a general statement or
default position that there is nothing new happening, like there is no
association among groups, or no relationship between two measured
phenomena
Null hypothesis
The chi-square distribution is used in the common chi-square
tests for goodness of fit of an observed distribution to a theoretical one,
the independence of two criteria of classification of qualitative data, and in
confidence interval estimation for a population standard deviation of a normal
distribution from a sample standard deviation. Many other statistical tests also
use this distribution, such as Friedman's analysis of variance by ranks.
Submission to:
Dr. Mohammad Khasro Miah

13. Determine if categorical data shows dependency or the
two classifications are independent. It can also be used to
make comparisons between theoretical
populations and actual data when categories are used
Submission to:
Dr. Mohammad Khasro Miah

14. the p-value or probability value is the probability of
obtaining test results at least as extreme as the results
actually observedduring the test, assuming that the null
hypothesis is correct.
Submission to:
Dr. Mohammad Khasro Miah

15. Why Factor Analysis is Used
Factor analysis is mostly used in:
a) Data reduction
b) Scale development
c) The evaluation of the psychometric quality of a measure, and
d) The assessment of the dimensionality of a set of variables
e) In the determination of a small number of factors based on a
particular number of inter-related quantitative variables factor
analysis is used
f) FA analysis can directly measure speed, height, weight, etc., some
variables such as egoism, creativity, happiness, religiosity,
comfort are not a single measurable entity.
Submission to:
Dr. Mohammad Khasro Miah

16. Limitations and Directions for Future Research
This research has limitations and consequently recommendations for future studies.
Our proposal represents an attempt to build and test a conceptual framework of
HRM policies and practices. Then, a first limitation is that the present findings
are therefore indicative rather than conclusive. It would be useful to further
assess the generalizability of the HRM to other business environments such as
American, European and Asian countries. Moreover, with more replicative and
creative research, a more comprehensive conceptual framework related to HRM
policies and practices can be developed in the future.
Second, in spite of having a reasonable fit, the six-factor model didn't present a good
incremental index (CFI), indicating the necessity of new tests and other
specifications, to generally improve the model fit. The models using structural
equations tend to present excellent fit indices in situations where the measures
have a good delimitation and theoretical precision, besides having validity and
reliability confirmed by several samples (Tabachnick & Fidell, 2007). In the case
of this study, the fit indices reached by the confirmatory validation could be
considered reasonable considering the high complexity of the construct.
Submission to:
Dr. Mohammad Khasro Miah

17. HR view point :
(i) What is the study about?
(ii) Why is the study being made?
(iii) Where will the study be carried out?
(iv) What type of data is required?
(v) Where can the required data be found?
(vi) What periods of time will the study include?
(vii) What will be the sample design?
(viii) What techniques of data collection will be used?
(ix) How will the data be analysed?
(x) In what style will the report be prepared?
Submission to:
Dr. Mohammad Khasro Miah

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Dr. Mohammad Khasro Miah

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Dr. Mohammad Khasro Miah

20. Response Pattern in Scalogram Analysis
Submission to:
Dr. Mohammad Khasro Miah

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Dr. Mohammad Khasro Miah

22. An Illustrative Tally Sheet for Determining the Number
of 70 Families in Different Income Groups
Submission to:
Dr. Mohammad Khasro Miah

23. MEASURES OF CENTRAL TENDENCY
Submission to:
Dr. Mohammad Khasro Miah

24. MEASURES OF CENTRAL TENDENCY
Submission to:
Dr. Mohammad Khasro Miah

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Dr. Mohammad Khasro Miah

26. MEASURES OF CENTRAL TENDENCY
Submission to:
Dr. Mohammad Khasro Miah

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Dr. Mohammad Khasro Miah

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Dr. Mohammad Khasro Miah

29. References and Recommended Readings