1. Sampling error occurs when statistical characteristics estimated from a sample differ from the true population parameters, since samples do not include all members of the population. 2. SPSS Statistics is statistical analysis software used for tasks like survey deployment, data mining, text analytics, and collaboration. It was originally called the Statistical Package for the Social Sciences. 3. Empirical research uses direct observation or experience to gain knowledge, relying on evidence from data collected through experience or experimentation. Both qualitative and quantitative analysis can be used.

1. RESEARCH METHODOLOGY MATERIALS CR
REASRCH
A perceived gap between the existing state and a
desired state, or a deviation from a norm,
standard, or status quo.
Although many problems turn out to have several
solutions (the means to close the gap or correct
the deviation), difficulties arise where such means
are either not obvious or are not immediately
available
SAMPLE ERROR
In statistics, sampling error is incurred when the
statistical characteristics of a population are
estimated from a subset, or sample, of that
population. Since the sample does not include all
members of the population, statistics on the
sample, such as means and quantiles, generally
differ from the characteristics of the entire
population, which are known as parameters. For
example, if one measures the height of a thousand
individuals from a country of one million, the
average height of the thousand is typically not the
same as the average height of all one million

2. people in the country. Since sampling is typically
done to determine the characteristics of a whole
population, the difference between the sample and
population values is considered a sampling error.[1]
Exact measurement of sampling error is generally
not feasible since the true population values are
unknown; however, sampling error can often be
estimated by probabilistic modeling of the sample.
SPSS
SPSS Statistics is a software package used for
statistical analysis. Long produced by SPSS Inc., it
was acquired by IBM in 2009. The current versions
(2015) are officially named IBM SPSS Statistics.
Companion products in the same family are used
for survey authoring and deployment (IBM SPSS
Data Collection), data mining (IBM SPSS Modeler),
text analytics, and collaboration and deployment
(batch and automated scoring services).
The software name originally stood for Statistical
Package for the Social Sciences (SPSS),[
2]
reflecting the original market, although the
software is now popular in other fields as well,
including the health sciences and marketing
EMPIRICAL RESEARCH
Empirical research is research using empirical
evidence. It is a way of gaining knowledge by means of

3. direct and indirect observation or experience. Empiricism
values such research more than other kinds. Empirical
evidence (the record of one's direct observations or
experiences) can be analyzed quantitatively or
qualitatively. Through quantifying the evidence or making
sense of it in qualitative form, a researcher can answer
empirical questions, which should be clearly defined and
answerable with the evidence collected (usually called
data). Research design varies by field and by the
question being investigated. Many researchers combine
qualitative and quantitative forms of analysis to better
answer questions which cannot be studied in laboratory
settings, particularly in the social sciences and in
education.
EXECUTIVE SUMMERY
An executive summary, or management
summary, is a short document or section of a
document, produced for business purposes, that
summarizes a longer report or proposal or a group
of related reports in such a way that readers can
rapidly become acquainted with a large body of
material without having to read it all.
SAMPLING
Sampling is the process whereby a researcher chooses
her sample. This might seem pretty straightforward: just
get some people together, right? But how does Brooke do
that? Should she just stand on a corner and start asking
people to take her survey? Should she send out an email

4. to every college student in the world? Where does she
even begin?
Because sampling isn't as straightforward as it initially
seems, there is a set process to help researchers choose
a good sample. Let's look closer at the process and
importance of sampling
-What is a Good Research Question
The first step in formulating a good research question is
to read and review lots of literature related to your topic
of concern. It is also a good idea to read some current
literature or recent literature to acquaint yourself with
the type of researches being done. Ther are many other
ways in which you can come up to a manageable and
specific research question that can be answered in a
given time period through your research. A research
question that can minimize confusion in the later steps of
your research.
How to formulate a good research question
1. Choose a research area
2. Select a research topic
3. Review literature of your interest
4. Select a general topic of interest
5. Narrow down the topic
6. Formulate several questions
7. Select one question for your research
8. Specific

5. 9. Clear
10. Simple
NON RANDOM SAMPLING
Subjects in a non-probability sample are usually
selected on the basis of their accessibility or by the
purposive personal judgment of the researcher.
The downside of the non-probability sampling
method is that an unknown proportion of the
entire population was not sampled.
METHODS
Convenience
OK, so Kiera wants to give her survey to a sample
of people in order to learn why Americans feel the
way they do about capital punishment. She and
her two research assistants go to a shopping mall
on a Tuesday morning and stop people to ask their
opinion on the death penalty and why they feel
that way.
Quota
For a moment, though, let's say that Kiera and her
research assistants are able to go to a mall at a
time when the entire population of American adults

6. is represented. She still has to choose which
people to survey. How should she do that?
CORRELATION AND REGRESSION
Correlation and regression analysis are related in the
sense that both deal with relationships among variables.
The correlation coefficient is a measure of linear
association between two variables. Values of the
correlation coefficient are always between -1 and +1
Regression analysis involves identifying the relationship
between a dependent variable and one or more
independent variables. A model of the relationship is
hypothesized, and estimates of the parameter values are
used to develop an estimated regression equation.
Various tests are then employed to determine if the
model is satisfactory. If the model is deemed
satisfactory, the estimated regression equation can be
used to predict the value of the dependent variable given
values for the independent variables.

7. Correlation.
Correlation and regression analysis are related in the
sense that both deal with relationships among variables.
The correlation coefficient is a measure of linear
association between two variables. Values of the
correlation coefficient are always between -1 and +1. A
correlation coefficient of +1 indicates that two variables
are perfectly related in a positive linear sense, a
correlation coefficient of -1 indicates that two variables
are perfectly related in a negative linear sense, and a
correlation coefficient of 0 indicates that there is no linear
relationship between the two variables. For simple linear
regression, the sample correlation coefficient is the
square root of the coefficient of determination, with the
sign of the correlation coefficient being the same as the
sign of b1, the coefficient of x1 in the estimated
regression equation.
 3.1. Factors influencing sample
size

8.  3.1.1. Laboratory
constraints
 3.1.2. Independence of
observation and pseudo-
replication
 3.1.3. Effect size
 3.2. Sample size determination
 4. A worked example
 5. Statistical analyses
 6. Presentation and reporting of
data
 7. Which software to use for
statistical analyses?
 8. Where to find help with statistics
 9. Conclusion
 10. Acknowledgements
 11. References
o Toxicology research
Importance of Literature Review
Review of literature in any study is not a cup of tea; it
requires scholarly maturity. Good review of literature is a
sign of professional maturity; it shows one’s grasp of the
field, one’s methodological sophistication in critiquing
others’ research, and the breadth and depth of one’s
reading (Krathwohl , 1988).

9. Firstly, review of literature acts as a stepping-stone
towards achievement of the study objectives. For
scholars, the depth and breadth of the literature review
emphasizes the credibility of the writer in his or her field
Secondly, literature reviews provide a solid background
to back one’s investigation. The review plays a critical
role in analyzing the existing literature and giving
justification as to how one’s research fits into the existing
body of knowledge. This implies that the literature
review provides the general understanding which gives
meaning to the discussion of findings, conclusions, and
recommendations.
Thirdly, literature reviews help the researcher to avoid
duplication, identify the gaps in other studies with the
goal of filling them, borrow from the research design and
methodology used to investigate that particular problem
and to interpret his or her own findings.
In general terms, the literature review helps to provide a
context for the research, justify the research, ensure the
research hasn’t been done, show where the research fits
into the existing body of knowledge, enable the
researcher to learn from previous theory on the subject,
illustrate how the subject has previously been studied,
highlight flaws in previous research, outline gaps in
previous research, show that the work is adding to the
understanding and knowledge of the field, help refine,
refocus or even change the topic.