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What are research biases and its types? Elaborate your answer.
Research biases:
The concept of research bias refers to the idea that some research may be conducted
with the goal of persuading you to adopt a particular point of view. The researcher's
bias is what causes the research findings to depict a specific conclusion. Several times
Several study errors can occur as a result of this bias because all potential variables
are not considered. In another study, a researcher may select a specific subject that is
likely to produce the desired results.
Types of Research biases:
Design Bias
Design bias has to do with how your research is set up and conducted. A "researcher
bias" exists when the researcher's preferences for what is best for the research setting
have a major influence on the research design, survey questions, and research
methods.
Acquiescence bias :
It refers to the kind of bias that develops when an experimenter asks questions of a
respondent and they have a propensity to agree with the experimenter's arguments.
They have an inclination to accept everything without questioning it and tend to think
that every concept is good.
Social desirability bias:
People who wish to fit in and respond to questions that are socially desirable are
involved in this form of research bias. In order to avoid this researcher should
convince the respondent that he is in a safe environment and nobody is judging.
Habituation :
Since thinking and responding take effort, respondents occasionally offer similar
responses because they utilize similar terminology, which generates research bias.
Therefore, moderators should craft engaging questionnaires.
Sponsor bias:
It happens when the participant expresses thoughts that are consistent with the
sponsors' basic values and beliefs causing defect in the research.
Researcher bias:
When constructing and presenting the study questions, the researcher has the
opportunity to create bias. Leading, double-barreled, negative, and loaded questions
are examples of biased questions that can affect how respondents respond and the
sincerity of their views.
Confirmation bias:
Bias occurs when researchers seek data to support their preexisting beliefs. Existing
beliefs can include one's anticipation of a particular outcome and expectations in a
particular situation. To reduce this bias, researchers must assess participant responses
and challenge current hypotheses and assumptions.
Culture bias:
When a researcher attempts to interpret a phenomenon using cultural standards. To

avoid this researcher in developing cultural understanding of others is never
completely achievable.
Question-order bias:
Question order bias occurs when the answers to one question influence the responses
to subsequent questions. Although it is almost always unavoidable, it can be
minimized by asking generic questions before specific ones.
What is sampling in research? How many types of sampling are there?
Elaborate your answer with probability and non probability types of sampling.
Sampling
Sampling refers to the method, or strategy of choosing a suitable sample, or a

representative section of a population, with the aim of determining the characteristics
or qualities of the entire population. In sampling, the population units are individuals,
cases, and data points. By employing inferential statistics, which enables us to draw
conclusions about populations from samples, we can learn about a population's
features by directly seeing only a portion of it.
Probability sampling and non-probability sampling are the two types of sampling that
are utilized in research. These two sample methods are discussed in more detail in the
following section.
Probability sampling:
A researcher chooses people from a population using the probability sampling

technique based on a few criteria. When this selection parameter is utilized, each
member has an equal chance of being included in the sample. This type of sampling is
further divided in to different categories that are illustrated below.
Simple random sampling:
One of the best probability sampling techniques for saving time and money is the
Simple Random Sampling strategy. It is a trustworthy method of gathering data when
each person in a population is chosen at random. Each applicant has an equal chance
of being selected to join a sample.
Cluster sampling:
To divide the entire population into groups or clusters that each represent a certain
demography, researchers employ the cluster sampling technique. Based on
demographic factors like age, gender, area, and so forth, clusters are found and
included in a sample. This makes drawing useful conclusions from the results for a
survey creator very simple.
Stratified random sampling:
Using a method known as stratified random sampling, the researcher splits the
population into smaller groups that do not cross over but nonetheless accurately
represent the overall population. Each of these groups can be independently sampled
after being set up for sampling.
Systematic sampling:
To select randomly selected sample participants from a population, researchers

employ the systematic sampling approach. It necessitates choosing a sample size and
a starting point that may be repeated frequently. This sampling strategy uses a certain
range and takes the shortest amount of time.
Non-probability sampling:
In non-probability sampling, the researcher chooses participants at random. This

example method doesn't employ a predefined or predetermined way of selection. As a
result, it might be challenging to guarantee that each element of a population has an
equal chance of being represented in a sample. The sub types of this sampling are as
follow:
Convenience sampling:
This strategy depends on how accessible the subjects are; for example, polling mall
patrons. Since the individuals may be reached easily, it is commonly known as
convenience sampling. Researchers with minimal time and resources , this non-
probability sampling method is used. Convenience sampling is employed when
resources are scarce, such as in the early phases of research.
Snowball sampling:
The snowball sampling technique is used by researchers when reaching out to people
is challenging. Researchers might use the snowball hypothesis to keep an eye on a
few categories for interviews and data collecting while surveying undocumented
immigrants. When researching extremely delicate subjects, researchers also employ
this model technique.
Purposive sampling:
The researcher has the choice of producing purposeful or judgmental samples.

Researchers only take into account the study's objectives and their comprehension of
the target audience.
Quota sampling:
It entails choosing participants in accordance with a predetermined standard. A

sample will in this scenario have the same features as the entire population because it
was established based on certain attributes. It is a quick technique for gathering
samples.

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What are research biases and its types? Elaborate your answer.

Types of Research biases:

Social desirability bias:

When a researcher attempts to interpret a phenomenon using cultural standards. To

Sampling refers to the method, or strategy of choosing a suitable sample, or a

A researcher chooses people from a population using the probability sampling

Simple random sampling:

Stratified random sampling:

To select randomly selected sample participants from a population, researchers

In non-probability sampling, the researcher chooses participants at random. This

The researcher has the choice of producing purposeful or judgmental samples.

It entails choosing participants in accordance with a predetermined standard. A

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