In this video, we are going to unpack the thorny topic of research bias. Also sometimes
called researcher bias. We will explain what it is look at some common types of
research bias and share some tips to help you minimise the potential biases in your
research. If you are currently working on a dissertation, thesis or research project be
sure to grab our free dissertation templates to help fast-track your write-up. These tried and
tested templates provide a detailed roadmap to guide you through each chapter section by
section. If that sounds helpful you can find the link in the description below.
So what exactly is research bias? Well, simply put research bias is when the researcher,
that is you, intentionally or unintentionally skews the process of a systematic inquiry which
then of course skews the outcomes of the study. In other words, research bias is what happens
when you affect the results of your research by influencing how you arrive at them. For example,
if you plan to research the effects of remote working arrangements across all levels of an
organisation but your sample consisted mostly of management-level respondents
you run into a form of research bias. In this case excluding input from lower-level
staff in other words not getting input from all levels of staff means that the results of the
study would be biased in favour of a certain perspective that of management. Of course,
if your research aims and research questions were only interested in the perspectives of
managers this sampling approach would not be a problem. But that is not the case here as there
is a misalignment between the research aims and the sample. By the way, if you want to learn more
about research aims and research questions check out our video covering that up here. You can also
find the link in the description below. Now it is important to remember that research bias is
not always deliberate or intended. Quite often it is just the result of a poorly designed study
or practical changes in terms of getting a well-rounded suitable sample. While perfect
objectivity is the ideal some level of bias is generally unavoidable when you are undertaking
a study. That said as a savvy researcher it is your job to reduce potential sources of
research bias as much as possible. To minimise potential bias you first need to know what to
look for. So next up I will unpack three common types of research bias we see at Grad Coach when
reviewing students' projects. These include selection bias, analysis bias and procedural
bias. Keep in mind that there are many different forms of bias that can creep into your research.
So do not take this as a comprehensive list it is just a useful starting point. To learn more about
other potential biases you can check out the Grad Coach blog. Link down in the description.
First up we have selection bias. The example I mentioned earlier about only surveying management
as opposed to all levels of employees is a prime example of this type of research bias.
In other words, selection bias occurs when your studies' design automatically excludes
a relevant group from the research process and therefore negatively impacts the quality of the
results. With selection bias, the results of your study will be biased towards the group that it
includes or favours meaning that you are likely to arrive at prejudiced results. For example,
research into government policies that only includes participants who voted for
a specific party is going to produce skewed results as the views of those who voted for
other parties will be excluded. Selection bias commonly occurs in quantitative research as the
sampling strategy adopted can have a major impact on the statistical results. That said
selection bias does of course also come up in qualitative research as there is still plenty
of room for skewed samples. So it is important to pay close attention to the makeup of your sample
and make sure that you adopt a sampling strategy that aligns with your research aims. Of course,
you will seldom achieve a perfect sample and that is okay but you need to be aware
of how your sample may be skewed and factor this into your thinking when you analyse the
result in data. If you are enjoying this video so far please help us out by hitting that like
button. You can also subscribe for loads of plain language actionable advice. If you are
new to research check out our free dissertation writing course which covers everything you need
to get started on your research project. As always links in the description.
Next up we have analysis bias. Analysis bias occurs when the analysis itself emphasises or
discounts certain data points so as to favour a particular result. Often the researchers own
expected result or hypothesis. In other words, analysis bias happens when you prioritise the
presentation of data that supports a certain idea or hypothesis rather than presenting all the data
indiscriminately. For example, if your study was looking into consumer perceptions of a specific
product you might present more analysis of data that reflects positive sentiment toward the
product and give less real estate to the analysis that reflects negative sentiment. In other words,
you would cherry-pick the data that suits your desired outcomes and as a result,
you would create a bias in terms of information conveyed by the study. Although this kind of bias
is common in quantitative research it can just as easily occur in qualitative studies
given the amount of interpretive power the researcher has. This may not be intentional or
even noticed by the researcher given the inherent subjectivity in qualitative research. As humans,
we naturally search for and interpret information in a way that confirms or supports our prior
beliefs or values. In psychology, this is called confirmation bias. So do not make the mistake of
thinking that analysis bias is always intentional and that you do not need to worry about it because
you are an honest researcher it really can creep up on anyone. To reduce the risk of analysis bias
a good starting point is to determine your data analysis strategy in as much detail as possible
before you even collect your data. In other words, decide in advance how you will prepare the data,
which analysis method you will use and be aware of how different analysis methods can favour
different types of data. Also, take the time to reflect on your own preconceived notions and
expectations regarding the analysis outcomes so that you are fully aware of the potential
influence you may have on the analysis and therefore hopefully, you can minimise it.
Last but definitely not least we have procedural bias which is also sometimes referred to as
administration bias. Procedural bias is one of the easier biases to overlook so it is important
to understand what it is and how to avoid it. This type of bias occurs when the administration of the
study especially the data collection aspect has an impact on either who responds or how
they respond. A practical example of procedural bias would be when participants in a study are
required to provide information under some form of constraint. For example, participants might
be given insufficient time to complete a survey resulting in incomplete or hastily filled out
forms that do not necessarily reflect how they really feel. This can happen really easily if,
for example, you innocently ask your participants to fill out a survey during their lunch break.
Another form of procedural bias can happen when you improperly incentivise participation
in a study. For example, offering a reward for completing a survey or interview might incline
participants to provide false or inaccurate information just to get through the process
as fast as possible and collect their reward. It could also potentially attract a particular type
of respondent a freebie seeker resulting in a skewed sample that does not really reflect your
demographic of interest. The format of your data collection method can also potentially
contribute to procedural bias if, for example, you decide to host your survey or interviews
online this could unintentionally exclude people who are not particularly tech-savvy,
do not have a suitable device or just do not have a reliable internet connection. On the flip side,
some people might find in-person interviews a bit intimidating compared to online ones at least or
they might find the physical environment in which they are being interviewed to
be uncomfortable or awkward. Maybe the boss is peering into the meeting room, for example. Now,
although procedural bias is more common in qualitative research it can come up in any form
of fieldwork where you are actively collecting data from study participants. So it is important
to consider how your data is being collected and how this might impact respondents. Simply put you
need to take the respondent's viewpoint and think about the challenges they might face no matter how
small or trivial these might seem. So it is always a good idea to have an informal discussion with
a handful of potential respondents before you start collecting data and ask for their input
regarding your proposed plan upfront. Okay, so let us do a quick recap. Research bias refers to any
instance where the researcher or the research design negatively influences the quality of a
study's results whether intentionally or not. So three common types of research bias we looked at
are selection bias where a skewed sample leads to skewed results, analysis bias where the analysis
method and or approach leads to biased results and procedural bias where the administration of
the study especially the data collection aspect has an impact on who respondents are and how they
respond. As I mentioned there are many other forms of research bias but we can only cover
a handful here. So be sure to familiarise yourself with as many potential sources of
bias as possible to minimise the risk of research bias in your study. Now as I mentioned earlier you
can learn more about all of this on the Grad Coach blog. The link is in the description.
If you got value from this video please hit that like button to help more students find
this content. For more videos like this check out the Grad Coach channel and subscribe for
plain language actionable research tips and advice every week. Also if you are looking
for one-on-one support with your dissertation, thesis or research project be sure to check
out our private coaching service where we hold your hand throughout the research process step
by step. You can learn more about that and book a free initial consultation at gradcoach.com.