Qualitative data can be used to ask the question “why.” It is used to
investigate situations. Qualitative data is mostly open-ended until research is
conducted. We can generate the data from qualitative research by using
interpretations, developing hypotheses, and initial understandings. When
discussing qualitative data, we are talking about a specific object’s
characteristics. Qualitative data is found through qualitative analysis of the
detailed information about the matter at hand. Quantitative data, is the
opposite of qualitative data. Quantitative data is statistical and is more
rigid and defined. This data type is measured using numbers and values,
making it a more suitable candidate for data analysis. Qualitative is open
for exploration, but quantitative data is much more concise and close-ended.
It can be used to ask the questions “how much” or “how many,”
followed by unquestionable information. A type of data I experience in
my professional life is invoices from contractors. the estimates are constantly
changing as the scope of work continues through the process. If unforeseen
problems arise during the process the invoice will have to be readjusted.
The difference between quantitative and qualitative data is one can be
counted and measured, the other is descriptive and not measured. Quantitative
data is countable, measurable and related to numbers. It can tell how
many, how much, and how often. It is factual and can be analysed
using statistical analysis. Qualitative data is descriptive, relating to words,
and language. Describes attributes to understand the why and how behind
certain behaviors. it is dynamic and subjective. Gathered through observations
and interviews. Analysed by grouping the gathered data into categories.In
the real estate industry, I can compare qualitative data to counts, such as
number of website inquiries, and sales. The qualitative data can be reviews,
postings, or surveys about the customer experience with the agency. There
are many differences between quantitative and qualitative data. Quantitative
data is any data that can be be put into a quantity. This is any data
that can be counted and or measured. The two types of quantitative data
is discrete data and continuous data. Quantitative data tells us how many,
how much, and how often. Quantitative data is measured by statistical
analysis through charts and tables. An example of quantitative data is 55%
of customers paid with a credit card versus cash.Qualitative data is data
that represents the how or the why behind the numbers. It is known as
descriptive data. This data is gathered though observation. There are two
types of qualitative data: nominal data and ordinal data. Nominal data is
a way to categorize certain data that does not have a quantitative value.
An example of this would be be like based out of Mexico or the
children have green eyes. Ordinal data is qualitative data that has some
sort of numerical value. An example of this would be like collecting data
in a. survey such as first second or third best. Quantitative data is all
about How much or how many. Qualitative data asks Why?. In qualitative
data the sample size is small and that too is drawn from non-representative
samples. Conversely, the sample size is large in quantitative data drawn
from the representative sample.Qualitative data develops initial understanding,
i.e. it defines the problem. Unlike quantitative data, which recommends the
final course of action.Quantitative research is advantageous for studies that
involve numbers, such as measuring achievement gaps between different
groups of students or assessing the effectiveness of a new blood pressure
medication.Qualitative research is often used to conduct social and behavioural
studies because human interactions are more complex than molecular reactions
in a beaker. Subjectivity, nonrandom sampling and small sample size
distinguishes qualitative research from quantitative research. A big advantage
of qualitative research is the ability to deeply probe and obtain rich
descriptive data about social phenomena through structured interviews, cultural
immersion, case studies and observation, for instance. Examples include
ethnography, narratives and grounded theory. Quantitative data is data that
expresses a quantity, amount, or range. Then can usually be something
like a measurement or the height of a person. Qualitative data is data
that isn’t easily reduced to numbers. Qualitative data answers questions of
‘what’, ‘how’, and ‘why’, versus answering questions of ‘how many’, and
‘how much’.
Advantages of Quantitative data – Since quantitative data can be
statistically analysed, researched based off this data will more than likely
be detailed. Since quantitative data has a numerical nature, there is a
reduced risk of personal bias. Results from quantitative data is extremely
accurate. Disadvantages of Quantitative data – Quantitative data is not
descriptive and therefore is difficult for researchers to make decisions based
only off the collected information.
-Quantitative data depends on the question types.
Advantages of Qualitative data – Qualitative data provides researchers with
a detailed analysis of subject matters.
-Qualitative data helps market researchers understand the mindset of their
customers
-Qualitative data can be used to conduct research in the future.
Disadvantages of Qualitative data - Collecting qualitative data is more time-
consuming.
-Qualitative data is difficult to generalize because fewer people are studied
-Qualitative data collection is dependent on the researcher’s skills and
experience
In my professional life I encounter a lot of qualitative data. When making
judgements on potentially fraudulent transactions I collect a lot of the
‘what’, ‘how’, and ‘why’ aspects of a customer’s account. It is my
responsibility to try to make sense of these transactions and determine
whether or not they could be fraudulent activity occurring on a customer’s
account
Quantitative is data collected by people to provide to researchers and be
able to analyse in detail subject matters. Qualitative is streamline summarized
in data into information that is relevant. The disadvantage of Quantitative
is that it takes a lot of time to do surveys and get a good perspective
of the subject of interest studied from. This makes it difficult to get
results and collect data correctly. The disadvantages for Qualitative can be
bias based that it is seen by opinion and data used by a researcher's
feelings to the experienced studied. Scientific data and numbers are not
correctly collected for the final results in a survey studied for. Quantitative
Data is when the data shows numbers, percents ranges and is exact or
precise on the information given. Examples that I experience with this on
a daily basis working in our family grocery store is the number of
Transactions Per day, The amount of cash, credit and check monetary
funds that we have gained throughout each day. The exact weight that
comes in per pallet or freight for our orders both in and out… The
advantage to this is that the numbers are clear, reliable and can be
tracked down and verified. The disadvantage is that all the data is tied
to the exact number and nothing else. Qualitative data differs because
it’s not the exact data, it's more of an estimate. It's not easily compared
or reduced to numerical answers. If someone asked me how many people,
we had shopping in the store on average I could give them my best
estimate based on experiences and knowledge but there would be no
definite answer for this because not every person who shops makes a
transaction. .Disadvantage to this is no way to be exact or to provide
charted information. I could give best guess. Advantage is that one can
ballpark the answer to the situation or example above and not have error
because it doesn't have the numbers to reflect that it has to be accurate.
The differences between quantitative and qualitative data is that quantitative
data expresses a certain amount, range, and or quantity. Whereas qualitative
data cannot be expressed by numbers but by opinions and characteristics.
An example of quantitative data that are encounter in my work is how
much a shipment weight and its dimensions. This data can determine how
much it will cost to transport this item from point a to b. For qualitative
data an example I can encounter daily are determining how many white
cars are parked in the grocery parking lot.Some advantages and disadvantages
of quantitative data is that it doesn’t need direct observation to be useful,
there’s higher and randomized samples, and it’s anonymous. Though the
data randomization will not create usable information, no specific feedback,
and the validity can create a doubt on the final results. The advantages
and disadvantages of qualitative data is that it will provide data from
viewpoints only and it can be based on available and incoming data. The
disadvantages are is its not a statistically representative form of data
collection and can create misleading information. Quantitative data is data
showcasing a particular quantity, amount, or range; normally inclusive of
measurement units such as test scores, and quality audit totals, number of
detractors as it pertains to service operations of a company. Many of the
examples I just note are from data my company collects to assure we
are offering service second to none to our members and clients. Working
in healthcare is something to be taken extremely seriously, and we have
measures in place to assess business understanding prior to staff supporting
customers and throughout their tenure with the company.
Qualitative data differs in that it is not easily reduced to number such
as the above examples. An example in my professional career is the
obtaining of survey feedback from our customers. Much like you or I
are given an opportunity to take a brief survey at the end of the call,
my company also offers this as an option. We want to hear feedback
from our customers and do better when there are opportunities presented
by which to do so. This can get tricky however as it is a number
rating as opposed to that quantitative/robust feedback you can get via other
data mining options. Although tougher to decode, no less an important
collection of data than any other means.
Quantitative – Advantages: Clear and concise results, rapid data collection,
reliable
Quantitative – Disadvantages: Can be costly due to number of participants
needed, every response gathered must stand on its own
Qualitative – Advantages: Less time consumption, and allows for speculation
Qualitative – Disadvantages: Sample size questioning/accuracy of sub-population
input, overall bias
Quantitative data is something that can be measured. It is when something
is measured by its quantity opposed to its quality. Qualitative data normally
is data that answers questions that pertain to what, why, and how. An
example of quantitative data is someones weight or height. Another example
is also the ounces of a water bottle such as 16.9 ounces of water. An
example of qualitative data could be the number of different color skittles
in a bag. Another example could be the colors of the kids uniforms in
a elementary school. The advantages of quantitative data is that you can
quickly collect the information and a disadvantage is that every answer
must stand on its own. A advantage of qualitative data is that it provides
a flexible approach and a disadvantage is that it can take a lot of time
to collect data. A type of quantitative data that I encounter in my
personal life is taking my daughter to the doctor and them measuring
her height. A qualitative encounter in my professional life is the use of
reports which I deal with a lot of at work. People frequently analyse
data using nominal data as a categorical variable so that differences can
be compared across categories. For example, I might ask for information
about store name, then also collect information on sales receipt total.
Different types and levels of data can be analysed only in certain ways.
For example, if you use nominal data--such as gender, you can only
count the results and report it as a number or percentage. However,
interval and ratio data can be summarized in other ways. Quantitative data
is something that can be measure or counted like numbers whereas
qualitative data is descriptive and not numerical.A good example of
quantitative data would be something as simple as our height and weight
or even surveys we get from companies printed on our receipts. With
height and weight, in the United States still uses the Imperial measuring
system which means that our height is typically stated in feet and inches
and weight is calculated in pounds and ounces. In a majority of other
countries, they use the Metric measuring system which calculates height as
meters and weight as grams. When a company prints a survey out on
a receipt for us, we typically are giving a rating scale to tell them
how much we liked their service or products. Normally this is like a 1-
5 system with 1 being bad and 5 being terrific. An example of qualitative
data could be our eye colours. Eye colours are typically green, blue,
brown or hazel. These are easy to explain because they are colours that
we are familiar with and that most people have when you look at their
eyes. Sometimes there are mixed colours but it's still the same concept
of explaining visually what the colour mix is. To be honest, surveys,
political and election polls in my life is the best representation of
quantitative, it is all about polling and numbers. Yes, including the
qualitative is the language or what reflects my life/lifestyle in the results
of the numerical data. I know, this is class but let be real. Surveys
and polling are to give a close to real or a direct point, to convey
and persuade. The Nielsen is a notable example, but you will get paid
for doing the survey, so who are they: Nielsen is a global leader in
audience insights, data and analytics, shaping the future of media. Measuring
behaviour across all channels and platforms to discover what audiences love,
we empower our clients with trusted intelligence that fuels action. Now,
it is about my lifestyle, and I am a liberal and I focus on what is
my benefit as an African American female. My disadvantage of those polls
politically is what my future will result in “Jim Crow in A Suit Now
and Future,” or my advantage “Civil Rights Equality for All.” Now, let
me back up to those annoying surveys, we get on the receipts from
stores like Walmart, “You Can Win Up To $1,000”. Yes, they are
gathering information on what they are to do better for as providing
quality customer service, but prices are still going up and you are more
like not to win the $1,000. To be realistic, give me $5 gift card for
doing the survey.Now, to conclude my discussion with the qualitative data,
is it going to get me ahead, or make the company who is doing the
data get richer. To give an analysis of what people like me are thinking,
living, working and not doing. What I feel, is where is my benefit, I
am still not getting more money, and still paying more for less. Oh,
before I forget it is to gain one’s attention as well, or to be a
distraction. Quantitative data refers to numeric variables such as how much
or how many. Qualitative data is measured by types such the types of
coins in a jar and color of cars in parking lot. The advantages of
categorizing the data in these two categories helps determine what type of
graph can be used to track and log the data. The disadvantages of these
categorize is that quantitative data gives false focus on numbers and can
also be misleading. While qualitative data can lose data and is not
statistically representative form of data collection. As an analyst in my
current job I deal with quantitative data all the time. I'm responsible to
ensure that the amount of money that is going out matches with what
our systems planned on. In my personal life quantitative data would be
grocery shopping. I'm very particular about making sure to grab the sales
prices and coupons and ensure it is in my budget to purchase the items
needed for that week. As for qualitative data I'm not quite sure when I
use this in my personal or professional life. Interval data differs from
ratio data in that the "0" point needs to be defined. For example, if I
ask a question to be rated on a scale of 1-10, that would result in
interval data. This is because I decided on what a "1" would mean. I
could just have easily used a scale from 1 to 5 , defining the steps
this way. On the other hand, ratio data is some kind of measurement,
such as gallons or inches. 0 gallons is not arbitrary and 1 gallon is
always a gallon.The differences between quantitative and qualitative date :
Quantitative data is data that has numerical value. The quantities of data
can be measured and numbered / ordered. Some examples of quantitative
data could be someone's age , the temperature outside or the cost of
bought goods(items). Qualitative data is data known by it's qualities. It's
data that is expressed by words and not numbers. Qualitative data cannot
be evaluated using the statistic method. Some examples of qualitative data
would be someone's name , the seasons of the year or the name of a
company .I would have to say that the advantages of of both would be
that we are able to separate the way we measure and operate different
tasks daily. When we are at home, work or out and about we can
determine how we will handle quantitative data . For example the weather
outside..if we need to wear the proper clothing we can measure hot cold
or how hot it is outside so we can dress appropriately. Another example
would be knowing someone's age when their birthday comes around each
year. We can determine what type of gift to buy them depending on
how old they will be turning. For qualitative data , we know that it
cannot be analyzed so how can we use it daily? Well, we can use it
to record and store people's names in our cell phones, on our computers
at work or home and on social media. Google is a great example of
quantitative data that is stored. We can look up anyone's name, a company
or facts about the weather, seasons of the year and so on. I use both
at home and work. I work as children's crisis center intake coordinator
so I am responsible for creating intake files for each patient that includes
vital information. This said information would include the patient's name,
age, address, insurance information, phone number, the guardian/parent's
information and other data that is necessary to create a complete file.
Most of the information gathered has to be analyzed by the doctors in
order to establish treatment for my patients. I would say that I have to
use bot quantitative & qualitative data everyday when registering new
patients. I feel like I have to pretty much incorporate both data strategies.
Hopefully , I have explained my response in a clear manner. I tried to
used what I listened to in the podcast this week which gives a clear
understanding of both qualitative & quantitative data. When consulting with
companies, data analysts often ask, "how will you use the data" before
advising clients what to collect and how to analyze it. Without being
able to act upon data, data will simply be discarded--a costly mistake for
companies. The reason that statistics is part of your business course is
that managers must understand how to use data and, moreover, appreciate
the different ways of analyzing it. I would say that from my previous
employers and professions the managers/supervisors have always relied on
the secretary , intake coordinators and registration specialist to gather the
important basic demographics , medical information , and all other important
details in order to create a base file for further servicing the community
and setting up direct care for individuals. The managers would then be
able to assess what that person is in need of and what direction to
point them in or how to begin working with that individual after proper
data have been collected. This would apply in many different fields such
as maybe a hospital or doctor's office setting, mental health, educational
programs or school registration . I have had the pleasure to work in all
fields mentioned above. Now I have transitioned into a new position as
an intake coordinator for a children's crisis center. I know that my job
will entail such task as gathering us basic data to establish treatment for
new clients. I anticipate this class helping me in so many ways.Another
example of quantitative data could be the amount of ounces in a milk
jug of your choice. Qualitative data is more so of s description of
something. The example you used was very detailed and gave me insight
from a different stand point on how to analyze quantitative data. Being
as though qualitative data is a description, using someones eye color or
hair color is also a good example on how to explain it.when I make
a call to a customer service and at the end of the call I am asked
if I can take a quick surveys. Many times I am told these surveys
helps them to see how they are doing. I have wondered if this is what
or could affect their evaluation in how much they could get in a raise
or work work performance. I do take the time and do it because of
this reason. I am not sure if that is used in a work performance but
just in case. I see it if it was me I would want to get a good
review in my job. Many polls, are designed to target women, then, it
is broken down, to race and color. Example, employment, and I understand
why, it is so important that The Department of Labor, have different
types of quantitative researches. This is a fact, who is going to support
the government if certain number of women are not in the workforce.
Since, COVID-19, women were targeted the most, because of the "Single
Parenting". It is expensive, day-care back in 1981 was approximately $20.00
a week now it is a tuition, yes from $300 to $1400 per week depending
on what part of the planet a person may live. I chose daycare, because
it is a need. To break it all down it is about MONEY, and who is
going to pay and benefit from it. So, women are slowly moving back
into the workforce, and many have gotten complacent with work-at-home,
because it is cheaper, for them and the company they work for. Some
data that can be used from a sales receipt could be what's being bought
from what departments. If you were to analyse what departments are the
most bought from at the specific store, you could obtain that data from
the sales receipt. From there you can determine what departments are least
and most shopped which could potentially be helpful to the store to
analyse this information. It could show the owners/managers what areas
may need improvement or to have sales on more than the others to
attract shoppers and get more traction in those departments.
