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.
