Data Science Isn't Just for Math Nerds
LuvDokta
Posted on September 7, 2024
Data Science Isn't Just for Math Nerds
Introduction
People often think Data Science is all about numbers, calculations, and complexity. But while math plays a significant role in the field, this article shows that Data Science goes far beyond mere numerical analysis.
This piece isn't meant to criticize math experts - a strong mathematical foundation is incredibly valuable. Instead, it's for those who once had a passion for Data Science but felt that the emphasis on math made them lose hope.
This article also speaks to individuals who are unsure about pursuing a career in Data Science, especially those who doubt their mathematical abilities. It aims to change the narrative by focusing on problem-solving skills rather than the narrow view that career success is solely reserved for math experts.
The idea behind Data Science
Data Science is about using data to uncover insights that can lead to better solutions, smarter decisions, and more positive impact.
Data Science is revolutionizing healthcare by uncovering valuable insights that lead to improved patient care and outcomes. Hospitals across the country are increasingly employing data analytics to address critical challenges, such as high readmission rates for heart disease patients.
At Johns Hopkins Medicine, they’ve been looking into why so many heart failure patients have trouble keeping up with their follow-up appointments. By digging through patient records, surveys, and even looking at things like transportation options, they found that getting to the hospital for regular check-ups was a big challenge for many, especially older patients.
To help out, they started the "Heart Failure Bridge Clinic," which is run by nurse practitioners. This clinic acts like a stepping stone for patients moving from hospital care back to their regular lives. The team there, which includes doctors, nurses, pharmacists, and social workers, works closely with each patient to make sure they’re getting the right care—things like managing their medications, following a proper diet, and learning how to handle their condition day-to-day.
This approach has made it easier for patients to get the care they need without always having to come back to the hospital, which not only improves their health outcomes but also helps reduce the chances of being readmitted. Plus, it’s a great way to ensure patients stay on track with their recovery and feel supported throughout the process.
For more details, you can check out here
This example shows the potential of data science in healthcare to not only identify barriers to care but also implement solutions that enhance patient access and quality of service. Hospitals utilizing data analytics can streamline operations and improve the overall patient experience, proving that a data-driven approach is essential for modern healthcare delivery.
In summary, data science is not just about numbers; it's about transforming insights into actionable strategies that improve patient care and operational efficiency across the healthcare spectrum.
The heart of Data Science(Math)
But let's not forget about the math side of things. Data science isn't just for the number crunchers, but math is still a pretty important part of it.
Take the normal distribution function, for example. Sounds super fancy, right? But really, it's just a way of understanding how things tend to cluster around an average or "normal" value.
Data scientists use this concept all the time to make sense of all kinds of real-world data, whether it's sales figures, test scores, or even the heights of people in a population.
Speaking of averages, let's talk about the difference between the mean and the median.
The mean is the simple average, but the median is the middle value when you put all the numbers in order.
mean :
-lets say you have 3 baskets of apples having, 3,5,9 apples respectively.
3+5+9=17
And because there are 3 items ,you divide by the number of baskets to get the mean
(3+5+9)/3=5.66
we'll round it off to get the values as a whole number.The mean becomes 6.
median :
-lets say you have a group of 3 people with ages 24,26,28 in a queue to sign a register.
The median of 24,26 and 28 is 26 the middle value
Now back to that stack of student papers. If there's one or two papers that are way off the charts, either super high or super low, the mean grade might not give you the best picture of how the class is actually performing; but, the median would show you the true middle point, which could be a more accurate representation of the overall student performance.
See, Data Science isn't just about crunching numbers, it's about using those numbers to tell a story and make better decisions. It's a tool that can be applied to all kinds of real-world situations, whether you're running a business, working in healthcare, or just trying to understand the world around you a little bit better.For practical insights on applying mean and median in data analysis, check out this thought-provoking article:
Embark on Your Data Journey
Steps to mastering Data science
The recipe to mastering Data Science wouldn't be complete without some spices now would it(hope you are not allergic to this kind of spice ><)
+-------------------------------+
| Steps to Mastering Data |
| Science |
+-------------------------------+
|
|
v
+-------------------------------+
| 1. Practice Programming |
| - Use Codewars |
| - Use LeetCode |
+-------------------------------+
|
|
v
+-------------------------------+
| 2. Learn Mathematics and |
| Statistics |
| - Explore Project Euler |
+-------------------------------+
|
|
v
+-------------------------------+
| 3. Join Data Science |
| Communities |
| - Engage with Kaggle |
+-------------------------------+
- Practice programming
I promise you'll fit right at home ,whether you are a beginner,intermediate ,advanced programmer or a casual learner.This will improve your logic and problem solving skills
If you are feeling ambitious try leetcode,with interview questions to get you job ready and also equip you with algorithms from basic to advanced
2. Learn mathematics and statistics
Previous mentioned sites also have mathematics problems and solutions for your needs,but if you want to dig right into maths try here,maths problems are categorized from easy to hard and you can use any method to solve the questions.This will make you challenge your knowledge and logic.
3. Join Data science communities
It might seem too little but a little help goes along way, any other Data Scientist knows this and every one of them is always ready to help you through any of the steps as you master Data Science.
Here is one such community :
The world's largest Data Science community with powerful tools and resources to help you achieve your Data Science goals
Conclusion
Don't be intimidated by the math. Think of it like a tool in your toolbox - you only need to use it when it's necessary for the task at hand.
Data science is all about taking those complex concepts and turning them into something that actually makes a difference in people's lives; and with a little bit of creativity and a whole lot of real-world application, you can slay that math dragon and become a Data Science superhero in no time!
So, where do you start? Joining a community like Data Science/ML/AI Discord community is a great first step.You'll find people who are just as passionate about data science as you are, and who are happy to share their knowledge and support you on your journey.
Posted on September 7, 2024
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