Reviewed by:
Summary: Mahima’s passion for learning beyond the syllabus led her to discover regression analysis, changing her academic perspective and inspiring her to embrace data-driven insights for personal growth.
Mahima had been a bright performer at her school. However, with the passage of time, it started to seem as if she was flailing about in academics. She liked studying and had always been an enthusiastic learner, which was validated by her curiosity for subjects beyond the scope of her syllabus.
Similarly, she was amazed by the vast body of knowledge in the form of books at the library and on the internet, which seemed like a treasure chest to her.
She felt irked by the disproportionate bias attached to the exams. In her pursuit of wisdom, her teachers often reprimanded her for “not sticking to the syllabus” and her parents considered her a “recalcitrant, pampered child.”
Her classmates’ unrestrained passion for outscoring one another at unit tests, periodicals, etc. made her question the unending race.
All of this made her rebellious and full of contempt. She had coined a term for these traits and the individuals exhibiting them: rabid regressives. She scribbled the term onto her bag, textbooks, and almost every other article that was a token of this dreaded connection.
The status quo was going to change, though.
Mahima’s school often organized seminars with industry experts, bureaucrats, and actors to encourage students to develop offbeat career interests. Mahima thought of them as useful pastimes, which gave her more food for thought.
On one such occasion, the school auditorium hosted Nidhi, a bright, experienced female statistician. She was also an alumna of the institution, which excited her to host the gathering. She wanted to make a difference.
A couple of minutes had gone by before she could begin. “A very good afternoon to you all!” She introduced herself and talked briefly about her education as a statistician in a premier institution and her current stint as an analyst at a multinational firm.
“Whatever I just said wouldn’t have made a lot of sense to you. Nevertheless, it will be better if you stay with me. There was an incident back in the day that ensured I ended up pursuing this field. Starting sixth grade, we were constantly prodded to read more; while this explained why we had the dreaded library-reading period, it also enabled the ones taking it seriously to improve their vocabulary and overall fluency in English.”
The mention of a familiar phenomenon piqued the audience. Nidhi continued, “Anyway, we were introduced to data representation in the sixth standard, and I was fascinated by it.”
“So, I started devoting a lot of time to the subject. Ma’am Amrita, our maths teacher, saw this and encouraged me to learn more. I would plot whatever data I could get a hold of; most of the time ten of my best friends were the ones who furnished these numbers; it had indeed become a hobby!”
“During one such exercise, I stacked the number of books my friends had borrowed from the library and read during the last four half-yearly terms against their score in the English exams.” Mahima grimaced slightly, but she was far too absorbed to stop listening.
“Do note that the scores were relative; as you may know, our report cards pegged our performance compared to the rest of the class. Also, our library exercise books had book reviews that recorded the lending we did. Thus, the data is perfectly non-fictitious,” she chuckled. “What I observed can be seen on the screen.” A set of enthusiastic eyes followed the presentation pointer’s ray and saw a chart.
“What I got was intriguing; I went to Ms. Amrita, who introduced me to a new and amazing idea: regression. If you try fitting the points, the overall trend is envisaged better.”
Mahima was startled. The overall trend of the increasing scores, with their dependency on the number of books read, was quite succinct. She also understood that the number of individuals sampled was ten itself, with the more enthusiastic readers getting brighter with time.
Nidhi continued, “While this cannot call a regression proper since the sample wasn’t representative, it explained the overall idea to a large extent, especially to an unacquainted individual”.
“A regression maps a causal relationship between variables. In this case, the ..” and Mahima’s conclusion followed as it is.
“This was in fact an example of a linear regression, in which a dependent variable influence by an independent one; in this case, the two follow a linear relationship, wherein the increase in the number of books read transcends to an increase in the scores obtained.”
“With Ms. Amrita’s exhortation, I persisted in pursuing the field while at school. During my undergrad stats studies, I was able to build upon it holistically, which imparted me with truly powerful knowledge.”
“I ended up becoming an analyst, as I had said; it’s a job profile where regression continues to come in handy. For instance, companies optimize their budget among the various media they utilize to advertise a particular product.”
“I assisted my team with such a problem for our TV and social media channels to arrive at a solution which ensured optimal spending for customer acquisition.”
“The general idea being, we had to arrive at an optimum sum of the two variables, with one influencing acquisition significantly more than other. The main thing to note is the amount of variation of y with x, in absolute terms.”
“We rely on computers to plot these since using graph papers isn’t feasible now”, and the gathering broke into laughter.
“Regression analysis forms an inseparable part of a wide array of other disciplines. It enables decision-making and finds its application in various domains like Machine Learning. In fact, I believe not learning regression may make you regressive!” Mahima couldn’t resist herself when Nidhi concluded. She ran after her when she began leaving the auditorium.
“Ma’am, back when you were here, how did you face the rabid regressives?” she squealed, huffing between deep breaths. “What do you mean, dear?” Nidhi inquired. There followed a hasty, drawn-out explanation.
“Being an outlier is exceptional! Make the most of it!” Nidhi’s quip kept resounding in Mahima’s head. She began understanding that despite bucking the trend, she could remain a part of the population. On Nidhi’s advice, she even started referring to online resources to pursue her newfound passion.
Nidhi told her, “Make transformations, logarithmic and exponential.”
Just like you, she wondered what the latter meant.
Also Read:
Regression in Machine Learning: Types & Examples.
What is Logistic Regression in Machine Learning: Explained Simply.
Unlocking the Power of KNN Algorithm in Machine Learning.
Feature Engineering in Machine Learning.
Regularization in Machine Learning: All you need to know.
How can Data Scientists use ChatGPT to develop Machine Learning Models?
Harnessing Machine Learning for Retail Demand Forecasting Excellence.
Anomaly detection Machine Learning algorithms.
Frequently Asked Questions
What is the significance of regression analysis?
Regression analysis is essential for identifying relationships between variables. It helps in decision-making across statistics, economics, and machine learning. By analyzing data trends, it predicts outcomes and optimizes processes.
How can regression analysis help in education?
Regression analysis can identify factors influencing student performance, helping educators improve teaching strategies and resource allocation. It provides insights into how different variables affect academic success.
Why is it important to pursue interests beyond the syllabus?
Exploring interests beyond the syllabus fosters a more profound love for learning, enhances critical thinking, and broadens knowledge. It encourages curiosity and innovation, equipping students with versatile skills for diverse career paths.
Closing Lines
Balancing academic requirements with personal interests is crucial in our pursuit of knowledge. Mahima’s journey illustrates the importance of embracing curiosity and exploring subjects beyond the syllabus. By understanding regression analysis, she discovered a passion for data-driven insights, demonstrating that stepping outside conventional boundaries can lead to profound personal and intellectual growth.
Authors
-
Written by:
Neha SinghReviewed by:
