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CLOSED! Freestyle prediction of grades in yet another MOODY data set
March 30 ,2022

This is the next in the sequence of data puzzles about grading methods of the eccentric professor Moody. Professor Moody found out that his former grading methods were leaked to the student by treacherous TA and changed his grading methods (and the TA).
Unfortunately, again the data was leaked to the students (Professor Moody does not use passwords). It indicates that Professor Moody may be tougher on certain majors and also may apply different grading criteria for different student seniority levels
Can you build a prediction model which will mimic Moody's grading as closely as possible?

Access the training and testing datasets and further instructions here:
Course Textbook:
Kaggle submission instructions

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Predict the sound that the mysterious box makes
May 15,2021

A mysterious box was found on the beach. Despite spending probably years in the water, it still works! But what does it do? It has four inputs (electric), a switch, and emits different weird and scary sounds as output in response to the electric signals on the inputs and different switch positions. It sizzles, gurgles, hisses, ominously tics like a bomb…..but nothing happens - just sounds. The training dataset describes which sounds have been noted in the laboratory (highest security level!) in nearly 20,000 experiments combining different input signals and switch positions. Using training data - built a predictive model which can be tested on the test data which can predict as well as possible the sounds which the box will produce in response to the inputs and switch positions. You can use any ML software from the R library and make sure you cross-validate!

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Predict Earnings of a Student
April 24,2021

Predict future earnings of students based on some obvious parameters such as major and GPA as well as some less obvious such as number of professional connections and even number of parking tickets (there is little known powerful theory linking the number of parking tickets and being the member of the infamous top 0.1%). Turns out that student earnings are quite predictable!

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Predict Grades in Professor Moody class
April 10,2021

Professor Moody has been teaching Statistics 101 classes for many years. His teaching evaluations went considerably south with the chief complaint: he DOES NOT seem to assign grades fairly. Students compared their scores among themselves and found quite a bit of discrepancy! But their complaints went nowhere since Professor promptly disappeared after posting the final grades and scores. A new brave TA managed to get hold of the carefully maintained grading table (spanning multiple years) of Professor Moody by messing a bit with Moody's computer. Well, let's not explain the details because he would get in trouble. Moreover, what he found was a remarkably structured account of how Professor Moody assigns his grades.
It seems Professor Moody is very alert in class. Remarkable but a little creepy, isn't it? Knowing this data, can you predict a grade for a student? Training data is available on Kaggle and lists the following attributes: major, seniority, score, attendance, questions, texting

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Hall of Fame - 2023

Taneesh Amin

Taneesh is one of top 5 scorers in the whole class. In addition he has won prediction challenge 2, with spectacular accuracy which provided dramatic ending on the Kaggle night!

Here is what Taneesh says about himself:

My name is Taneesh Amin and I am a Freshman (sophomore by the time you see this) graduating in 2026 with a major in Computer Science and the newly announced Data Science Major. Data101 was one of the more intellectually inspiring classes I have taken so far as a student. It really increased my love for Data Science, and I am so glad I am able to gain skills to pursue a career in it. If anyone had any interest in data science I would definitely recommend this course. If you are interested in seeing my continued data journey, I will be sharing it on my github (Taneesh04) and my Instagram ( where I analyze various patterns, mostly in sports using skills that have been taught to me in this class.

Rey Riordan

Rey has acheived top result (#1) in overall score in entire class (over 100%, maxing also extra credits!). Plus he placed top 5 overall in Quinlan competition for best overall prediction.

Here is what Rey says about himself and he even has something to share!

Hi, I'm a freshman pursuing majors in computer science and cognitive science as well as a minor in either mathematics or data science. I took this course to take my first steps into the field of data analysis, but I would like to stress to any incoming Data 101 students that this course is not about learning the gritty details of coding in R. Professor Imielinski focuses more on data science conceptually as being a way to think and analyze the world around us, which I think is much more useful! As a thanks for reading this far, here is a link to my notes that helped me do well in the class:

And as a final note, if your R code isn't working you probably either made a typo or missed a comma. Good luck to everyone!


Mayeesha has been on of the top 5 students in the class of 200 and also outstanding prediction challenges competitior (in the first two prediction challenges)

Here is what she says about herself and the class

Hi everyone, I’m Mayeesha! I am majoring in Cell Biology and Neuroscience and minoring in Psychology. I took Data 101 during my last semester as a graduating senior while trying to explore different career paths. I cannot stress enough how much this class has taught me about thinking analytically about the information presented to me. From realizing the role of bias in skewing samples and results to subsetting the data to find meaningful patterns, this class has shown me the importance of being critical about what I read and see on a daily basis. Despite my lack of coding experience, Professor Imielinski has been so encouraging and kind in office hours while showing me how to use R, which I feel much more comfortable with now! I look forward to using the data analysis skills I have gained in my future career and would recommend this course to anyone looking to gain a more keen understanding of how to analyze and present findings in a way that is meaningful to the audience at hand.


Melanie has achieved 2nd highest score in the class (also, like Rey, above 100 with extra credits). She also placed in top 5 of leaderboard for prediciton challenges

Here is what Melanie says about herself.

Hello! I’m a freshman majoring in mathematics and computer science. I took this class because I was interested in exploring data science and am currently considering it as a future career. I had a lot of fun figuring out the patterns in the prediction challenges and I’m thankful to Professor Imielinski for giving me the opportunity to learn and practice R! The skills I’ve learned in this class helped me to get a research position for the summer and I’m excited to apply my statistical analysis and R skills to data in the real world :)

Howard Luo

Howard is the winner of 2023 Quinlan competition!

He got the highest combine accuracy from all competitions and won the trophe this year! In addition he placed in top 3 out of 200 students in overall score in the class. He also saved me a few times discovering early on some crippling mistakes like publishing values of prediction variable (the one which is supposed to be missing!)

Here is what Howards says about himself:

Hey there! I'm a sophomore in the class of 2025, majoring in computer science, mathematics, and possibly the newly introduced data science major. I had originally intended to devote myself entirely to artificial intelligence, but I enjoy the statistical elements of CS that this class contains. This course far exceeded my expectations and serves as an excellent foundation for data science purposes. This course teaches many fundamental basics in R for practical applications, which makes it suitable for students across a wide range of majors. I would like to thank Professor Imieliński especially, as I would most likely not be continuing data science if not for him. Thank You!