Statistical Applets created by me
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Dr. Nisha Arora
Jul 24, 2026, 2:33:47 AMJul 24
to dataanalys...@googlegroups.com
Dear All,
I always use applets and simulations to teach Linear Algebra, Statistics or conceptual topics in Machine Learning and Data Science.
Earlier, I had created sample simulations in Shiny R but didn't deploy it. This time, I created some tools using Python and deployed those so others can also use them for their teaching-learning purpose.
Here are the links of Statistical Simulations apps for Binomial, Poisson, Uniform, and Normal distribution:
https://enjoy-stats-binomial-distribution.streamlit.app/
https://enjoy-stats-poison-distribution.streamlit.app/
https://enjoy-stats-discrete-uniform-app.streamlit.app/
https://enjoy-stats-continuous-uniform-app.streamlit.app/
https://enjoy-stats-normal-distribution.streamlit.app/
Feel free to use or share those with learners. Any feedback, most welcome!
I'll add more such apps for other topics too.
I always use applets and simulations to teach Linear Algebra, Statistics or conceptual topics in Machine Learning and Data Science.
Earlier, I had created sample simulations in Shiny R but didn't deploy it. This time, I created some tools using Python and deployed those so others can also use them for their teaching-learning purpose.
Here are the links of Statistical Simulations apps for Binomial, Poisson, Uniform, and Normal distribution:
https://enjoy-stats-binomial-distribution.streamlit.app/
https://enjoy-stats-poison-distribution.streamlit.app/
https://enjoy-stats-discrete-uniform-app.streamlit.app/
https://enjoy-stats-continuous-uniform-app.streamlit.app/
https://enjoy-stats-normal-distribution.streamlit.app/
Feel free to use or share those with learners. Any feedback, most welcome!
I'll add more such apps for other topics too.
Warm regards,
Dr. Nisha Arora
Trainer | Author of Python-Powered Excel ( Analytics, Data Science & AI )
📍 Pune, India | 📞 +91-9654582757
Dr. Nisha Arora
Trainer | Author of Python-Powered Excel ( Analytics, Data Science & AI )
📍 Pune, India | 📞 +91-9654582757
Preeti Dabas
Jul 24, 2026, 3:52:20 AMJul 24
to dataanalys...@googlegroups.com
Wow Ma'am,
This is amazing. Thanks a lot for sharing the treasure.
Regards.
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Dr. Nisha Arora
Jul 29, 2026, 3:12:08 AMJul 29
to dataanalys...@googlegroups.com
Dear All,
Some of you found these applets useful to teach statistical concepts to non-math students as they can play, interact and grasp the concept, even if they fear math (Math is beautiful and should not be feared but I know many are not comfortable with symbols and equations)
In this series, I've created another app, which helps explore the relationship between 2 numerical variables, explain the concept of covariance, correlation (spurious correlation, almost zero correlation etc) via scatter plot and numbers.
Some of you found these applets useful to teach statistical concepts to non-math students as they can play, interact and grasp the concept, even if they fear math (Math is beautiful and should not be feared but I know many are not comfortable with symbols and equations)
In this series, I've created another app, which helps explore the relationship between 2 numerical variables, explain the concept of covariance, correlation (spurious correlation, almost zero correlation etc) via scatter plot and numbers.
Check it out here: https://enjoy-stats-covariance-correlation-scatterplot.streamlit.app/
Warm regards,
Dr. Nisha Arora
Dr. Nisha Arora
Trainer | Author | Reviewer | Speaker ( Analytics, Data Science & AI )
📧 dr.aro...@gmail.com | 📍 Pune, India | 📞 +91-9654582757
📧 dr.aro...@gmail.com | 📍 Pune, India | 📞 +91-9654582757
Dr. Nisha Arora
Jul 30, 2026, 12:57:17 AMJul 30
to DataAnalysis
Dear All,
Thanks @Dr Preeti.
Added one more app to the list.
While Teaching Linear Regression, we always discuss scatterplot, possible lines we can fit and then finding best fit line. For this I usually draw lines or use animations so learners can see candidate lines and their comparision.
So I create an app, that allows users to try multiple candidate lines, visualize the same, check model coffiecient and cost functions simultineously all with click off a button. Learners can also see best-fit line and Cost function.
Here's the app for you to explore:
https://enjoy-stats-best-fit-line.streamlit.app/
You feedback will help me make refinements, if needed or build more apps that are useful.
Thanks @Dr Preeti.
Added one more app to the list.
While Teaching Linear Regression, we always discuss scatterplot, possible lines we can fit and then finding best fit line. For this I usually draw lines or use animations so learners can see candidate lines and their comparision.
So I create an app, that allows users to try multiple candidate lines, visualize the same, check model coffiecient and cost functions simultineously all with click off a button. Learners can also see best-fit line and Cost function.
Here's the app for you to explore:
https://enjoy-stats-best-fit-line.streamlit.app/
You feedback will help me make refinements, if needed or build more apps that are useful.
Dr. Nisha Arora
Aug 5, 2026, 8:24:26 AMAug 5
to dataanalys...@googlegroups.com
Dear All,
While trying Linear regression to predict one variable based on the other, how do you draw the "best" line through those points, the line that mathematically fits the data best? As multiple lines are possible, which one is the best?
While trying Linear regression to predict one variable based on the other, how do you draw the "best" line through those points, the line that mathematically fits the data best? As multiple lines are possible, which one is the best?
The answer lies in the residuals. The best-fit line is the one that minimizes the overall prediction error, making it the most reliable representation of the linear relationship in the data.
That's much easier to understand when you can interact with the data.
So I built this interactive app where you can:
✔ Choose a built-in dataset to play with
✔ Try multiple candidate lines, observe their coefficients and associated cost
✔ Watch the best-fit line with one click
✔ Develop an intuition for linear regression instead of simply memorizing formulas
👉Try it here: https://lnkd.in/dthWYmgA or watch a quick video attached to see it's functionality
Warm regards,
Dr. Nisha Arora
Trainer | Author of Python-Powered Excel ( Analytics, Data Science & AI )
📍 Pune, India | 📞 +91-9654582757
Dr. Nisha Arora
Trainer | Author of Python-Powered Excel ( Analytics, Data Science & AI )
📍 Pune, India | 📞 +91-9654582757
Dr. Nisha Arora
Aug 17, 2026, 8:12:12 PMAug 17
to dataanalys...@googlegroups.com
Dear All,
I've built a simple app to play with and get intuitions, equation of a straight line, specifically for slope-intercept form (Many of my data science learners come from non-math backgrounds, this app is helping them learn the concept better). You might want to check: https://enjoy-stats-equation-of-a-line-slope-intercept.streamlit.app/
I've built a simple app to play with and get intuitions, equation of a straight line, specifically for slope-intercept form (Many of my data science learners come from non-math backgrounds, this app is helping them learn the concept better). You might want to check: https://enjoy-stats-equation-of-a-line-slope-intercept.streamlit.app/
Warm regards,
Dr. Nisha Arora
Trainer | Author | Reviewer | Speaker ( Analytics, Data Science & AI )
📧 dr.aro...@gmail.com | 📍 Pune, India | 📞 +91-9654582757
Dr. Nisha Arora
Trainer | Author | Reviewer | Speaker ( Analytics, Data Science & AI )
📧 dr.aro...@gmail.com | 📍 Pune, India | 📞 +91-9654582757
Dr. Nisha Arora
Aug 24, 2026, 7:13:24 PMAug 24
to dataanalys...@googlegroups.com
Dear All,
If you have used logistic regression, you might have seen s-shape sigmoid function and effect of decision threshold on class prediction.
Imbalanced data and accuracy paradox, etc. My next app helps you play with these things. Check it out here:
https://enjoy-stats-logistic-regression-app.streamlit.app/
If you have used logistic regression, you might have seen s-shape sigmoid function and effect of decision threshold on class prediction.
Imbalanced data and accuracy paradox, etc. My next app helps you play with these things. Check it out here:
https://enjoy-stats-logistic-regression-app.streamlit.app/
Warm regards,
Dr. Nisha Arora
Trainer | Author | Reviewer | Speaker ( Analytics, Data Science & AI )
📧 dr.aro...@gmail.com | 📍 Pune, India | 📞 +91-9654582757
Dr. Nisha Arora
Trainer | Author | Reviewer | Speaker ( Analytics, Data Science & AI )
📧 dr.aro...@gmail.com | 📍 Pune, India | 📞 +91-9654582757
Dr. Nisha Arora
Aug 25, 2026, 3:41:15 AMAug 25
to dataanalys...@googlegroups.com
Dear All,
Long back I had written multiple articles about performance evaluation metrics of classification models at my blog.
Some of my answers at forums also explained Odd-Ratio (something which confuses learners and I have even seen trainers explaining the wrong thing.
I created an app that computes and explains (briefly) some common model evaluation metrics for classification problems.
ROC-AUC and Odds-Ratio deserve their separate apps for simplistic explanations, and will launch those too.
Here's the link: https://enjoy-stats-classification-metric-app.streamlit.app/
Long back I had written multiple articles about performance evaluation metrics of classification models at my blog.
Some of my answers at forums also explained Odd-Ratio (something which confuses learners and I have even seen trainers explaining the wrong thing.
I created an app that computes and explains (briefly) some common model evaluation metrics for classification problems.
ROC-AUC and Odds-Ratio deserve their separate apps for simplistic explanations, and will launch those too.
Here's the link: https://enjoy-stats-classification-metric-app.streamlit.app/
Warm regards,
Dr. Nisha Arora
Trainer | Author | Reviewer | Speaker ( Analytics, Data Science & AI )
📧 dr.aro...@gmail.com | 📍 Pune, India | 📞 +91-9654582757
Dr. Nisha Arora
Trainer | Author | Reviewer | Speaker ( Analytics, Data Science & AI )
📧 dr.aro...@gmail.com | 📍 Pune, India | 📞 +91-9654582757
Dr. Nisha Arora
Aug 31, 2026, 8:33:48 AMAug 31
to dataanalys...@googlegroups.com
Dear All,
K Nearest Neighbours is one of the simplest ML algorithms to understand. It is a non parametric algorithm which does not make any assumptions about the Function
Y = F(X)
Although popular for classification, it can also be used for prediction tasks.
A simple applet like the following helps you see the impact of 'k' (number of neighbours) on the prediction in case of binary/ multi-class classification or prediction/regression task.
Explore the applet here: https://enjoy-stats-knn-classification-regression.streamlit.app/
Warm regards,
Dr. Nisha Arora
Trainer | Author | Reviewer | Speaker ( Analytics, Data Science & AI )
📧 dr.aro...@gmail.com | 📍 Pune, India | 📞 +91-9654582757
Dr. Nisha Arora
Trainer | Author | Reviewer | Speaker ( Analytics, Data Science & AI )
📧 dr.aro...@gmail.com | 📍 Pune, India | 📞 +91-9654582757
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