Christina Shanahan

[Christina Shanahan @stina_28]

This article discusses solving second order differential equations in python. It gives a few good examples that are clear and easy to understand.
#math3185

https://t.co/OhKQGcJ2nh

[Christina Shanahan @stina_28]

@BenEpp_19 I like how this article gives a lot of background information. It’s nice to be able to see things build off of each other and I think it makes it easier to comprehend.

[Christina Shanahan @stina_28]

@_jaydonp I really like the step by step breakdown in this article. I think it makes it easier to follow and understand. It also makes it easier to follow what the code is doing.

[Christina Shanahan @stina_28]

This article goes into depth about R-squared. The graphs that go along with the discussion are super helpful. I like how it shows that an R-squared value can be high but that doesn’t always mean the line will be a good model.
#math3185

https://t.co/00hT2GuVTA

[Christina Shanahan @stina_28]

@g_miller3003 I thought the interactive graphs were super cool. You can experiment with the data to help better understand outcomes of certain situations.

[Christina Shanahan @stina_28]

@BenEpp_19 I like how this article talked about the difference between PCR and PLS regression. I also liked the brief step walkthrough for PLS in Python.

[Christina Shanahan @stina_28]

@_jaydonp I like how in the graph comparing the sin function and the data points that it shows how far each point is from the line. It helps to see how good of a fit the line is.

[Christina Shanahan @stina_28]

This article talks about when/why you would use a weighted least squares regression. It also gives a walkthrough of implementing it into python.
#math3185

https://t.co/Fa29RHFkx3

[Christina Shanahan @stina_28]

@BenEpp_19 I like how concise this article is. I thought the comparison in the last graph was interesting.

[Christina Shanahan @stina_28]

@_jaydonp I liked the real world application in the introduction where it mentions when you may not want to use splines. I thought the comparison at the end between the parametric curve and cubic spline methods was cool.

[Christina Shanahan @stina_28]

@g_miller3003 I like the comparisons this article made and the detail it goes into for everything. The images are also super helpful!

[Christina Shanahan @stina_28]

This article walks through cubic splines using an example. I feel it does a good job explaining them in detail. It also gives a sample code for the equation. I thought the Regressio Library was interesting. #math3185

https://t.co/ESUXJ3K7q0

[Christina Shanahan @stina_28]

@g_miller3003 I like how this articles gives the advantages of Newtons Divided Difference. I thought it was cool that it gave code for several different coding languages.

[Christina Shanahan @stina_28]

@BenEpp_19 I like how organized the code feels. It is also a lot shorter than I thought it would be.

[Christina Shanahan @stina_28]

@_jaydonp I thought it was cool that this article gave several different examples of interpolating polynomials. I liked how it answers questions about some of the concepts too.

[Christina Shanahan @stina_28]

This article briefly discusses Neville’s Method. It gives a good worked out example and then a piece of code for Neville’s Method to compare answers to.
#math3185

https://t.co/9LgXivkfqE

[Christina Shanahan @stina_28]

@g_miller3003 I like how many different examples are given and how they’re all completely worked out. I also like how organized the article looks.

[Christina Shanahan @stina_28]

@BenEpp_19 This was a good refresher since we are coming back from break. I like how it gives two different approaches to solving the problem.

[Christina Shanahan @stina_28]

@_jaydonp I feel like this is a good reminder to be careful how you type your equations into python. I think it’s easy to get lost because everything is in one line.

[Christina Shanahan @stina_28]

This article talks about what the least squares method is and why we use it. It provides a good real world example of where it could be used. #math3185

https://t.co/5VyX1WBHXu