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Tutor profile: Maggie C.

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Maggie C.
Tutor since 2012, Statistics & Data Science MS student
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Questions

Subject: German

TutorMe
Question:

What is the difference between "gleiche" and "selbe"? They both translate to "same".

Inactive
Maggie C.
Answer:

"Gleiche" is similar to the word "alike". If you and your friend buy matching jeans, "die zwei Jeans sind gleich". "Selbe" would apply if you and your friend buy the same pair of jeans and share them. The two of you have "die selbe Jeans."

Subject: Writing

TutorMe
Question:

What information should be part of your outline when writing an academic paper?

Inactive
Maggie C.
Answer:

When I write an outline, I make it as detailed as possible. In this way, I divide the project into chunks. The first chunk is just about analysis. What evidence from my research/readings can I use to make my argument? What is the most convincing order? How can I transition from one argument to the next? My outline will contain all the data I want to include as well as the thesis for the paper, and the thesis for each section. The second chunk of my project is the writing. Here I consider style and the smaller transitions. How do I transition from one detail to the next within a paragraph? How do I grab the reader's attention in the intro? How do I encourage them to continue thinking about this topic in the conclusion? I think it is easier to accomplish good analysis AND good style when you only focus on one task at a time.

Subject: Statistics

TutorMe
Question:

Please describe the normal distribution and why we use it for statistics.

Inactive
Maggie C.
Answer:

The normal distribution is a pattern that appears again and again in nature and many sciences. Imaging we have a data set of all the heights of women who are patients at a particular hospital. The average height might be something like 5' 4''. You can imagine that this will also be the most common height of women. More women will be 5' 4'' than say 5' 10''. This relationship between more-average and more-common creates the bell-shaped curve we call the normal distribution. Although datasets do not look exactly like the bell-curve, they often look very similar. That means that the bell curve can serve as a model for many situations. Things we know about the bell curve will be approximately true about any data set that looks like a bell curve.

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