Difference between revisions of "Stat 202 2019S Course Materials"
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| + | '''Lab 1:''' Choose a topic from the list below, or choose your own topic. Find data on that topic. Try Google and Kaggle.Com. If you can't find data on your topic, choose another topic. Then answer the following questions: | ||
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| + | * What is your topic? | ||
| + | * How did you find data? | ||
| + | * What dead ends did you encounter? | ||
| + | * Is the data structured or unstructured? | ||
| + | * What are the cases? | ||
| + | * What are some of the variables (there may be too many to list)? | ||
| + | * Is each of these variables quantitative, ordinal categorical, nominal categorical, binary, or identifier? | ||
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| + | Suggested topics for data search: (actually, whatever interests you): sports (of various kinds, there are lots of free good data on baseball), entertainment, movies (again good data), law, criminology, government, city planning, architecture, weather, climate, geology, seismology, medicine, epidemiology, health, fitness, biology, evolution, extinction, ecology, math, computer science, statistics, data science, anthropology, ethnic studies, gender studies, history, sociology, culture, tourism, archeology, art, literature, writing, journalism, census, linguistics, finance, economics, business, astronomy, physics, chemistry, library sciences, theology, anything else you can think of. | ||
Revision as of 21:58, 13 January 2019
Spring 2019 Course Materials go here:
Lab 1: Choose a topic from the list below, or choose your own topic. Find data on that topic. Try Google and Kaggle.Com. If you can't find data on your topic, choose another topic. Then answer the following questions:
- What is your topic?
- How did you find data?
- What dead ends did you encounter?
- Is the data structured or unstructured?
- What are the cases?
- What are some of the variables (there may be too many to list)?
- Is each of these variables quantitative, ordinal categorical, nominal categorical, binary, or identifier?
Suggested topics for data search: (actually, whatever interests you): sports (of various kinds, there are lots of free good data on baseball), entertainment, movies (again good data), law, criminology, government, city planning, architecture, weather, climate, geology, seismology, medicine, epidemiology, health, fitness, biology, evolution, extinction, ecology, math, computer science, statistics, data science, anthropology, ethnic studies, gender studies, history, sociology, culture, tourism, archeology, art, literature, writing, journalism, census, linguistics, finance, economics, business, astronomy, physics, chemistry, library sciences, theology, anything else you can think of.
