Difference between revisions of "Stat 202 2018F Course Materials"
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Fall 2018 Course Materials will go here. | Fall 2018 Course Materials will go here. | ||
| − | '''Materials:''' [[Old_Lectures:_Stat_202|''[Materials From Past]'']][[Homework:_Stat_202_Summer_2016|''[Exercises with Solutions]'']][[Data:_Stat_202|''[Data from 2017]'']][[Links:_Stat_202_Summer_2016|''[Links and Other Materials]'']] | + | '''Materials:''' [[Objectives_2018F|''[Objectives]'']][[Old_Lectures:_Stat_202|''[Materials From Past]'']][[Homework:_Stat_202_Summer_2016|''[Exercises with Solutions]'']][[Data:_Stat_202|''[Data from 2017]'']][[Links:_Stat_202_Summer_2016|''[Links and Other Materials]'']] |
We will stop using data from 2017 as soon as the textbook snafu is sorted out. | We will stop using data from 2017 as soon as the textbook snafu is sorted out. | ||
Revision as of 16:15, 16 September 2018
Fall 2018 Course Materials will go here.
Materials: [Objectives][Materials From Past][Exercises with Solutions][Data from 2017][Links and Other Materials]
We will stop using data from 2017 as soon as the textbook snafu is sorted out.
More Data Sets:
- Small Diamonds Data Set (3000 diamonds sampled from full Diamonds Data Set): diamonds3K.
- Codebook for full Diamonds Data Set.
- Cars Miles Per Gallon Data Set: mpg.
- Codebook for Cars Miles Per Gallon Data Set.
- Simulated Exam Scores: rounded N(70,10): egexam.
Homework 0: Choose a topic from the list below. 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)?
- Are the 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.
