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STAT 2

Lecture 1:

An introduction

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About the lecturer

Brad Luen

bradluen@stat.berkeley.edu(put STAT 2 in subject line)

http://www.stat.berkeley.edu/users/bradluen/stat2/

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Why are we here?

World is full of data

Statistics lets us make sense ofdata

Therefore, statistics helps us

make sense of the world

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Why are we here?

It's a requirement... It's a prerequisite... It's easy units...

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Why are we here?

Statistical literacy: understandstatistical statements

Statistical reasoning: drawconclusions from statisticalstatements

Statistical thinking: investigateproblems statistically

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What we're going to do today

Course outline: everything you

have to do this semester Course structure: everything you

need to know about statistics, in

half an hour

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CourseStructure

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Week in, week out

Textbook: Statistics byFreedman, Pisani & Purves, 3rd or4th ed.

Lectures: M-F 10-11 am, hereDiscussion: M-Th: 11 am in 332

Evans; 11 am in 344 Evans;12 pm in 344 Evans

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Grading

Weekly quizzes: 20% (best 5 of6)

Midterm: Friday 18th July: 30% Final: Friday 15th August: 50%For full schedule, see course

webpageFirst quiz: this Thursday duringdiscussion

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Where to get help

Brad's office hours: Wed 11am -1pm

Partha's office hours: W 9-10 am,

Th 3-4 pm Daniel's office hours: Tu 9-10

am, 2-3 pmProbably in 307 Evans but to beconfirmed

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Protips

Don't fall behind! Read the book! Come to office hours!

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Questions?

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I

Dealing with data:weeks 1 and 2

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Design of experiments

How do you design anexperiment to show what you

want to show? How can you set up a fair

comparison? What if you can't do an

experiment?

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Summarising data

Summarise data through: Graphs Averages Spreads

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Mistakes in measurement

Physics sez: V=IRIs physics right?

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II

The best fit:weeks 3 and 4

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Correlation

How strong is therelationship?

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Regression

Which line shows theaverage weight giventhe person's height?

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Prediction

How accurately can wepredict a person'sweight, given theirheight?

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Probability

What does chance mean?

How do we calculate probabilitiesof complex events? What if we can't do exact

calculations?

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Intermission: The outcome effect

France vs Holland soccer, June18th

Most sportsbooks: bet $1, win $2

if France wins One sportsbook: bet $1, win $2 if

France wins OR draws I bet on France Holland 4, France 1

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The outcome effect

After the fact, probability ismeaningless

Single probability statementsgenerally can't be judged onoutcomes alone

Need multiple observations for atest

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III

Variation:Weeks 5 and 6

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The law of averages

After taking a large number ofobservations, the observed

average is very close to thetheoretical average... if the theoryis right

How can we use this knowledgeto statistically model events?

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How to gamble

Don't gamble

In most cases, you're sure to losein the long run We can analyse games (and life)

in terms of expected value

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Taking samples and surveys

How do we avoid bias?

How do we deal with chanceerrors? How large should our sample size

be?

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How accurate are samples?

How accurate are opinion pollpercentages? How accurate are experimental

averages?

Confidence intervals: the mostconfusing things in all statistics

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IV

Putting it to the test:Weeks 7 and 8

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More about errors

Types of error Models for error Checking for cheats

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Is the difference real?

Testing for a significant

difference What tests assume

How to interpret test results

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Is the difference real: advanced

Looking too hard Bad models, bad tests Make your own tests

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Recap

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Statistical literacy

Understand graphs

Understand probabilisticstatements Understand experimental and

survey results

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Statistical reasoning

Draw conclusions from graphsand data summaries

Make decisions based onprobabilities Evaluate conclusions others have

drawn from statistics

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Statistical thinking

Design experiments to testhypotheses

Build and evaluate predictionmodels

Understand the relative strengthof statistical conclusions

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Next time:

How statistics helpedto vanquish polio