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Defining Probability

- Lesson 8.8 -

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Khris Davis

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Khris Davis

Chris Davis

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Khris Davis

Chris Davis

Today’s Key Analysis (#1)

How improbable were the MLB records set by the two Khris/Chris Davis’s?

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Lesson 8.8

Guided Notes

Handout: skewthescript.org/5-1

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Topics

  • Law of large numbers
  • Simple definition of probability
  • Properties of probabilities
  • Probability models

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Topics

  • Law of large numbers
  • Simple definition of probability
  • Properties of probabilities
  • Probability models

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Law of Large Numbers

Law of large numbers: After many trials, the relative frequency of outcomes will approach their probability.

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Source: Digital First project from Bedford, Freeman, & Worth publishers

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Source: Digital First project from Bedford, Freeman, & Worth publishers

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Being “due for one”

You have a fair coin. You flip it 10 times. In which situation is getting tails (T) on your next flip more likely?

Situation 1: HTTHHTHTHT

Situation 2: HTTHHHHHHH

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Being “due for one”

You have a fair coin. You flip it 10 times. In which situation is getting tails (T) on your next flip more likely?

Situation 1: HTTHHTHTHT

Situation 2: HTTHHHHHHH

It’s equally likely! The probability doesn’t change because of previous results.

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Being “due for one”

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Khris Davis

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Khris Davis

Chris Davis

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Khris Davis

2015

Batting Average: 0.247

Home Runs: 27

Source: Baseball Reference

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Khris Davis

2015

Batting Average: 0.247

Home Runs: 27

24.7% of his at-bats ended in hits (rather than outs)

Source: Baseball Reference

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Chris Davis

2015

Batting Average: 0.262

Home Runs: 47

Source: Baseball Reference

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Chris Davis

2015

Batting Average: 0.262

Home Runs: 47

Source: Baseball Reference

Led the MLB

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Being “due for one”

Chris Davis

2015

Batting Average: 0.262

Home Runs: 47

Source: Baseball Reference

Led the MLB

Led the MLB in neck size (probably)

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Being “due for one”

Chris Davis

2018

Batting Average:

Home Runs:

Source: Baseball Reference

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Being “due for one”

Chris Davis

2018

Batting Average: 0.168

Home Runs: 16

Source: Baseball Reference

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Chris Davis

2018

Batting Average: 0.168

Home Runs: 16

Source: Baseball Reference

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0,

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2,

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1,

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1, 1,

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1, 1, 0,

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

Sept. 2018

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

Sept. 2018

1,

Sept. 14, 2018

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

Sept. 2018

1, 0,

Sept. 14, 2018

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

Sept. 2018

1, 0, 0,

Sept. 14, 2018

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

Sept. 2018

1, 0, 0, 0, 0, 0

Sept. 14, 2018

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

Sept. 2018

1, 0, 0, 0, 0, 0

Sept. 14, 2018

April 2019

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

Sept. 2018

1, 0, 0, 0, 0, 0

Sept. 14, 2018

April 2019

“He’s due for a hit”

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

Sept. 2018

1, 0, 0, 0, 0, 0

Sept. 14, 2018

April 2019

0,

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

Sept. 2018

1, 0, 0, 0, 0, 0

Sept. 14, 2018

April 2019

0, 0,

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

Sept. 2018

1, 0, 0, 0, 0, 0

Sept. 14, 2018

April 2019

0, 0, 0,

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

Sept. 2018

1, 0, 0, 0, 0, 0

Sept. 14, 2018

April 2019

0, 0, 0, 0,

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

Sept. 2018

1, 0, 0, 0, 0, 0

Sept. 14, 2018

April 2019

0, 0, 0, 0,

“He’s due for a hit”

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

Sept. 2018

1, 0, 0, 0, 0, 0

Sept. 14, 2018

April 2019

0, 0, 0, 0, 0,

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

Sept. 2018

1, 0, 0, 0, 0, 0

Sept. 14, 2018

April 2019

0, 0, 0, 0, 0, 0,

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

Sept. 2018

1, 0, 0, 0, 0, 0

Sept. 14, 2018

April 2019

0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

Sept. 2018

1, 0, 0, 0, 0, 0

Sept. 14, 2018

April 2019

0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,

17 straight hitless games

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

Sept. 2018

1, 0, 0, 0, 0, 0

Sept. 14, 2018

April 2019

0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Chris Davis

Number of Hits per Game

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

Sept. 2018

1, 0, 0, 0, 0, 0

Sept. 14, 2018

April 2019

0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3

April 13, 2019

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Being “due for one”

Chris Davis

54 straight at-bats without a hit

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

Sept. 2018

1, 0, 0, 0, 0, 0

Sept. 14, 2018

April 2019

0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3

April 13, 2019

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Being “due for one”

Chris Davis

54 straight at-bats without a hit

MLB Record

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

Sept. 2018

1, 0, 0, 0, 0, 0

Sept. 14, 2018

April 2019

0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3

April 13, 2019

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Being “due for one”

Chris Davis

54 straight at-bats without a hit

MLB Record

May 2018

0, 2, 1, 1, 0, 0, 1, 1, 0, 2, 0, 0, 1

Sept. 2018

1, 0, 0, 0, 0, 0

Sept. 14, 2018

April 2019

0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3

April 13, 2019

MLB modern-era began in 1900! All-time records are rare.

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Chris asks for the ball

Teammates celebrate

After the hit that broke the streak…

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Unlike the coin flips, Chris Davis’s chance at getting a hit isn’t the same for every at-bat. However, the “due for one” logic is still flawed:

  • Repeated failure doesn’t indicate a higher chance of success on a future attempt. If anything, it may indicate your original estimate of the probability of success was already too high.

“Due for one” myth

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Being “due for one”

A Tale of Two Khris/Chris Davis’s

Khris Davis

Chris Davis

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Being “due for one”

Khris Davis

2015

Batting Average: 0.247

Home Runs: 27

24.7% of his at-bats ended in hits (rather than outs)

Source: Baseball Reference

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Khris Davis

2015 - 0.247

Source: Baseball Reference

Batting Average

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Khris Davis

2015 - 0.247

2016 - 0.247

Source: Baseball Reference

Batting Average

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Khris Davis

2015 - 0.247

2016 - 0.247

2017 - 0.247

Source: Baseball Reference

Batting Average

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Khris Davis

2015 - 0.247

2016 - 0.247

2017 - 0.247

2018 - 0.247

Source: Baseball Reference

Batting Average

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Khris Davis

2015 - 0.247 (97/392)

2016 - 0.247 (137/555)

2017 - 0.247 (140/566)

2018 - 0.247 (142/576)

Source: Baseball Reference

Batting Average

Hits

At-Bats

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Being “due for one”

Khris Davis

2015 - 0.247

2016 - 0.247

2017 - 0.247

2018 - 0.247

Batting Average

MLB Record for longest batting average streak*

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Khris Davis

2015 - 0.247

2016 - 0.247

2017 - 0.247

2018 - 0.247

20190.220

Batting Average

A Tale of Two Khris/Chris Davis’s

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Being “due for one”

Khris Davis

2015 - 0.247

2016 - 0.247

2017 - 0.247

2018 - 0.247

20190.220

Batting Average

I guess he was “due for” a year with a different batting average! Lol jk.

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Topics

  • Law of large numbers
  • Simple definition of probability
  • Properties of probabilities
  • Probability models

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Simple definition of probability

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Simple definition of probability

This is the simple definition of probability

    • Only used when all outcomes are equally likely.

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Simple definition of probability

There are 8 red marbles and 12 blue marbles in a jar. What is the probability of selecting a red marble from the jar?

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There are 8 red marbles and 12 blue marbles in a jar. What is the probability of selecting a red marble from the jar?

R: Event of selecting a red marble from the jar

P(R): Probability of Event R occurring

Simple definition of probability

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Simple definition of probability

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Simple definition of probability

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Simple definition of probability

 

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Simple definition of probability

 

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Simple definition of probability

 

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Simple definition of probability

 

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Topics

  • Law of large numbers
  • Simple definition of probability
  • Properties of probabilities
  • Probability models

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Properties of Probabilities

Properties:

 

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Properties:

  • Probabilities are always between 0 – 1 (0% - 100%).

Properties of Probabilities

 

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Properties of Probabilities

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Properties of Probabilities

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Properties:

  • Probabilities are always between 0 – 1 (0% - 100%).
  • The probabilities of all possible events add to 1 (100%).

Properties of Probabilities

 

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Properties of Probabilities

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Properties of Probabilities

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Properties of Probabilities

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Properties of Probabilities

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Properties:

  • Probabilities are always between 0 – 1 (0% - 100%).
  • The probabilities of all possible events add to 1 (100%).
  • Complement rule: the probability of event A not happening, P(AC), is equal to 1 – P(A).

Properties of Probabilities

 

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Properties of Probabilities

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Properties of Probabilities

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Properties of Probabilities

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Properties of Probabilities

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Properties of Probabilities

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Topics

  • Law of large numbers
  • Simple definition of probability
  • Properties of probabilities
  • Probability models

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Probability Models

Probability models: List a set of outcomes and their probabilities

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Probability Models

Probability models: List a set of outcomes and their probabilities.

Properties:

  • All probabilities are between 0 – 1.
  • All probabilities add to 1.

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Probability Models

I have a bag of 20 beads. They are a mix of clear/solid and red/green. There are 6 clear red beads in the bag and 8 red solid beads. There are 2 clear green beads and 4 green solid beads.

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Probability Models

Bead Type

clear red

red solid

clear green

green solid

Probability

I have a bag of 20 beads. They are a mix of clear/solid and red/green. There are 6 clear red beads in the bag and 8 red solid beads. There are 2 clear green beads and 4 green solid beads.

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Probability Models

1. All probabilities are between 0 – 1

2. All probabilities add to 1

I have a bag of 20 beads. They are a mix of clear/solid and red/green. There are 6 clear red beads in the bag and 8 red solid beads. There are 2 clear green beads and 4 green solid beads.

Bead Type

clear red

red solid

clear green

green solid

Probability

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Probability Models

1. All probabilities are between 0 – 1

2. All probabilities add to 1

I have a bag of 20 beads. They are a mix of clear/solid and red/green. There are 6 clear red beads in the bag and 8 red solid beads. There are 2 clear green beads and 4 green solid beads.

Bead Type

clear red

red solid

clear green

green solid

Probability

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Probability Models

1. All probabilities are between 0 – 1

2. All probabilities add to 1 🡪 0.3+0.4+0.1+0.2

I have a bag of 20 beads. They are a mix of clear/solid and red/green. There are 6 clear red beads in the bag and 8 red solid beads. There are 2 clear green beads and 4 green solid beads.

Bead Type

clear red

red solid

clear green

green solid

Probability

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Probability Models

1. All probabilities are between 0 – 1

2. All probabilities add to 1 🡪 0.3+0.4+0.1+0.2 = 1

I have a bag of 20 beads. They are a mix of clear/solid and red/green. There are 6 clear red beads in the bag and 8 red solid beads. There are 2 clear green beads and 4 green solid beads.

Bead Type

clear red

red solid

clear green

green solid

Probability

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Probability Models

Let: R = Select a red bead, Q = Select a red solid bead

1. Find P(Q): 2. Find P(R):

3. Find P(QC): 4. Find P(RC):

Bead Type

clear red

red solid

clear green

green solid

Probability

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Bead Type

clear red

red solid

clear green

green solid

Probability

Probability Models

1. Find P(Q): 2. Find P(R):

3. Find P(QC): 4. Find P(RC):

Let: R = Select a red bead, Q = Select a red solid bead

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Bead Type

clear red

red solid

clear green

green solid

Probability

Probability Models

1. Find P(Q): 0.40 2. Find P(R):

3. Find P(QC): 4. Find P(RC):

Let: R = Select a red bead, Q = Select a red solid bead

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Bead Type

clear red

red solid

clear green

green solid

Probability

Probability Models

1. Find P(Q): 0.40 2. Find P(R):

3. Find P(QC): 4. Find P(RC):

Let: R = Select a red bead, Q = Select a red solid bead

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Bead Type

clear red

red solid

clear green

green solid

Probability

Probability Models

1. Find P(Q): 0.40 2. Find P(R): 0.3 + 0.4 = 0.7

3. Find P(QC): 4. Find P(RC):

Let: R = Select a red bead, Q = Select a red solid bead

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Bead Type

clear red

red solid

clear green

green solid

Probability

Probability Models

1. Find P(Q): 0.40 2. Find P(R): 0.3 + 0.4 = 0.7

3. Find P(QC): 4. Find P(RC):

Let: R = Select a red bead, Q = Select a red solid bead

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Bead Type

clear red

red solid

clear green

green solid

Probability

Probability Models

1. Find P(Q): 0.40 2. Find P(R): 0.3 + 0.4 = 0.7

3. Find P(QC): .3+.1+.2=.6 4. Find P(RC):

Let: R = Select a red bead, Q = Select a red solid bead

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Bead Type

clear red

red solid

clear green

green solid

Probability

Probability Models

1. Find P(Q): 0.40 2. Find P(R): 0.3 + 0.4 = 0.7

3. Find P(QC): .3+.1+.2=.6 4. Find P(RC):

Let: R = Select a red bead, Q = Select a red solid bead

0.4

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Bead Type

clear red

red solid

clear green

green solid

Probability

Probability Models

1. Find P(Q): 0.40 2. Find P(R): 0.3 + 0.4 = 0.7

3. Find P(QC): .3+.1+.2=.6 4. Find P(RC):

or 1 - .4 = .6

Let: R = Select a red bead, Q = Select a red solid bead

0.4

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Bead Type

clear red

red solid

clear green

green solid

Probability

Probability Models

1. Find P(Q): 0.40 2. Find P(R): 0.3 + 0.4 = 0.7

3. Find P(QC): .3+.1+.2=.6 4. Find P(RC):

or 1 - .4 = .6

Let: R = Select a red bead, Q = Select a red solid bead

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Bead Type

clear red

red solid

clear green

green solid

Probability

Probability Models

1. Find P(Q): 0.40 2. Find P(R): 0.3 + 0.4 = 0.7

3. Find P(QC): .3+.1+.2=.6 4. Find P(RC): 0.1 + 0.2 = 0.3

or 1 - .4 = .6

Let: R = Select a red bead, Q = Select a red solid bead

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Bead Type

clear red

red solid

clear green

green solid

Probability

Probability Models

1. Find P(Q): 0.40 2. Find P(R): 0.3 + 0.4 = 0.7

3. Find P(QC): .3+.1+.2=.6 4. Find P(RC): 0.1 + 0.2 = 0.3

or 1 - .4 = .6

0.7

Let: R = Select a red bead, Q = Select a red solid bead

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Bead Type

clear red

red solid

clear green

green solid

Probability

Probability Models

1. Find P(Q): 0.40 2. Find P(R): 0.3 + 0.4 = 0.7

3. Find P(QC): .3+.1+.2=.6 4. Find P(RC): 0.1 + 0.2 = 0.3

or 1 - .4 = .6 or 1 - 0.7 = 0.3

Let: R = Select a red bead, Q = Select a red solid bead

0.7

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Lesson 8.8

Discussion

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How do police choose who to stop?

During the “Stop and Frisk” program, NYC police were allowed to stop people in public if they had a reasonable suspicion the person might soon commit a crime.

    • Ex: Stop someone wearing a trench coat during July heat.
    • Allowed police to be more proactive, rather than reactive, to crime.

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How do police choose who to stop?

Problem: “The low burden of proof, the large discretion granted to police and the relatively invisible nature of these sorts of encounters combine to create real potential for abuse.”

-Criminology professors Henry Fradella and Michael White*

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Problem: “The low burden of proof, the large discretion granted to police and the relatively invisible nature of these sorts of encounters combine to create real potential for abuse.”

-Criminology professors Henry Fradella and Michael White*

Of the millions of stops, only about 12% of all stops resulted in an arrest or a summons.*

How do police choose who to stop?

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Are police biased in who they choose to stop?

How do police choose who to stop?

From “Stop and Frisk” protest

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Population of NYC in 2011

Race-Ethnicity

Black

Hispanic

White

Population

2,054,101

2,373,304

2,731,173

Source: 2011 American Community Survey (data.census.gov)

Proportion of stops in 2011 NYC sample

Race-Ethnicity

Black

Hispanic

White

Proportion of Stops

55.1%

35.2%

9.7%

Note: Proportions calculated just among these three groups (the predominant groups in the dataset)

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Population of NYC in 2011

Race-Ethnicity

Black

Hispanic

White

Population

2,054,101

2,373,304

2,731,173

Source: 2011 American Community Survey (data.census.gov)

Proportion of stops in 2011 NYC sample

Race-Ethnicity

Black

Hispanic

White

Proportion of Stops

55.1%

35.2%

9.7%

Note: Proportions calculated just among these three groups (the predominant groups in the dataset)

Discussion Question: If stops were done completely at random, which groups would be stopped proportionally more often? Less often? What conclusions can you draw from this?

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Race-Ethnicity

Black

Hispanic

White

Population

2,054,101

2,373,304

2,731,173

Proportion of Stops

If stops were done completely at random…

Note: Proportions calculated just among these three groups (the predominant groups in the dataset)

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Race-Ethnicity

Black

Hispanic

White

Population

2,054,101

2,373,304

2,731,173

Proportion of Stops

2,054,101

7,158,578 =28.6%

2,373,304

7,158,578 =33.2%

2,731,173

7,158,578 =38.2%

If stops were done completely at random…

Note: Proportions calculated just among these three groups (the predominant groups in the dataset)

Race-Ethnicity

Black

Hispanic

White

Proportion of Stops

55.1%

35.2%

9.7%

Actual stops:

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Race-Ethnicity

Black

Hispanic

White

Population

2,054,101

2,373,304

2,731,173

Proportion of Stops

2,054,101

7,158,578 =28.6%

2,373,304

7,158,578 =33.2%

2,731,173

7,158,578 =38.2%

If stops were done completely at random…

Note: Proportions calculated just among these three groups (the predominant groups in the dataset)

Race-Ethnicity

Black

Hispanic

White

Proportion of Stops

55.1%

35.2%

9.7%

Actual stops:

Discussion Question: What conclusions can you draw from these differences?

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Lesson 8.8

Practice

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