Transcript lecture2-jobs&crime

Jobs and Crime
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A theme for this course

US and CA criminal justice systems will be
case studies, but are there larger issues about
the public sector?
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Public Sector
Health
Safety
Civics
Education
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What determines the quality of life in a
nation, a state or a locality?

The distribution of GDP between the public
and private sectors?
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Total Tax Burden As % of GDP, 2004
Google Forbes overall tax burden
Country
Sweden
France
UK
Germany
Canada
Switzerland
USA
Mexico
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Total Tax burden
50.7%
43.7
36.1
34.8
33.0
29.4
25.5
18.5
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Public Vs. Private Goods
Labor for
Private Goods
Production Function
Contraint
Private
Goods
Labor for
Public Goods
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Labor, Private
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Output, Private
Production Possibility Frontier
L, Private
Output, Public
L, public
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Output, Private
Production Possibility Frontier
L, Private
Output, Public
L, public
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Private
Mexico
US Canada
UK
Sweden
Public
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Production Possibility Frontier
PRIVATE
Inefficient
Does the global economy
Cause a bias towards
Private instead of public
Goods and services?
PUBLIC
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Production Possibility Frontier
Public Goods:
Defense
Inefficient
Does being the world’s
Policeman cause a bias
Away from other public
Goods and services?
Public Goods: Health
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Expenditures Per Pupil
Fiscal
Year
70-71 80-81 90-91
00-01 03-04
05-06
CA
Rank
14
19
28
25
28
35
Nominal 902
$, CA
2438
4595
6986
7673
8607
US
2307
4902
7373
8310
9576
842
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Production Possibility Frontier
Public Goods:
Prison
Operation
Inefficient
Which would you rather
do (1) keep the 30% of
state prisoners who are
pot-heads locked up, or
(2) educate your kids?
Public Goods: education
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US Politics
“It’s the economy stupid!”
 Issues in 2008, 2009, & 2010

 Human
capital and education
 The family and social conservatives
 Huck
& Chuck
 Mitt
I will argue that the issues of family and education are connected
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31.0/33.8~8.6 decline
7.3%
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31.0%
17
5.8%
7.3/5.8 ~ 26% rise
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33.8%
18
The Economy and Crime
Is crime affected by the business cycle?
 Do economic factors cause crime?

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Where is the economy headed?
Survey of Professional Forecasters
http://www.phil.frb.org/files/spf/survq407.h
tml
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Governor’s Budget
Summary 2008-09
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Jan 1990
Jan 2007
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California Forecasts & Record:
Umemployment rate: CA Dept. of Finance
Year
2004
2005
2006
2007
2008
2009
2010
CA
6.2%
5.4%
4.9%
5.3%
5.7%
5.6%
5.5%
US
5.5%
5.1%
4.6%
4.6%
5.0%
5.0%
4.8%
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Outline

Seriousness Survey
 What

can we learn from the survey?
Crime File
 Victims
 Jobs

and Crime
Jobs and Crime
 Why
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do some people get involved with crime?
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Class Survey 2009 Vs. Sample 2008
Scoring Ten Behaviors
 88 responses in 2010, 103 responses in ’09,
97 responses in ‘08

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SERIOUSNESS SURVEY
RATE THE SERIOUSNESS OF EACH OF THE FOLLOWING
BEHAVIORS ON A SCALE FROM ZERO( LEAST SERIOUS)
TO TEN( MOST SERIOUS):
MEDIAN ‘09 ‘10
1. HOMICIDE
_10 10__
2. MASS POISONING ( e.g. TYLENOL) _ 10 9__
3. FORCIBLE RAPE
_ 10
10__
4. ARSON: SET FIRE TO A GARAGE
_ 7 7__
5. SELLING HEROIN
_ 7
7__
6. AUTO THEFT
_6
6__
7. EMBEZZLEMENT OF $1,000
_ 6
5__
8. PROSTITUTE IN A HOUSE OF PROSTITUTION _ 4
3.5_
9. POSSESSION OF MARIJUANA
_ 1 2__
10. SNIFFING GLUE
_ 1 1__
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Conclusions
Consistency from year to year
 Triage is possible: we can separate the more
serious behaviors from the less serious
behaviors

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Distribution of Homicide Scores 2010
Histogram of Homicide Scores
70
Mode = 10
Median = 10
Mean = 9.6
60
Frequency
65
50
40
30
15
20
10
0
0
0
0
0
1
1
2
3
4
5
6
2
7
5
0
0
8
9
10
More
Bin
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Distribution of Homicide Scores 2009
Histogram Distribution of Homicide Scores, Econ 160 W 2009
100
90
80
60
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
Median: 52nd Person
40
20
One 1
One 6
Series: HOMICIDE
Sample 1 103
Observations 103
Six 8’s
Jarque-Bera
Probability
9.650485
10.00000
10.00000
1.000000
1.117672
-5.249860
37.30991
5525.152
0.000000
0
1.25
2.50
3.75
5.00
6.25
7.50
One 7
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8.75 10.00
Four 9’s
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Histogram of Homicide Sores, '08
Frequency
100
84
80
60
40
20
0
0
1
0
1
1
0
0
3
0
1
2
3
4
5
6
7
8
7
9
0
10
Seriousness Score
Mode = 10, most likely number
Median = 10, score of 49th or middle person
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Average scores 2001 and 2002
12.0
10.0
Score 2002
8.0
6.0
4.0
2.0
0.0
0
1
2
3
4
5
6
7
8
9
10
Score 2001
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Conclusions
Consistency from year to year
 Triage is possible: we can separate the more
serious behaviors from the less serious
behaviors
 For serious behaviors, a clear majority view

 For
example, for homicide 80 out of 88 score it
either 9 and 10, while 85 out of 88 score it
between 8 and 10
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Central Limit theorem in Action
Homicide Mean with 95% Confidence interval
10.4
10.2
10
9.8
Score
9.6
9.4
9.2
lower
mean
upper
9
8.8
8.6
8.4
0
6
12
103
50
20
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25
40
60
80
100
120
Number of Students
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f ( z)  [1 / 2 ] * e
1/ 2[( z 0) /1]2
Density Function for the Standardized Normal Variate
0.45
0.4
0.35
Density
0.3
0.25
0.2
0.15
0.1
2.5%
2.5%
0.05
mean
0
-5
-4
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-3
-2
-1
0
1
Standard Deviations
2
3
4
5
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Histogram of the distribution of Rape Scores, Econ 160 W 2009
60
Series: RAPE
Sample 1 103
Observations 103
59
50
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
40
25
30
20
10
Jarque-Bera
Probability
9.242718
10.00000
10.00000
4.000000
1.150158
-1.960168
7.483749
152.2384
0.000000
0
4
5
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6
7
8
9
10
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Frequency
Histogram: Forcible Rape Scores, '08
70
60
50
40
30
20
10
0
61
20
0
0
0
0
0
0
1
0
1
2
3
4
5
6
5
7
10
8
9
10
Seriousness Scores
Mode: 10
Median: 10
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Three Views about Pot: 2010
Histogram of Pot Scores 2010
30
25
Frequency
25
20
18
20
15
10
6
5
7
5
4
0
0
1
1
1
8
9
10
0
Bin
0
1
2
3
4
5
6
7
Pot Scores
63 score 0–2
17 score 3-5
8 score 7-10
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The Vocal Minority: sixteen score Pot high
Histogram of Distribution of Possession of Pot Scores, Econ 160 W 2009
30
Series: POT
Sample 1 103
Observations 103
25
20
15
4
3
5
3
1
10
5
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
1.980583
1.000000
8.000000
0.000000
1.965290
1.327678
4.383029
Jarque-Bera
Probability
38.46917
0.000000
0
0
1
2
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3
4
5
6
7
8
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Histogram: Possession of Pot, Scores
Frequency
25
21
23
20
14 15
15
10
7
6
7
5
2
1
0
1
7
8
9
10
0
0
1
2
3
4
5
6
Seriousness Scores
Mode: 1
Median: 2
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Center of the Scores Distribution
Mode: most likely
 Median: middle person
 Average: sum of scores divided by total
number of people

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John Tukey: Box Plot for Sniffing
Glue Econ 160 W 2009
73 folks score as 2 0r below
Fight for 14 3’s
Smallest = 0
Q1 = 0
Median = 1
Q3 = 3
Largest = 10
IQR =
3
Median
Outliers: 10, 10, 10, 9,
8, 8, 8,
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16 folks score as 4 or above
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Conclusions
Consistency from year to year
 Triage is possible: we can separate the more
serious behaviors from the less serious
behaviors
 For serious behaviors, a clear majority view

 For
example, for homicide 102 out of 103 score
it between 6 and 10, while 100 out of 103 score
it between 8 and 10
The less serious behaviors are more controversial!
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Dispersion of Scores Distribution

Measures of dispersion
 Standard
deviation
 Inter-quartile range
 Range: Maximum - Minimum
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SERIOUSNESS SURVEY
RATE THE SERIOUSNESS OF EACH OF THE FOLLOWING
BEHAVIORS ON A SCALE FROM ZERO( LEAST SERIOUS)
TO TEN( MOST SERIOUS):
Minimum, Maximum
1. HOMICIDE
_2, 10
2. MASS POISONING ( e.g. TYLENOL)
_0, 10
3. FORCIBLE RAPE
_6, 10
4. ARSON: SET FIRE TO A GARAGE
_2, 10
5. SELLING HEROIN
_0, 10
6. AUTO THEFT
_3, 10
7. EMBEZZLEMENT OF $1,000
_0, 9
8. PROSTITUTE IN A HOUSE OF PROSTITUTION _0, 10
9. POSSESSION OF MARIJUANA
_0, 10
10. SNIFFING GLUE
_0, 8
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The more serious the behavior, the less
disagreement about policy
Dispersion (Disagreement) Versus Seriousness, 2008
3.00
Standard Deviation
2.50
Prostitute
Possess Pot
2.00
Sniffing Glue
Arson
1.50
y = -0.095x + 2.4217
Forcible Rape
R2 = 0.3905
1.00
Homicide
0.50
0.00
0
2
4
6
8
10
12
Seriousness Score
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Policy is more difficult
Policy is easier
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Bureau of
Justice
Statistics,
Report to the
Nation
The Alternative
p.170
One more
step:
converting
seriousness
scores to a
metric (years
of sentence or
Loss rate of $)
The
Economics of
Crime
Control, Ch. 4
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Mapping Seriousness Scores Into Dollars, 2008
$10,000,000.00
Homicide
$1,000,000.00
Loss Rate
$100,000.00
$10,000.00
Embezzlement of $ 1000
$1,000.00
$100.00
$10.00
$1.00
0
$0.10
2
4
6
8
10
12
Sniffing Glue
Seriousness Scores
Source: $ 1.54 Million (1990), Orley Ashenfelter, Princeton,
Based on highway safety
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Types of Crime

Motivation: self-interest, greed
 Street
Crimes: robbery, burglary, auto theft,
larceny
 White Collar: embezzlement, tax evasion,
check fraud, telephone fraud
 Status Offenses: runaway, truant, vagrant,
beyond control of parents
 Black Market: gambling, prostitution,drugs
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Types of Crime

Motivation: Hate, Rage
 Street
Crimes: homicide, aggravated assault,
rape
 Crimes Against Public Order: vandalism,
terrorism
 Hate Crimes
 Columbine
High
 James Byrd: dragging death in Texas
 Jewish Community Center in Granada Hills
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Jobs and Crime
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Questions About Crime
Does the Business Cycle Affect Crime
Rates?
 Does an Individual’s Life Cycle Affect
Crime Rates?
 Why do some people live socially
unproductive lives?

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Two Points About Economic
Conditions and Crime

Relationship of Crime to the Business Cycle
 Short
Run: Business Cycle
 Is Phil Cook wrong?
 California: the misery index and crime
 misery

index = unemployment rate + inflation rate
Relationship of Crime to the Life Cycle
 Long
Run
 Investment in Education
 Role of the Family
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California Unemployment Rate and Inflation Rate, 1952-2004
25.00
unemployment rate
20.00
inflation rate
misery rate
Per Cent
15.00
10.00
5.00
0.00
1940
1950
1960
1970
1980
1990
2000
2010
-5.00
Year
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CA Crime Index Per 1000 and Misery Index (Percent), 1952-2004
45.00
40.00
35.00
Misery index
CA Crime Index
Rate
30.00
25.00
20.00
15.00
10.00
5.00
0.00
1940
1950
1960
1970
1980
1990
2000
2010
Year
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CA Crime Index(t) = a +b*Misery Index(t)
CA Crime Index Per Capita Versus Misery Index
0.05
0.04
0.03
0.015
0.02
0.010
0.01
0.005
0.00
0.000
-0.005
-0.010
-0.015
55
60
65
70
Residual
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80
85
Actual
90
95
00
Fitted
56
CA Crime Index Per 1000 Vs. Misery Index
45
1980
40
Crime Index
35
30
25
20
2002
15
10
1954
1952
5
0
0.00
5.00
10.00
15.00
20.00
25.00
Misery Index
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California: Crime Index Versus Misery Index .
40
35
30
Crime Index
25
20
y = -0.1702x
2
+ 6.0493x - 16.491
R2 = 0.7761
15
10
Observed Data
Quadratic Fit
5
0
0.00
5.00
10.00
Misery Index
15.00
20.00
25.00
Date
Jul-99
Jan-99
Jul-98
Jan-98
Jul-97
Jan-97
Jul-96
Jan-96
Jul-95
Jan-95
Jul-94
Jan-94
Jul-93
Jan-93
Jul-92
Jan-92
2
Jul-91
Jan-91
Jul-90
Jan-90
Jul-89
Jan-89
Rate
US Unemployment Rates, Males, Seasonally Adjusted .
14
12
10
8
6
4
White, 20 plus
Black, 20 plus
0
Date
Aug-99
Feb-99
Aug-98
Feb-98
Aug-97
Feb-97
Aug-96
Feb-96
Aug-95
Feb-95
Aug-94
Feb-94
Aug-93
Feb-93
Aug-92
5
Feb-92
10
Aug-91
Feb-91
Aug-90
Feb-90
Aug-89
Feb-89
Rate
Unemployment Rates, Seasonally Adjusted, Males 16-19 .
50
45
40
35
30
25
20
15
White Male 16-19
Black Male 16-19
0
Why do people work in labor market?
Tastes?
 Assume everybody has the same tastes!
 Human capital: earning power

 Education
 Work
experience
 Health
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An Individual’s Life Cycle for a
Socially Productive Life
Learning over the life cycle
 Accumulating earning power or human
capital
 Earnings depend upon

 ability
 knowledge
 work
experience
 health
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Productive Life Cycle
Social Institution
Family - PreSchool - School - College - Job - Retirement
Function
Learning: Accumulating Human Capital - Earning - Spending
Age Line
0
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4
6
18
23
65
63
Accumulating Human Capital
Inflow
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Stock
Outflow
64
Accumulating Human Capital
Inflow +
Net Inflow
Stock
Outflow
-
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Accumulating Human Capital
Learning +
-
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Investment
Human
Capital
Depreciation
66
Allocation of Your Time
Build Capital
by Learning
Human Capital
Use Capital
for Earning
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24 hours
Time Endowment
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0 hours
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24 hours
Leisure
(learning)
69
Allocation of Your Time
Build Capital
by Learning
Human Capital
Use Capital
for Earning
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Earnings
$480
Opportunities for trading leisure
for earnings (income) at a rate,
$20 per hour, determined by your
stock of human capital
$0
0 hours
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24 hours
Leisure
(learning)
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Salaries by Education Level, CA
Full Time* Workers
Education
No HS Dipl.
HS Dipl.
Bachelor’s
Master’s
Doctorate
Professional
Salary
$26,115
$27,326
$44,426
$52,787
$59,348
$77,877
Wage
$13.06
$13.69
$26.39
$26.97
$29.67
$38.94
*Full Time: >35 hrs/wk, >48 wks/yr.; Source: LA Times, 1-10-93
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Earnings
$480
college grad
$240
dropout
$0
0 hours
24 hours
Leisure
(learning)
Economists Assume You Can
make Comparisons

For example: you can compare a high level
of your income and a low level of your
leisure with a low level of your income and
a high level of your leisure
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Earnings
$480
low value
high
Iso-Preference Curves:
You value all points on
a curve equally
high value
$0
0 hours
24 hours
Leisure
(learning)
Earnings low value
$480
$180
for 9 hrs
of work
high
Optimum
high value
$0
0 hours
15 hours
of leisure
24 hours
Leisure
(learning)
Earnings low value
$480
high
slope of the iso-preference
curve through the 24 hour
endowment is the lowest
wage at which you are
willing to work
$0
0 hours
24 hours
Leisure
(learning)
Earnings low value
$480
high
slope of the iso-preference
curve through the 24 hour
endowment is the lowest
wage at which you are
willing to work
$96
$0
0 hours
24 hours
dropout is unwilling to work for $4/hr
Leisure
(learning)
Participation in the Labor Force:
Willing to look for work

If your market wage exceeds your
reservation wage
 college
grad, @$20/hr, participates
 the junior high dropout, @ $4/hr, does not
We assumed the college grad and the
dropout both have the same values for
income and leisure
 Only their learning histories differ

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Earnings low value
$480
high
slope of the iso-preference
curve through the 24 hour
endowment is the lowest
wage at which you are
willing to work
$96
$0
0 hours
24 hours
dropout is unwilling to work for $4/hr
Leisure
(learning)
Hazards to Personal Success
Dropping out
 Joining gangs
 Anti-social behavior

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Productive Life Cycle
Social Institution
Family - PreSchool - School - College - Job - Retirement
Function
Learning: Accumulating Human Capital - Earning - Spending
Age Line
0
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4
6
18
23
65
83
Legal Work or Illegal Work?
Choice with Uncertain Outcomes
Legal work
Choice
Illegal work
Legal Work or Illegal Work?
Choice with Uncertain Outcomes
Unemployed (fail)
Legal work
Employed (succeed)
Choice
Apprehended (fail)
Illegal work
Not Apprehended
(succeed)
Legal Work or Illegal Work?
Choice with Uncertain Outcomes
0.1
Unemployed (fail)
$0
Legal work
0.9
Choice
Employed (succeed)
$12,000/yr
0.2
Apprehended (fail)
$0
0.8
Not Apprehended
(succeed) $14,000
Illegal work
Legal Work or Illegal Work?
Choice with Uncertain Outcomes
0.1
Unemployed (fail)
$0
Legal work
0.9
Choice
Employed (succeed)
$12,000/yr
Expected legal Income = 0.9*$12,000 = $10,800
0.2
Illegal work
0.8
Apprehended (fail)
$0
Not Apprehended
(succeed) $14,000/yr
Expected illegal income = 0.8*$14,000 = $11,200
Legal Work or Illegal Work?
Choice with Uncertain Outcomes
0.05
0.1
Unemployed (fail)
$0
Legal work
0.95 0.9
Choice
Employed (succeed)
$12,000/yr
Expected legal Income = 0.95*$12,000 = $11,400
0.2
Illegal work
0.8
Apprehended (fail)
$0
Not Apprehended
(succeed) $14,000/yr
Expected illegal income = 0.8*$14,000 = $11,200
Social Measures to Reduce
Crime

Maintain a full-employment economy
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Legal Work or Illegal Work?
Choice with Uncertain Outcomes
0.1
Unemployed (fail)
$0
Legal work
0.9
Choice
Employed (succeed)
$12,000/yr
Expected legal Income = 0.9*$12,000 = $10,800
0.3
0.2
Illegal work
0.7 0.8
Apprehended (fail)
$0
Not Apprehended
(succeed) $14,000/yr
Expected illegal income = 0.7*$14,000 = $9,800
Social Measures to Reduce
Crime

Maintain an Effective Criminal Justice
System
 keep
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the probability of apprehension high
91
Legal Work or Illegal Work?
Choice with Uncertain Outcomes
0.1
Unemployed (fail)
$0
Legal work
0.9
Choice
Employed (succeed)
$12,000/yr
Expected legal Income = 0.9*$12,000 = $10,800
0.2
Illegal work
0.8
Apprehended (fail)
-$3,000 (fine) $0
Not Apprehended
(succeed) $14,000/yr
Expected illegal income = 0.8*$14,000 - 0.2*$3,000 = $10,600
Social Measures to Reduce
Crime

Punish the criminal
 make
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crime less attractive
93
Social Measures to Reduce
Crime
Maintain a full-employment economy
 Maintain an Effective Criminal Justice
System

 keep

the probability of apprehension high
Punish the criminal
 make
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crime less attractive
94
Summary
Your economic status affects your probable
behavior: work or crime
 Earning power affects your probable
behavior
 When you are are a young teen you need a
parent or role model to motivate you to stay
in school and keep learning

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95
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96
2003
Number of Responses Versus Score for Homicide
100
90
90
80
Number
70
60
50
40
30
20
15
10
1
3
0
1
0
0
0
0
1
2
1
2
3
4
5
6
7
8
0
9
10
Score
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97
Class Survey 2003
Scoring Ten Behaviors
 113 Responses
 No two are the same
 Two most similar responses
 Two most different responses

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98
Similar Scorings
Homicide
Poisoning
Rape
Arson
Sell Heroin
Auto Theft
Embezzle
Prostitute
Possess Pot
Sniff Glue
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10
10
10
7
7
4
4
5
3
0
10
10
10
8
5
7
4
2
1
0
99
Different Scorings
Homicide
Poisoning
Rape
Arson
Sell Heroin
Auto Theft
Embezzle
Prostitute
Possess Pot
Sniff Glue
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10
10
10
10
8
9
7
7
5
8
1
5
2
4
3
6
7
8
9
10
100
2003
Number of Responses Versus Score for Homicide
100
90
90
80
Number
70
60
50
40
30
20
15
10
1
3
0
1
0
0
0
0
1
2
1
2
3
4
5
6
7
8
0
9
10
Score
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101
Dispersion Versus Median Score, 2003
2.5
Dispersion
2
1.5
1
0.5
0
0
2
4
6
8
10
12
Median Score
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102
Mean Rating
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103
SERIOUSNESS SURVEY
RATE THE SERIOUSNESS OF EACH OF THE FOLLOWING
BEHAVIORS ON A SCALE FROM ZERO( LEAST SERIOUS)
TO TEN( MOST SERIOUS):
MEDIAN ‘03 ‘05
1. HOMICIDE
_10 10__
2. MASS POISONING ( e.g. TYLENOL)
_ 9 8__
3. FORCIBLE RAPE
_ 9 9__
4. ARSON: SET FIRE TO A GARAGE
_ 7 7__
5. SELLING HEROIN
_ 6 6__
6. AUTO THEFT
_ 5.5 6__
7. EMBEZZLEMENT OF $1,000
_ 4 4__
8. PROSTITUTE IN A HOUSE OF PROSTITUTION _ 3 3__
9. POSSESSION OF MARIJUANA
_ 2 2__
10. SNIFFING GLUE
_ 1 1__
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104
Misery Index, California 1952-2003
25.00
unemployment rate
inflation rate
misery index
20.00
Rate
15.00
10.00
5.00
0.00
1950
1960
1970
1980
1990
2000
2010
-5.00
year
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105
California Misery Index and Crime Index, 1952-2002
45.00
CA Misery Index
CA Crime Index Per 1000
40.00
35.00
Rate
30.00
25.00
20.00
15.00
10.00
5.00
0.00
1950
1960
1970
1980
1990
2000
2010
Year
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106
California: Crime Index Versus Misery Index .
40
1980
1992
35
1975
30
1970
Crime Index
25
1998
20
15
10
1952
5
0
0.00
5.00
10.00
Misery Index
15.00
20.00
25.00
How best to
Learn in a
Lecture class
That does not
Have a
Section?
We
Recommend
Going to class.
The questions
On the exams
Are from topics
Discussed in
Class.
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How much
math does 160
require?
1.Descriptive
Graphs
2. Analytical
Graphs (exams)
3. Notation e.g
OF=f(CR,SE,SV
108
Frequency
Homicide, W 06, 61 Respondents
60
50
40
30
20
10
0
53
0
0
0
0
1
1
2
3
4
5
0
0
0
6
7
8
7
9
10
Seriousness
Mode = 10, largest number of responses
Median = 10, score of 31st person
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109
Homicide, W 05, 98 Respondents
74
Frequency
80
60
40
16
20
1
2
0
1
0
0
1
3
1
2
3
4
5
6
7
8
0
9
10
Seriousness
Mode = 10, largest number of responses
Median = 10, score of 49th person
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110
Number of Responses Versus Score for Homicide 2004
73
80
70
60
Responses
50
40
30
14
20
1
10
1
3
0
0
1
2
3
4
5
6
7
8
9
10
Score
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111
Rape, W 05, 98 Respondents
Frequency
50
39
40
27
30
19
20
10
0
0
1
0
1
1
2
3
4
5
4
7
0
6
7
8
9
10
Seriousness
Mode = 9
Median = 9
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112
Possession of Marijuana, W 06, 61
Respondents
Frequency
40
33
30
20
9
10
6
2
5
2
2
1
0
1
6
7
8
9
10
0
1
2
3
4
5
Seriousness
Mode = 1
Median = 1
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113
Number of Responses Vs. Possession of Pot Score ‘02
35
31
30
27
Frequency
25
23
20
15
10
10
7
5
4
4
5
2
0
0
1
2
3
4
Score
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5
6
7
8
0
0
9
10
114
Disagreement Versus Seriousness, 02
Dispersion (Standard Deviation)
3
2.5
Sniff Glue
Prostitute
Selling Heroin
Possess Pot
2
Embezzle
Arson
1.5
Mass Poisoning
Auto Theft
Rape
1
Homicide
Homicide
2004
0.5
0
0
2
4
6
8
10
12
Score
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115
Embezzlement
Standard Deviation or Dispersion
John Tukey: Box Plot for Pot ‘09
Smallest = 0
Q1 = 1
Median = 1
Q3 = 3
Largest = 8
IQR =
2
Outliers: 8, 8,
8, 7,
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118