PRISONS AND JAILS
THEORY OF THE
CORRECTIONAL FACILITIES
Former Chief Justice
Warren Burger
To put people behind walls
and bars and do little or
nothing with them is to win a
battle but to lose a war. It is
wrong, it is expensive, it is
stupid.
EARLY PUNIS
Ch 12 and 13 Practice Test #3
1. Psychologists using the concept of motivation have suggested that
A. biological mechanisms are unrelated to motivation.
B. Actions may be internally or externally motivated.
C. People are always responsible for their actio
STYLES OF POLICING
WATCHMAN
STYLE
LEGALISTIC
STYLE
SERVICE
STYLE
EVOLVING
STYLE
INFORMAL
POLICE
INTERVENTION
INTO THE
LIVES OF
RESIDENTS IN
LOWER CLASS
COMMUNITY
USING
PERSUASTION
OR THREATS
ENFORCING
THE PRECISE
LETTER OF
THE LAW.
TAKE A
HANDS OFF
APPROA
PRISONS AND
JAILS
WHAT TO DO WITH THOSE WHO
BREAK THE LAW?
CAPITAL PUNISHMENT
EXECUTIONS IN 2009/2011
TEXAS
ALABAMA
OHIO
VIRGINIA
GEORGIA
OKLAHOMA
FLORIDA
SOUTH CAROLINA
TENNESSEE
24
6
5
3
3
3
2
2
2
13
6
5
1
4
2
2
1
0
NUMBERS OF INMATES UNDER
SENTENCE OF
A.P. Statistics: Chapter3 Review 2 Name k 1 )
SHOW ALL WORK FOR FULL CREDITIE
l.) Johannes Kepler spent years trying to discover a reiationship between the time (in days) for a planet to
revolve around the sun and the distance (in millions of kilometers)
1. To determine whether extra personnel are needed for the day, the owners of a water adventure park would like to
find a model that would allow them to predict the days attendance each morning before opening based on the day of
the week and weather condi
Variable Selection
STT226W
so far we have assumed variables chosen in advance
set of varibles to include are not usually predetermined
no unique set of best variables
set of variables that is best for one purpose may not be best for another
suppose we hav
Transformation for Nonlinear Relation Only
If the regression relation between X and Y is nonlinear but the distribution of the error terms is
reasonably close to a normal distribution with equal variance, then transformations on X should be
attempted. The
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POLYNOMIAL REGRESSION MODELS
frequently used for curvilinear response model
model may fit the data well but take unexpected directions outside the range of the data
ONE PREDICTOR VARIABLE SECOND ORDER MODEL (x2 term)
E ( y) 0 1x 2 x 2
0 is the mea
Transformation for Nonnormality and Unequal Error Variances
Unequal error variances and nonnormality of the error terms frequently occur together. In this case, we
need a transformation on Y, since the shapes and spreads of the distributions of Y need to
QUALITATIVE PREDICTORS
Qualitative, as well as quantitative, predictor variables can be used in regression models. For example,
gender (male,female), purchase status (purchase, no purchase), and class year in school (freshman,
sophomore, junior, senior).
Exercise 4.88 on page 246
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A naval base is considering modifying or adding to its fleet of 48 standard aircraft. The final decision regarding the type and number of aircraft to be added
depends on a comparison of cost versus effectiveness of the mo
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MULTICOLLINEARITY
When two or more X ' s in the model are moderately or highly correlated
HOW TO DETECT
significant correlations between pairs of X ' s
non-significant t-tests for 's with significant global F test
opposite signs than expected for
Correlation coefficient
Analysis of Variance
Coefficient of Determination
1
Correlation Coefficient
r=
S xy
S xx S yy
=
( x - x )( y - y )
(
(
x - x ) y - y )
2
2
Measure of the strength of the LINEAR association between x and y
2
Correlation coefficien
Inference for slope
Confidence interval
Hypothesis testing
Inference for intercept
Confidence interval
Hypothesis testing
Sampling Distribution of b 0
?
b 0 ~ N b 0 ,s ( b 0 )
(
)
x2
1
x2
2 1
) = s2 +
s (b0
= s +
2
( x - x)
n
n
S xx
the differen
Recap of last time
Example
Some properties of LS line
LS estimators are unbiased
Model Assumptions
Estimating s2
Properties & Interpretation of s2
Sampling distribution of slope
Sampling distribution of intercept
Recap of Last Time
Example
Find the least
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Homework 9
DUE: Friday, April 18
READ: Indicator Variables and Interaction Models in the LECTURES folder on Blackboard
1. A study was published of mens and womens winning times in the Boston Marathon. The
independent variables used to model winnin
Interaction Model
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Predict amount of oil (in gallons) used to heat a home from degrees below freezing
(F) and amount of insulation (inches). So Deg = 0 means it is 32F outside, Deg = 10
means it is 22F outside and Deg = -10 means it is 42F outside.
Getting data into R
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An important first step is learning how to get data into R. The most direct way is to simply type data into the
Console window. Type
>a=4
and notice that a has been added to the Workspace window.
Now type
>x=c(2,3,4)
and notice
(a). The plot shows a strong positive linear relationship between hours of staff time and amount of
billings.
(b).
(c). I observe 6 runs.
(d). n1 = 11, n2 = 9; expected runs =
2n1n2
2(11)(9)
1
1 10.9 ; sd of runs = 2.15345
n1 n2
(11 9)
(e). Yes, there i
1.
(a).
(b). The relationship between X and Y is curvilinear
(c).
(Intercept)
-1051.108
X
66.186
I(X^2)
-1.006
(d). The variance inflation factors are greater than 10 which means that there is a multicollinearity
problem.
vif(model1)
X I(X^2)
1453
1453
(e
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RESIDUAL CORRELATION
correlated eror terms suggest there is additional information in the data that has not been exploited in
the current model
EFFECT OF RESIDUAL CORRELATION
's are still unbiased but dont have minimum variance
2
estimates of and
Homework 6
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1. (a). Fit the model using the method of least squares. Is there evidence that the model is useful for
predicting y? Test using = 0.05.
> attach(GASKETS)
> model=lm(numdef~speed)
> summary(model)
(Intercept)
speed
Estimate Std. Error t
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LIMITATION OF DURBIN WATSON TEST
A nonsignificant Durbin Watson test just means no first order correlation
EXAMPLE #3 Ski Sales and Personal Disposable Income
d = 1.968, pvalue = 0.734, do not reject H 0 : 0
observed # of runs = 21
expected # of r