Basic Concepts of Probability and Statistics in the Law

ISBN-10: 038787500X
ISBN-13: 9780387875002
Edition: 2009
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Description: This text provides a basic introduction to concepts of probability and statistics specifically for lawyers.

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Book details

List price: $33.99
Copyright year: 2009
Publisher: Springer London, Limited
Publication date: 6/11/2009
Binding: Paperback
Pages: 174
Size: 6.00" wide x 9.00" long x 0.50" tall
Weight: 0.638
Language: English

This text provides a basic introduction to concepts of probability and statistics specifically for lawyers.

Probability
Classical and Legal Probability
Bayes's Theorem
Screening Tests
Debate over Bayesian analysis
Descriptive Tools
Measures of Central Location
Mean
Median
Mode
Variants of the Mean
Measures of Dispersion
Variance and Standard Deviation
Variance of Sample Sums and the Sample Mean
Correlation
Measuring the Disparity Between Two Proportions
Compound Events
The Addition Rule
The Product Rule
Significance
The Concept of Significance
Rejecting the Null Hypothesis
The Two-or-Three Standard Error Rule
Statistical and Legal Significance
Factors That Determine Significance
Nonsignificant Data
Random Variables and Their Distributions
Expectation, Variance, and Correlation
The Binomial Distribution
The Hypergeometric Distribution
The Normal Distribution
The Poisson Distribution
Student's t-Distribution
The Geometric and Exponential Distributions
Confidence
Power
Sampling
What is Sampling?
Simple Random Sampling
The Problem of Bias
More Complex Designs
Small Samples
Epidemiology
Cohort Studies
Case-Control Studies
Biases and Confounding
Association vs. Causation
Combining the Evidence
Aggregated and Disaggregated Data
Meta-analysis
Regression Models
Four Models
Pay Discrimination in an Agricultural Extension Service
Nitrogen Oxide Emission Reduction
Daily Driving Limits for Truckers
Bloc Voting
Estimating the Model
Measuring Indeterminacy in Models
Inherent Variability
Sampling Error
Confidence and Prediction Intervals in Relation to the Regression Estimate
Regression Models - Further Considerations
Choice of Explanatory Variables
Proxy Variables
Tainted Variables
Aggregation Issues
Forms of Models
Forms for Variables
Logarithms
Quadratic Terms
Interactive Variables
Measuring Uncertainty in Models
Assumptions of the Model
First Assumption: The Errors Have Zero Mean
Second Assumption: The Errors Are Independent
Third Assumption: The Errors Have Constant Variance
Fourth Assumption: The Errors Are Normally Distributed
Validating the Model
Logistic Regression
Table of Cases
Index

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