# Drill and Practice

• ### Correlates of Desistance

Research has shown that marital status and employment are correlates of desistance. That is, adolescents involved with crime were more likely to discontinue offending in adulthood if they were married and had a good job. Most of what criminologists know about the process of desistance from crime is based on a sample of adult males in the 1950's. There is no question that life in America has changed drastically in the past fifty years. Given the importance of examining historical change inherent in the life course perspective, it is important to determine how changes in the social structure over time impact individuals. Therefore, the goals of this data analysis exercise are to examine changes in marriage and employment over the last fifty years. The purposes are to identify the changes that have taken place, and to hypothesize how these changes may affect the process of desistance from crime today.
• ### World Development Chart

This scatterplot lets users plot a number of demographic variables and see the log transformation of those variables for numerous countries and income groups. Users can also see the information for any year from 1975 to 2004.
• ### Data Collection: Data Matters with Excel: Estimating Population Variance

This activity uses Microsoft Excel to estimate the population variance of grouped data two ways: the variance within a group and the variance between groups. This activity accompanies Section 7.3 of Data Matters.
• ### Multiple Comparisons

This exercise includes a discussion on comparing data with very different sample sizes and nonhomogeneity of variance. The data comes from a study on the behavior of pregnant women with regard to cigarette smoking.
• ### Learning Objectives for Introductory Statistics

This text document lists detailed learning objectives for introductory statistics courses. Learning objectives are brief, clear statements of what learners will be able to perform at the end of a course. These objectives were developed for a one semester general education introductory statistics course. The objectives cover the broad categories of Graphics, Summary Statistics, The Normal Distribution, Correlation and Scatterplots, Introduction to Regression, Two way Tables, Data Collection and Surveys, Basic Probability, Sampling Distributions, Confidence Intervals, Tests of Hypothesis, and T-distributions.
• ### Data Collection:US Census Bureau: Census 2000 Datasets

Users can select from detailed tables and geographical comparison tables to generate data from the 2000 Census.
• ### Dataset: Rock Fries Your Brains

This exercise uses descriptive statistics to analyze a data set about how rats respond to rock music vs. classical music.
• ### Star Library: An Unusual Episode

This article describes an activity that illustrates contingency table (two-way table) analysis. Students use contingency tables to analyze the "unusual episode" (the sinking of the ocean liner Titanic)data (from Dawson 1995) and attempt to use their analysis to deduce the origin of the data. The activity is appropriate for use in an introductory college statistics course or in a high school AP statistics course. Key words: contingency table (two-way table), conditional distribution

• ### Statistical Mechanics

This course in Statistical Mechanics features problem sets and exams. Basic principles examined include: the laws of thermodynamics and the concepts of temperature, work, heat, and entropy; postulates of classical statistical mechanics, microcanonical, canonical, and grand canonical distributions; applications to lattice vibrations, ideal gas, photon gas; quantum statistical mechanics; Fermi and Bose systems; and interacting systems: cluster expansions, van der Waal's gas, and mean-field theory.
• ### Probabilistic Systems Analysis and Applied Probability

This course features a full set of lecture notes and problem sets introducing students to the modeling, quantification, and analysis of uncertainty. Topics covered include: formulation and solution in sample space, random variables, transform techniques, simple random processes and their probability distributions, Markov processes, limit theorems, and elements of statistical inference.