Curriculum

  • This page from the Bureau of Labor Statistics provides data and statistics on Inflation & Consumer Spending, Wages, Earnings, & Benefits, Productivity, Safety & Health, International Labor, Occupations, and Demographics. Data is in Excel, html, or pdf format.
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  • This tutorial introduces the statistical software SPSS for Windows users. Topics covered include: The Basics, Data, Descriptive Statistics, Chi-square & T-tests, Correlations & Regression, Oneway ANOVA, Factorial ANOVA.
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  • This collection of datasets from Harvard University covers many ecological topics from insects to hurricanes. Each dataset's description includes the name of the investigator, dates of collection, location, abstract, and method of collection. The metadata file for each dataset provides descriptions of the variables. Please read the terms of agreement before use.
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  • This pdf document contains 7 pages of random number tables and 1 page of instructions for use.
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  • This online textbook covers the following probability and statistics topics: Independence; Venn Diagrams; Bayes's Theorem; Counting; Binomial Expansion; Binomial Distribution; Continuous Distributions; Infinitesimals in Probability; Averaging; Variance; Gaussian Distribution; Random Walks; Correlation; Causation; Linear Regression; Unbiased Estimators; Hypothesis Testing; Shape of the Distribution; Variance of Mean Differences.
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  • This page explains simple linear regression with an example on muscle strength versus lean body mass.
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  • This resource explains Multiple Regression and concepts associated with it. Key Words: Predicted values; Residuals; Dummy Variables; Interaction Effects; T-Test; Regression Coefficients; Correlation; Partial Correlation; R-Squared; Adjusted R-Squared; Multicollinearity; Variance-Inflation Factors; Transformation; Cook's Distance; Validity; Durbin-Watson Coefficient.
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  • This tutorial provides a basic introduction to many topics in statistics and probability. Topics include: Sets and subsets, Statistical experiments, Counting, Basic probability rules, Bayes' theorem, Probability distributions, Discrete vs. Continuous, Binomial, Negative Binomial, Hypergeometric, Multinomial, Poisson, Normal, Sampling theory, Central tendency, Variability, Sampling distributions, t Distribution, Chi-Square Distribution, F Distribution, Estimation problems, Hypothesis testing, Power, Survey sampling, Simple random samples, Stratified samples, Cluster samples, Sample size.
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  • As discussed, the murder rates for Blacks in the United States are substantially higher than those for Whites, with Latino murder rates falling in the middle. These differences have existed throughout the 20th and into the 21st century and, with few exceptions, are found in different sections of the United States. Although biological and genetic explanations for racial differences in crime rates, including murder, have been discredited and are no longer accepted by most criminologists, both cultural and structural theories are widespread in the literature on crime and violence. It is also important to remember that Latino is an ethnic rather than a racial classification. The point of this exercise is to examine differences in selected structural positions of Blacks, Whites and Latinos in the United States that may help explain long-standing differences in their murder rates.
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  • Everyday we have specific routines we engage in. Many of these routines are tailored to preventing us from becoming victims of crime. We do things like lock our doors, watch where we walk at night, or avoid walking alone. We take these actions because at some level we are afraid of the possibility of being a victim of crime. Although we may not consciously think about it, these routines may be influenced by a variety of factors. What factors might make some individuals more afraid than others?

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