Course Code: statlaw
Duration: 14 hours
Course Outline:

Introductory session

  • The nature of law enforcement statistical research
  • Methods of Statistical Analysis in Law Enforcement
  • Applications and advances of Statistical Analysis and Forecasting
  • Questions and Problems

Organizing the data

  • Data types and measures
  • Graphic presentation
  • Frequency distribution of nominal, ordinal and interval data
  • Proportions and percentages, rates
  • Cumulative distributions
  • Cross-tabulations
  • Exercises

Measure of Central Tendency

  • The Mode
  • The Median
  • The Mean
  • Comparing measures of central tendency
  • Choosing the most appropriate measure to data
  • Exercises

Measures of Variability

  • Measuring spread
  • The Variance and the Standard deviation
  • The Range, Interquartile
  • Comparing measures of variability
  • Choosing the most appropriate measure to data
  • Exercises

Probability and distributions

  • Rules of probability
  • Probability distributions
  • Normal distribution, characteristics
  • Standard z scores
  • t-Student distribution
  • Chi2 distribution
  • Exercises

Inferencing from samples

  • Sampling methods
  • Sampling distribution of means
  • Confidence intervals
  • Estimating proportions
  • Exercises

Decision making – Hypothesis Testing

  • Logic of statistical hypothesis testing
  • Levels of significance
  • Understanding difference between One-tailed and two-tailed tests
  • Testing the single mean and variance
  • Testing differences between means
  • Normality tests, Shapiro-Wilk, Anderson-Darling
  • Exercises

Analysis of Variance

  • The logic of Analysis of Variance
  • Multiple comparision of means
  • Exercises

Nonparametric tests of significance

  • Chi-square tests- one-way, two-way
  • The Median test
  • Exercises

Association analysis - Correlation of quantitative and qualitative data

  • Graphical Analysis - Scatter Plots
  • Strength of relationship
  • Direction of relationship
  • Measures of correlation
  • Pearson’s linear correlation coefficient
  • Spearman’s Rank-Order correlation coefficient
  • Kruskal-Wallis test
  • Correlation coefficient for nominal data in tabular format.
  • Exercises

Association analysis – Regression

  • The regression model
  • Graphical interpretation
  • Interpretation of model parameters
  • Measures of fit
  • Validation
  • Exercises

Multivariate methods

  • Principal Component Analysis
  • Discriminant Analysis

Forecasting

  • Forecasting – data and methods
  • Description of forecasting process
  • Problems in forecasting
  • Quantitative forecasting methods
  • Qualitative forecasting methods
  • Role of Machine learning in forecasting
  • Methods of forecast evaluations

Time Series Forecasting Methods

  • Simple benchmark methods
  • Regression based forecasting
  • Time series decomposition
  • Exponential smoothing

Making predictions about potential crimes – Examples

  • Crime mapping
  • Regression methods
  • Data Mining
  • Spatiotemporal analysis