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- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Basic_Statistics_Using_R_for_Crime_Analysis_(Choi)/01%3A_Chapters/1.02%3A_Introduction_to_Data_Formations_and_GraphicsThis chapter focuses on transforming survey data from the 2012 General Social Survey (GSS) and visualizing it using the R programming language. The survey targets the American population's attitudes t...This chapter focuses on transforming survey data from the 2012 General Social Survey (GSS) and visualizing it using the R programming language. The survey targets the American population's attitudes towards police use of force. The chapter explains how to import the data using the haven package, transform categorical variables correctly, and employ the dplyr package for data manipulation. Additionally, it introduces the ggplot2 package for creating graphical representations of the data.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Basic_Statistics_Using_R_for_Crime_Analysis_(Choi)/01%3A_Chapters/1.03%3A_Creating_a_New_Variable_and_Producing_Summary_StatisticsThis chapter focuses on creating new variables and producing summary statistics using the 2018 Part 1 crime data from Pennsylvania's Uniform Crime Report. It explains the distinction between Part 1 (s...This chapter focuses on creating new variables and producing summary statistics using the 2018 Part 1 crime data from Pennsylvania's Uniform Crime Report. It explains the distinction between Part 1 (serious) and Part 2 (less serious) crimes and the limitations of the UCR due to underreporting. The chapter guides how to manipulate data in R, including renaming variables, calculating crime rates, and categorizing cities by population.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Basic_Statistics_Using_R_for_Crime_Analysis_(Choi)/01%3A_Chapters/1.04%3A_Central_Tendency_and_VariabilityThe page explains the concepts of central tendency and variability, key statistical measures that summarize and describe datasets. Central tendency includes mean, median, and mode, while variability i...The page explains the concepts of central tendency and variability, key statistical measures that summarize and describe datasets. Central tendency includes mean, median, and mode, while variability includes variance and standard deviation. The page also provides a guide on using R to compute these measures using the Gapminder dataset, showcasing steps to load and manipulate the data, and calculate these statistics.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Basic_Statistics_Using_R_for_Crime_Analysis_(Choi)/01%3A_Chapters/1.07%3A_T-TestThis page introduces the t-test, a statistical tool used to compare the means of two groups, and explains its use in examining differences in continuous data. Two types of t-tests are discussed: indep...This page introduces the t-test, a statistical tool used to compare the means of two groups, and explains its use in examining differences in continuous data. Two types of t-tests are discussed: independent-samples t-test, for comparing distinct groups, and paired-samples t-test, for comparing the same group over time. The context used involves assessing the impact of Cognitive Behavioral Therapy (CBT) programs on inmates' antisocial attitudes.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Basic_Statistics_Using_R_for_Crime_Analysis_(Choi)/01%3A_Chapters/1.01%3A_Introduction_to_Crime_Data_Analysis_R_and_RStudioData analysis in the criminal justice system extends beyond policing, playing a crucial role in investigations, prevention strategies, and broader public safety initiatives. Crime analysts support law...Data analysis in the criminal justice system extends beyond policing, playing a crucial role in investigations, prevention strategies, and broader public safety initiatives. Crime analysts support law enforcement by uncovering trends, aiding investigations, and optimizing resource allocation. They also contribute to correctional settings and court proceedings by identifying security risks and assessing rehabilitation programs' effectiveness.
- https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Statistics_Through_an_Equity_Lens_(Anthony)/01%3A_Chapters/1.02%3A_Descriptive_StatisticsThis chapter focuses on the foundational role of descriptive statistics in data-equity projects, emphasizing the need to collect and understand data to address specific issues. Descriptive statistics ...This chapter focuses on the foundational role of descriptive statistics in data-equity projects, emphasizing the need to collect and understand data to address specific issues. Descriptive statistics involve organizing, describing, and summarizing data using various statistical methods such as measures of central tendency, variability, and distribution shapes. The chapter also highlights the significance of data disaggregation to uncover equity gaps.
