1: Chapters
- Page ID
- 52011
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)- 1.1: An Overview of Statistics
- This page introduces the concept of equity-mindfulness in statistics, focusing on applying statistical methods to social justice issues in healthcare. It covers fundamental topics such as data equity, health equity frameworks, and the social determinants of health. It emphasizes understanding disparities in health outcomes across different racial and socioeconomic groups. Basic statistical concepts, data classifications, levels of measurement, and sampling techniques are outlined.
- 1.2: 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.
- 1.3: Probability
- This chapter introduces the concept of probability, emphasizing its significance in daily decision-making and its role in statistics. It covers probability definitions, rules, distributions, and their application to social justice issues. Key topics include the normal curve, z-scores, and blending probability with social issues like racial profiling and wrongful convictions. The chapter underscores the importance of understanding probability to facilitate awareness and drive social change.
- 1.5: Significance of Statistical Inference Methods
- This chapter explores inferential statistics, focusing on concepts such as confidence intervals, hypothesis testing, and errors in statistical inference. It emphasizes the importance of understanding sampling variations and discusses tests like t-tests and chi-square tests. It also touches on the misuse of statistics in scientific racism, emphasizing the need for socially just statistical methods. The chapter links statistical inference to broader societal issues.
- 1.6: Correlation and Regression Analysis
- The page discusses the impact of a U.S. Supreme Court ruling on affirmative action and its implications for diversity in higher education and healthcare. It examines statistical concepts like inferential analysis, emphasizing the distinction between correlation and causation. Correlation measures the linear relationship between variables, while regression predicts dependent variables based on independent ones through equations.
- 1.7: Case Studies
- This page explores the use of case studies to bridge theory and practice in social justice issues through mathematical statistics. It discusses three types of case studies: intrinsic, instrumental, and collective. Three specific cases are examined: the demographic profile of fathers receiving reentry services, the PRASAD Project's holistic model addressing social justice through health, education, and environmental measures, and community health centers in Massachusetts.