PPT-Quantitative Literacy:

Quantitative Literacy Thinking Between the Lines Crauder Evans Johnson Noell Chapter 4 Personal Finance 2011 W H Freeman and Company 1 Chapter 4 Personal Finance Lesson Plan 2 Saving money The power of compounding. WESTMONT ASSESSMENT . REDESIGN. General Education Committee. Program Review Committee. Integrating the Major Discipline . Reasoning Abstractly . Reading Imaginative Literature . Understanding Society . By Idris Fabio Augustus Crockett-Magee. &. Sam Brill. What is Quantitative Easing?. Quantitative . E. asing (QE) is a policy used by the Bank of England introduced in March 2009. . This is a Monetary policy used when the interest rate can not go any lower (0.5%).. Research in Education. Sohee Kang. Ph.D. , . l. ecturer . Math . and . Statistics . Learning . Centre. Outline. Analyzing Educational Research Data. Collecting data. Using R (R commander) for describing and testing hypotheses. Slide #. 1. Bivariate EDA. Describe the . relationship between pairs of . variables. Four characteristics to describe. Association (Direction). Form. Outliers. Strength. Quantitative Bivariate EDA. Slide #. Teaching . Probability and Decision Theory in . Foundations . of Logical . Reasoning. Quantitative Literacy in Philosophy. [. Quantitative literacy] requires logic, data analysis, and probability….It enables individuals to analyze evidence, to read graphs, to understand logical arguments, to detect logical fallacies, to understand evidence, and to evaluate risks. Quantitative literacy means knowing how to reason and how to think. . Development & Lessons Learned. - Stuart Boersma, Central Washington Univ.. - . Caren. . Diefenderfer. , . Hollins. University. - Shannon . Dingman. , Univ. of Arkansas. - Bernie Madison, Univ. of Arkansas. Slide #. 1. Univariate EDA. Purpose – describe the distribution. Distribution . is concerned with what values a variable takes and how often it takes each value. Four characteristics. Shape. Outliers. Slide #. 1. Univariate EDA. Purpose – describe the distribution. Distribution . is concerned with what values a variable takes and how often it takes each value. Quantitative vs. . Categorical. Do . Imaging Biomarkers Alliance (. QIBA. ®. ) . Edward F. Jackson, PhD – Chair, QIBA. Professor and Chair, Department of Medical Physics. University of Wisconsin School of Medicine & Public Health. Literacy Characteristics. Matrix and Overlapping characteristics and integrated interventions. Guiding Principles. Literacy Hierarchy. Literacy Intervention Analysis. Literacy Strategies.  . Literacy: Guiding Principles . Fibonacci: http://www.youtube.com/watch?v=E9cX_14rf4g. Math Across the Curriculum. Rob Kimball. Or. If we are not going to use it outside of math class, why do we. have to learn it?. Or. We downloaded some data to a spreadsheet, calculated some statistics, and used those statistics to support oral arguments….. Section 118. Özlem. . Elgün. Solving for the rate (percent change). Solving for the initial value (a.k.a. old value, reference value) . Solving for time (using logarithms). Review. from previous class:. LSP 120: Quantitative Reasoning and Technological Literacy Section 118 Özlem Elgün Solving for the rate (percent change) Solving for the initial value (a.k.a. old value, reference value) Solving for time (using logarithms) Reading. . Writing. . Speaking . . Listening. . Pragmatics. . Critical Thinking. Engagement in Literacy Experience. Carnahan & Williamson (. Eds. ), 2010. Engagement in Literacy Experiences.