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Data in a Flash (DAAC Study)
dynamics lends the OTD database its value as a global change research tool. With a lightning database compiled over time, scientists can map the spatial distribution and temporal (time-based) variability of global lightning and thunderstorm activity. Moreover, in t...
Charles A. Dana Center: Clarifying Activities: Mathematical Models with Applications
approach the problem geometrically using the assumption that the pile of sand approximates a cone. The formula for the volume of the cone whose height and base radius is equal to that of the pile of sand, V = 1/3pr2h, would be a good model for determining the amoun...
Beacon Learning Center: The Gravity of the Situation
and computer files in order to perform tasks and/or for enjoyment. Numeric Problem Solvers 03 Florida students use numeric operations and concepts to describe, analyze, communicate, synthesize numeric data, and to identify and solve problems. Cooperative Workers 08 Florida students work coo...
 Summaries of the Evaluations Referenced in Emerging Answers 2007
identifiers, surveys were matched based on demographic data. Although 1477 students took the 6 month follow-up survey, only 68% were matched. The low retention rate can be attributed to incomplete information on baseline or follow-up questionnaires, absences, drop-outs, migration, and the stu...
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identifiers, surveys were matched based on demographic data. Although 1477 students took the 6 month follow-up survey, only 68% were matched. The low retention rate can be attributed to incomplete information on baseline or follow-up questionnaires, absences, drop-outs, migration, and the students moved to different classes by the 6 month follow-up. *Results approached significance for seriously considering always using a condom (p=.06).
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http://www.thenationalcampaign.org/ea2007/EA2007_program_summaries.pdf#page=66
www.thenationalcampaign.org/ea2007/EA2007_program_summaries.pdf#page=66
identifiers, surveys were matched <span class="highlight">based</span> on demographic data. Although 1477 students took the 6 month follow-up survey, only 68% were matched. The low retention rate can be attributed to incomplete information on baseline or follow-up questionnaires, absences, drop-outs, migration, and the students moved to different classes by the 6 month follow-up. *Results approached significance <span class="highlight">for</span> seriously considering always <span class="highlight">using</span> <span class="highlight">a</span> condom (p=.06).
Charles A. Dana Center: Algebra II Sequence Rationale
While revisiting the data activity from Unit I, emphasis should be placed on: Identifying the limitations of the domain and range for the situation versus the domain and range for the function Parameters for the situation, and =...
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While revisiting the data activity from Unit I, emphasis should be placed on: Identifying the limitations of the domain and range for the situation versus the domain and range for the function Parameters for the situation, and The use of this data collected to create and solve a mathematical model to make inferences and justifications. Unit II: Linear Functions
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http://www.utdanacenter.org/mathtoolkit/downloads/scope/OLDalg2scope/sequence_rationale.pdf#page=15
www.utdanacenter.org/mathtoolkit/downloads/scope/OLDalg2scope/sequence_ra...
 While revisiting the data <span class="highlight">activity</span> from Unit I, emphasis should be placed on:  Identifying the limitations of the <span class="highlight">domain</span> and range <span class="highlight">for</span> the situation versus the <span class="highlight">domain</span> and range <span class="highlight">for</span> the function  Parameters <span class="highlight">for</span> the situation, and  The use of this data collected to create and solve <span class="highlight">a</span> mathematical model to make inferences and justifications. Unit II: Linear Functions
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http://www.utdanacenter.org/mathtoolkit/downloads/scope/OLDalg2scope/sequence_rationale.pdf#page=17
www.utdanacenter.org/mathtoolkit/downloads/scope/OLDalg2scope/sequence_ra...
 While revisiting the data <span class="highlight">activity</span> from Unit I, emphasis should be placed on:  Identifying the limitations of the <span class="highlight">domain</span> and range <span class="highlight">for</span> the situation versus the <span class="highlight">domain</span> and range <span class="highlight">for</span> the function  Parameters <span class="highlight">for</span> the situation, and  The use of this data collected to create and solve <span class="highlight">a</span> mathematical model to make inferences and justifications. Unit III: Quadratic Functions
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http://www.utdanacenter.org/mathtoolkit/downloads/scope/OLDalg2scope/sequence_rationale.pdf#page=19
www.utdanacenter.org/mathtoolkit/downloads/scope/OLDalg2scope/sequence_ra...
 While revisiting the data <span class="highlight">activity</span> from Unit I, emphasis should be placed on:  Identifying the limitations of the <span class="highlight">domain</span> and range <span class="highlight">for</span> the situation versus the <span class="highlight">domain</span> and range <span class="highlight">for</span> the function  Parameters <span class="highlight">for</span> the situation, and  The use of this data collected to create and solve <span class="highlight">a</span> mathematical model to make inferences and justifications. Unit IV: Square Root Functions
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http://www.utdanacenter.org/mathtoolkit/downloads/scope/OLDalg2scope/sequence_rationale.pdf#page=21
www.utdanacenter.org/mathtoolkit/downloads/scope/OLDalg2scope/sequence_ra...
 While revisiting the data <span class="highlight">activity</span> from Unit I, emphasis should be placed on:  Identifying the limitations of the <span class="highlight">domain</span> and range <span class="highlight">for</span> the situation versus the <span class="highlight">domain</span> and range <span class="highlight">for</span> the function  Parameters <span class="highlight">for</span> the situation, and  The use of this data collected to create and solve <span class="highlight">a</span> mathematical model to make inferences and justifications. Unit V: Rational Functions
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http://www.utdanacenter.org/mathtoolkit/downloads/scope/OLDalg2scope/sequence_rationale.pdf#page=23
www.utdanacenter.org/mathtoolkit/downloads/scope/OLDalg2scope/sequence_ra...
 While revisiting the data <span class="highlight">activity</span> from Unit I, emphasis should be placed on:  Identifying the limitations of the <span class="highlight">domain</span> and range <span class="highlight">for</span> the situation versus the <span class="highlight">domain</span> and range <span class="highlight">for</span> the function  Parameters <span class="highlight">for</span> the situation, and  The use of this data collected to create and solve <span class="highlight">a</span> mathematical model to make inferences and justifications. Unit VI: Exponential and Logarithmic Functions
ALGEBRA II
problems. DAP.6.AII.1 *Find regression line for scatter plot, using appropriate technology, and interpret the correlation coefficient DAP.6.AII.2 *Interpret and use the correlation coefficient to assess the strength of the linear relationship between two variables DAP.6.AII.3 *Find...
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problems. DAP.6.AII.1 *Find regression line for scatter plot, using appropriate technology, and interpret the correlation coefficient DAP.6.AII.2 *Interpret and use the correlation coefficient to assess the strength of the linear relationship between two variables DAP.6.AII.3 *Find the quadratic curve of best fit using appropriate technology DAP.6.AII.4 *Identify strengths and weaknesses of using regression equations to approximate data DAP.6.AII.5 *Compute and explain measures of spread (range
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http://arkansased.org/teachers/pdf/alg_II_06.pdf#page=8
arkansased.org/teachers/pdf/alg_II_06.pdf#page=8
problems. DAP.6.AII.1 *Find regression line <span class="highlight">for</span> scatter plot, <span class="highlight">using</span> appropriate technology, and interpret the correlation coefficient DAP.6.AII.2 *Interpret and use the correlation coefficient to assess the strength of the linear relationship between two variables DAP.6.AII.3 *Find the quadratic curve of best fit <span class="highlight">using</span> appropriate technology DAP.6.AII.4 *Identify strengths and weaknesses of <span class="highlight">using</span> regression equations to approximate data DAP.6.AII.5 *Compute and explain measures of spread (range
KINDERGARTEN
Priority Academic Student Skills School Improvement 172 Mathematics b. Identify whether the model/equation is a curve of best fit for the data, using various methods and tools which may include a graphing calculator. * 2. Measures of Central Tendency and Variability...
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Priority Academic Student Skills School Improvement 172 Mathematics b. Identify whether the model/equation is a curve of best fit for the data, using various methods and tools which may include a graphing calculator. * 2. Measures of Central Tendency and Variability a. Analyze and synthesize data from a sample using appropriate measures of central tendency (mean, median, mode, weighted average). b. Analyze and synthesize data from a sample using appropriate measures of
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http://sde.state.ok.us/Curriculum/PASS/Subject/math.pdf#page=40
sde.state.ok.us/Curriculum/PASS/Subject/math.pdf#page=40
Priority Academic Student Skills School Improvement 172 Mathematics b. Identify whether the model/equation is <span class="highlight">a</span> curve of best fit <span class="highlight">for</span> the data, <span class="highlight">using</span> various methods and tools which may include <span class="highlight">a</span> graphing calculator. * 2. Measures of Central Tendency and Variability <span class="highlight">a</span>. Analyze and synthesize data from <span class="highlight">a</span> sample <span class="highlight">using</span> appropriate measures of central tendency (mean, median, mode, weighted average). b. Analyze and synthesize data from <span class="highlight">a</span> sample <span class="highlight">using</span> appropriate measures of
Core Content For Mathematics Assessment
data using matrices and will use matrix addition, subtraction, multiplication (with matrices no larger than 2x2) and scalar multiplication to solve real-world problems. Characteristics of Data Sets MA-HS-4.2.1 Students will describe and compare data distributions and make inferences from the...
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data using matrices and will use matrix addition, subtraction, multiplication (with matrices no larger than 2x2) and scalar multiplication to solve real-world problems. Characteristics of Data Sets MA-HS-4.2.1 Students will describe and compare data distributions and make inferences from the data based on the shapes of graphs, measures of center (mean, median, mode) and measures of spread (range, standard deviation). DOK 2 MA-HS-4.2.2 Students will know the characteristics of the Gaussian normal
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http://www.education.ky.gov/users/OTL/CCA%204%201%20FINAL/CCA_41.pdf#page=89
www.education.ky.gov/users/OTL/CCA%204%201%20FINAL/CCA_41.pdf#page=89
data <span class="highlight">using</span> matrices and will use matrix addition, subtraction, multiplication (with matrices no larger than 2x2) and scalar multiplication to solve real-world problems. Characteristics of Data Sets MA-HS-4.2.1 Students will describe and compare data distributions and make inferences from the data <span class="highlight">based</span> on the shapes of graphs, measures of center (mean, median, mode) and measures of spread (range, standard deviation). DOK 2 MA-HS-4.2.2 Students will know the characteristics of the <span class="highlight">Gaussian</span> normal
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9 Topics in Discrete Mathematics: Glossary Mathematics Curriculum Framework Revised 2004 Amended 2008 Arkansas Department of Education Linear programming A method for finding the maximum or minimum value of a function in two variables subject to given constraints on the variab...
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9 Topics in Discrete Mathematics: Glossary Mathematics Curriculum Framework Revised 2004 Amended 2008 Arkansas Department of Education Linear programming A method for finding the maximum or minimum value of a function in two variables subject to given constraints on the variables Normal distribution A pattern for the distribution of a set of data which follows a bell shaped curve; sometimes called the Gaussian distribution Objective function (or objective quantity) An algebraic expression in
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http://arkansased.org/teachers/pdf/discrete_math_9-12_08.pdf#page=10
arkansased.org/teachers/pdf/discrete_math_9-12_08.pdf#page=10
9 Topics in Discrete Mathematics: Glossary Mathematics Curriculum Framework Revised 2004 Amended 2008 Arkansas Department of Education Linear programming <span class="highlight">A</span> method <span class="highlight">for</span> finding the maximum or minimum value of <span class="highlight">a</span> function in two variables subject to given constraints on the variables Normal distribution <span class="highlight">A</span> pattern <span class="highlight">for</span> the distribution of <span class="highlight">a</span> set of data which follows <span class="highlight">a</span> bell shaped curve; sometimes called the <span class="highlight">Gaussian</span> distribution Objective function (or objective quantity) An algebraic expression in
Microsoft Word - VSC. Algegra II 6.07.doc
defined, simple rational or exponential model and apply that model to solve the problem. Assessment Limits #0;� The majority of the items should include a verbal description of a real-world situation. Skill Statement #0;� Given a scatter plot of approximately...
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defined, simple rational or exponential model and apply that model to solve the problem. Assessment Limits #0;� The majority of the items should include a verbal description of a real-world situation. Skill Statement #0;� Given a scatter plot of approximately linear data, the student will write an equation of best fit and/or use that equation to find values for x or f(x) using a graphing calculator. #0;� Given a verbal description and/or a table of values of a function, the students will recognize
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http://mdk12.org/share/hsvsc/source/VSC_algebraII_hs.pdf#page=6
mdk12.org/share/hsvsc/source/VSC_algebraII_hs.pdf#page=6
defined, simple rational or exponential model and apply that model to solve the problem. Assessment Limits #0;� The majority of the items should include <span class="highlight">a</span> verbal description of <span class="highlight">a</span> real-world situation. Skill Statement #0;� Given <span class="highlight">a</span> scatter plot of approximately linear data, the student will write an equation of best fit and/or use that equation to find values <span class="highlight">for</span> x or f(x) <span class="highlight">using</span> <span class="highlight">a</span> graphing calculator. #0;� Given <span class="highlight">a</span> verbal description and/or <span class="highlight">a</span> table of values of <span class="highlight">a</span> function, the students will recognize
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