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Collaborative Statistics: Data Sets
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This module provides data sets for use with the Collaborative Statistics textbook/collection. ... More

This module provides data sets for use with the Collaborative Statistics textbook/collection. Data sets include a series of recorded motorcycle race and practice lap times as well as IPO stock prices. Less

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Material Type:
Readings
Provider:
Rice University
Provider Set:
Connexions
Author:
Barbara Illowsky, Ph.d.
Susan Dean
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Color Sudoku
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The popular sudoku puzzles use numbers, but the game could played with ... More

The popular sudoku puzzles use numbers, but the game could played with any set of 9 different objects! In this activity (on pages 56-75 of PDF), learners use objects of different colors (marbles, paper squares, candies) to solve sudoku puzzles. Learners use logic to determine where all the colored objects go, given the different colors already present on the puzzles. The activity includes suggestions for how to approach the game, 10 puzzles of varying size and difficulty, and links to websites with many more puzzles. Less

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Subject:
Education
Mathematics
Material Type:
Activities and Labs
Games
Instructional Material
Provider:
Science and Math Informal Learning Educators (SMILE)
Provider Set:
SMILE Pathway: Science and Math Activities in One Search
Author:
OMSI
Oregon Museum of Science and Industry
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Introduction to Probability Theory
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In this course, the student will learn the basic terminology and concepts ... More

In this course, the student will learn the basic terminology and concepts of probability theory, including sample size, random experiments, outcome spaces, discrete distribution, probability density function, expected values, and conditional probability. The course also delves into the fundamental properties of several special distributions, including binomial, geometric, normal, exponential, and Poisson distributions. Upon successful completion of this course, the student will be able to: Define probability, outcome space, events, and probability functions; Use combinations to evaluate the probability of outcomes in coin-flipping experiments; Calculate the union of events and conditional probability; Apply Bayes's theorem to simple situations; Calculate the expected values of discrete and continuous distributions; Calculate the sums of random variables; Calculate cumulative distributions and marginal distributions; Evaluate random processes governed by binomial, multinomial, geometric, exponential, normal, and Poisson distributions; Define the law of large numbers and the central limit theorem. (Mathematics 252) Less

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Assessments
Full Course
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Video Lectures
Provider:
The Saylor Foundation
Provider Set:
Saylor Foundation
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Real Analysis I
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This course is designed to introduce the student to the rigorous examination ... More

This course is designed to introduce the student to the rigorous examination of the real number system and the foundations of calculus. Analysis lies at the heart of the trinity of higher mathematics algebra, analysis, and topology because it is where the other two fields meet. Upon successful completion of this course, the student will be able to: Use set notation and quantifiers correctly in mathematical statements and proofs; Use proof by induction or contradiction when appropriate; Define the rational numbers, the natural numbers, and the real numbers, and understand their relationship to one another; Define the well-ordering principle the completeness/supremum property of the real line, and the Archimedean property; Prove the existence of irrational numbers; Define supremum and infimum; Correctly and fluently manipulate expressions with absolute value and state the triangle inequality; Define and identify injective, surjective, and bijective mappings; Name the various cardinalities of sets and identify the cardinality of a given set; Define Euclidean space and vector space and show that Euclidean space is a vector space; Define the complex numbers and manipulate them algebraically; Write equations for lines and planes in Euclidean space; Define a normed linear space, a norm, and an inner product; Define metric spaces, open sets; define open, closed, and bounded sets; define cluster points; define density; Define convergence of sequences and prove or disprove the convergence of given sequences; Prove and use properties of limits; Prove standard results about closures, intersections, and unions of open and closed sets; Define compactness using both open covers and sequences; State and prove the Heine-Borel Theorem; State the Bolzano-Weierstrass Theorem; State and use the Cantor Finite Intersection Property; Define Cauchy sequence and prove that specific sequences are Cauchy; Define completeness and prove that Euclidean space with the standard metric is complete; Show that convergent sequences are Cauchy; Define limit superior and limit inferior; Define convergence of series using the Cauchy criterion and use the comparison, ratio, and root tests to show convergence of series; Define continuity and state, prove, and use properties of limits of continuous functions, including the fact that continuous functions attain extreme values on compact sets; Define divergence of functions to infinity and use properties of infinite limits; State and prove the intermediate value property; Define uniform continuity and show that given functions are or are not uniformly continuous; Give standard examples of discontinuous functions, such as the Dirichlet function; Define connectedness and identify connected and disconnected sets Construct the Cantor ternary set and state its properties; Distinguish between pointwise and uniform convergence; Prove that if a sequence of continuous functions converges uniformly, their limit is also continuous; Define derivatives of real- and extended-real-valued functions; Compute derivatives using the limit definition and prove basic properties of derivatives; State the Mean Value Theorem and use it in proofs; Construct the Riemann Integral and state its properties; State the Fundamental Theorem of Calculus and use it in proofs; Define pointwise and uniform convergence of series of functions; Use the Weierstrass M-Test to check for uniform convergence of series; Construct Taylor Series and state Taylor's Theorem; Identify necessary and sufficient conditions for term-by-term differentiation of power series. (Mathematics 241) Less

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Material Type:
Assessments
Full Course
Homework and Assignments
Readings
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Textbooks
Video Lectures
Provider:
The Saylor Foundation
Provider Set:
Saylor Foundation
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.)310.1( tcejbus ngised enotspac eht dna )150.1 ,140.1 ,130.1( stcejbus ngised aera ... More

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