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Probability
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In this class, students will be able to identify what is probability and have a general concept. The students should be able to calculate the probability questions by using the formula of conditional probability (P( A|B )=number of A/the total number of outcomes.) 

Subject:
Statistics and Probability
Material Type:
Lesson Plan
Author:
Kailin Zheng
Date Added:
04/21/2019
Practical probability exercises
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In this lesson is colected four practical exercises about probability. Lesson is ready to use, but teachers should be prepared to add some extra information about this topic befor doing the lesson.

Subject:
Statistics and Probability
Material Type:
Lesson Plan
Author:
Kristaps Auzans
Date Added:
05/15/2017
Lecture 11: Probability and Statistics for Computer Science - "Linear Regression"
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Lecture for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Subject:
Applied Science
Computer Science
Material Type:
Lecture
Lecture Notes
Lesson Plan
Provider:
CUNY Academic Works
Provider Set:
City College of New York
Author:
Evan Agovino
Nyc Tech-in-residence Corps
Date Added:
05/06/2020
Lecture 7: Probability and Statistics for Computer Science - "Project Review"
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Lecture for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Subject:
Applied Science
Computer Science
Material Type:
Lecture
Lecture Notes
Lesson Plan
Provider:
CUNY Academic Works
Provider Set:
City College of New York
Author:
Evan Agovino
Nyc Tech-in-residence Corps
Date Added:
05/06/2020
Exam: Probability and Statistics for Computer Science - "Midterm Exam Review"
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Midterm Exam Review for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Subject:
Applied Science
Computer Science
Material Type:
Assessment
Provider:
CUNY Academic Works
Provider Set:
City College of New York
Author:
Evan Agovino
Nyc Tech-in-residence Corps
Date Added:
05/06/2020
Modeling Conditional Probabilities 2
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This lesson unit is intended to help teachers assess how well students understand conditional probability, and, in particular, to help teachers identify and assist students who have the following difficulties: representing events as a subset of a sample space using tables and tree diagrams; and understanding when conditional probabilities are equal for particular and general situations.

Subject:
Mathematics
Statistics and Probability
Material Type:
Assessment
Lesson Plan
Provider:
Shell Center for Mathematical Education
Provider Set:
Mathematics Assessment Project (MAP)
Date Added:
04/26/2013
Evaluating Statements About Probability
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This lesson unit addresses common misconceptions relating to probability of simple and compound events. The lesson will help you assess how well students understand concepts of: Equally likely events; randomness; and sample sizes.

Subject:
Mathematics
Statistics and Probability
Material Type:
Assessment
Lesson Plan
Provider:
Shell Center for Mathematical Education
Provider Set:
Mathematics Assessment Project (MAP)
Date Added:
04/26/2013
Exam: Probability and Statistics for Computer Science - "Practice Final Exam"
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Practice Final Exam for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Subject:
Applied Science
Computer Science
Material Type:
Assessment
Provider:
CUNY Academic Works
Provider Set:
City College of New York
Author:
Evan Agovino
Nyc Tech-in-residence Corps
Date Added:
05/06/2020
Math, Grade 7, Samples and Probability, Probability As A Measure Of Likelihood
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Students will begin to think about probability by considering how likely it is that their house will be struck by lightning. They will consider the relative likelihood of familiar events (e.g., outdoor temperature, test scores) on the continuum between impossible and certain. Students will discuss where on the continuum "likely," "unlikely," and "equally likely as unlikely" are.Key ConceptsAs students begin their study of probability, they look at the likelihood of events. Students have an intuitive sense of likelihood, even if no numbers or ratios are attached to the events. For example, there is clearly a better chance that a specific student will be chosen at random from a class than from the entire school.Goals and Learning ObjectivesThink about the concept of likelihood.Understand that probability is a measure of likelihood.Informally estimate the likelihood of certain events.Begin to think about why one event is more likely than another.SWD: Students with disabilities may need additional support seeing the relationships among problems and strategies. Throughout this unit, keep anchor charts available and visible to assist them in making connections and working toward mastery. Provide explicit think alouds comparing strategies and making connections. In addition, ask probing questions to get students to articulate how a peer solved the problem or how one strategy or visual representation is connected or related to another.

Subject:
Mathematics
Statistics and Probability
Material Type:
Lesson Plan
Date Added:
09/21/2015
Introduction to Probability
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The tools of probability theory, and of the related field of statistical inference, are the keys for being able to analyze and make sense of data. These tools underlie important advances in many fields, from the basic sciences to engineering and management.
This resource is a companion site to 6.041SC Probabilistic Systems Analysis and Applied Probability. It covers the same content, using videos developed for an edX version of the course.

Subject:
Applied Science
Engineering
Mathematics
Statistics and Probability
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Jaillet, Patrick
Tsitsiklis, John
Date Added:
02/01/2018
Math, Grade 7, Samples and Probability, Comparing Theoretical & Experimental Probability
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Students extend their understanding of compound events. They will compare experimental results to predicted results by calculating the probability of an event, then conducting an experiment.Key ConceptsStudents apply their understanding of compound events to actual experiments.Students will see there is variability in actual results.Goals and Learning ObjectivesContinue to explore compound independent events.Compare theoretical probability to experimental probability.

Subject:
Statistics and Probability
Material Type:
Lesson Plan
Date Added:
09/21/2015
Lecture 5: Probability and Statistics for Computer Science - "Random Variables and Distribution"
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Lecture for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Subject:
Applied Science
Computer Science
Material Type:
Lecture
Lecture Notes
Lesson Plan
Provider:
CUNY Academic Works
Provider Set:
City College of New York
Author:
Evan Agovino
Nyc Tech-in-residence Corps
Date Added:
05/06/2020
Lecture 10: Probability and Statistics for Computer Science - "Relationships Between Variables"
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Lecture for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Subject:
Applied Science
Computer Science
Material Type:
Lecture
Lecture Notes
Lesson Plan
Provider:
CUNY Academic Works
Provider Set:
City College of New York
Author:
Evan Agovino
Nyc Tech-in-residence Corps
Date Added:
05/06/2020
Buttons: Statistical Questions
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Statistics is the study of variability. Students who understand statistics need to be able to identify and pose questions that can be answered by data that vary. The purpose of this task is to provide questions related to a particular context (a jar of buttons) so that students can identify which are statistical questions. The task also provides students with an opportunity to write a statistical question that pertains to the context.

Subject:
Mathematics
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Illustrative Mathematics
Provider Set:
Illustrative Mathematics
Author:
Illustrative Mathematics
Date Added:
10/19/2012
Lecture 2: Probability and Statistics for Computer Science - "Descriptive Stats"
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Lecture for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Subject:
Applied Science
Computer Science
Material Type:
Lecture
Lecture Notes
Lesson Plan
Provider:
CUNY Academic Works
Provider Set:
City College of New York
Author:
Agovino Evan
Cuny City College
Evan Agovino
Nyc Tech-in-residence Corps
Date Added:
05/06/2020
Basic Probability
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Short Description:
This book provides a brief introduction to some common ideas in the study of probability. At the University of Minnesota, this material is included in a course on College Algebra designed to give students the basic skills to take an introductory Statistics course. The material itself is basic, and should be within the grasp of students who have successfully completed a high school Algebra I course.

Word Count: 1827

ISBN: 978-1-946135-79-7

(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)

Subject:
Mathematics
Statistics and Probability
Material Type:
Textbook
Provider:
University of Minnesota
Author:
Mike Weimerskirch
Date Added:
01/01/2022
Probability: Birthday Probability Problem
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This lesson is a birthday problem that determines the probability that at least 2 people in a room of 30 share the same birthday. [Probability playlist: Lesson 17 of 29]

Subject:
Mathematics
Statistics and Probability
Material Type:
Lecture
Provider:
Khan Academy
Provider Set:
Khan Academy
Author:
Salman Khan
Date Added:
01/17/2012