'Simple events' diaporamas de présentation

Probability

Probability. 2/25/2012. Basic Probability. We are going to study probability so that we can use it later during the study of inferential statistics. Rare Event Rule for Inferential Statistics

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Probability

Probability. Chapter 4. Basic Probability. We are going to study probability so that we can use it later during the study of inferential statistics. Rare Event Rule for Inferential Statistics

2.44k views • 97 slides

Review

Review. Detecting Outliers. Review. Detecting Outliers Standard Deviation Percentiles/Box Plots Suspected and Highly Suspected Outliers. Review. Detecting Outliers Standard Deviation Percentiles/Box Plots Suspected and Highly Suspected Outliers. Review. Detecting Outliers

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Prof. Saibal Chattopadhyay IIM Calcutta

IIMC Long Duration Executive Education Executive Programme in Business Management Statistics for Managerial Decisions. Prof. Saibal Chattopadhyay IIM Calcutta. An Outline of the Course. Probability Theory: Basic Concepts Distribution Theory:Random Variables

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PUAF 610 TA

PUAF 610 TA. Session 4. Some words. My email: jhlu@umd.edu Things to be discussed in TA Questions on the course and problem sets. Today. Problem Sets 1 * Probability Sampling * Standard Error STATA. Measurement scales.

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3 3 Addition Rule

3 3 Addition Rule. Compound Event Any event combining two or more simple events. Definition. Compound Event Any event combining two or more simple events Notation P(A or B) = P (event A occurs or event B occurs or they both occur). Definition. General Rule

559 views • 33 slides

Chapter 3

Chapter 3. Probability. Chapter Outline. 3.1 Basic Concepts of Probability 3.2 Conditional Probability and the Multiplication Rule 3.3 The Addition Rule 3.4 Additional Topics in Probability and Counting. Section 3.1. Basic Concepts of Probability. Section 3.1 Objectives.

811 views • 33 slides

Section 3.1

Basic Concepts of Probability. Section 3.1. Section 3.1 Objectives. Identify the sample space of a probability experiment Identify simple events Use the Fundamental Counting Principle Distinguish among classical probability, empirical probability, and subjective probability

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Section 3.1

Section 3.1. Basic Concepts of Probability. Section 3.1 Objectives. Identify the sample space of a probability experiment Identify simple events Use the Fundamental Counting Principle Distinguish among classical probability, empirical probability, and subjective probability

561 views • 31 slides

Discrete Random Variables

Discrete Random Variables. Introduction. In previous lectures we established a foundation of the probability theory; we applied the probability theory to some applications; w e covered combinatorial problems; w e studied Bayesian theorem. In this lecture

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5.1

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Lecture Slides

Lecture Slides. Elementary Statistics Twelfth Edition and the Triola Statistics Series by Mario F. Triola. Chapter 4 Probability. 4-1 Review and Preview 4-2 Basic Concepts of Probability 4-3 Addition Rule 4-4 Multiplication Rule: Basics

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Probability Rules

Probability Rules. Section 4.2 Created by Laura Ralston. 4 Basic Probability Rules. Probability of any event E is a number (fraction or decimal) between and including 0 and 1 0 < P(E) < 1. If an event E cannot occur, its probability is 0 P(impossible event) =0. The Complement.

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Addition Rule

Addition Rule. Definition. Compound Event Any event combining 2 or more simple events. Notation P ( A or B ) = P (event A occurs or event B occurs or A and B both occur). General Rule for a Compound Event.

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Section 4-3

Section 4-3. The Addition Rule. COMPOUND EVENT. A compound event is any event combining two or more simple events. NOTATION P ( A or B ) = P (in a single trial, event A occurs or event B occurs or they both occur).

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Student Learning of Probabilistic Concepts and their Misconceptions

Student Learning of Probabilistic Concepts and their Misconceptions. Presented by: Nadia Monrose EMS 792X November 28, 2011. Introduction Intuition and Probabilistic Learning Epistemology of Probabilistic Development Misconceptions Instructional Practices Discussion/Implications.

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FASTA forces assemblers to make mistakes

FASTG: Representing the true information content of a genome assembly. Iain MacCallum, David B. Jaffe Broad Institute of MIT and Harvard, Cambridge, MA In collaboration with: Michael Schatz, Daniel Rokhsar , and Assemblathon Format Group. The Solution: FASTG

109 views • 1 slides