'Discrete data' diaporamas de présentation

Chapter 6 Discrete Probability Distributions

KVANLI PAVUR KEELING. Chapter 6 Discrete Probability Distributions. Chapter Objectives. At the completion of this chapter, you should be able to answer the following questions: ? What is meant by the term " probability distribution ?"

934 views • 74 slides

CPSC 531:Input Modeling

678 views • 34 slides

Toward a unified approach to fitting loss models

Toward a unified approach to fitting loss models. Jacques Rioux and Stuart Klugman, for presentation at the IAC, Feb. 9, 2004. Handout/slides. E-mail me Stuart.klugman@drake.edu. Overview. What problem is being addressed? The general idea The specific ideas Models to consider

447 views • 34 slides

Epic Enterprise Implementation

1.12k views • 32 slides

Chapter 2

Data, Reality, and Problem Solving. Chapter 2. Data, Reality, and Problem Solving Sections 2.1-2.4 The Reality of Conducting a Study. HAWKES LEARNING SYSTEMS math courseware specialists. Objectives:. Learn the ethical concerns of conducting a study.

446 views • 32 slides

Simulation Modeling and Analysis

Simulation Modeling and Analysis. Output Analysis. 1. Outline. Stochastic Nature of Output Taxonomy of Simulation Outputs Measures of Performance Point Estimation Interval Estimation Output Analysis in Terminating Simulations Output Analysis in Steady-state Simulations. 2. Introduction.

903 views • 31 slides

Psychology 10

Psychology 10. Analysis of Psychological Data January 29, 2014. The Plan for Today. More on interpolation Measures of central tendency Mean, median, and mode The mean From raw data From grouped data The median The median and interpolation. More examples of interpolation.

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Continuous Data

388 views • 23 slides

Statistical Inference for Managers

Statistical Inference for Managers. Lecture 3 Probability Distributions. Probability Distribution. Types of Probability Distributions: (As discussed in first lecture) 1- Discrete Probability: Can have only a limited number of values.

338 views • 20 slides

Relations and Functions

Relations and Functions. Lesson 3: Graphs of Relations and Functions. Todays Objectives. Graph a set of data and determine the restrictions on the domain and range Explain why data points should or should not be connected on the graph for a situation

446 views • 19 slides

EPI 824 Reproductive outcomes

EPI 824 Reproductive outcomes. Wilfried Karmaus Department of Epidemiology, MSU karmaus@msu.edu You find class material in: http://www.msu.edu/course/epi/824/. Content. Scales Incidence, point / period / lifetime prevalence Sources of information Methods of determination

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How Content360 Solutions Helped Achieve HIMSS Stage 7

379 views • 17 slides

6-6

6-6. Classifying Data. Objective Classify data as either categorical or quantitative Understand the difference between discrete and continuous. Lesson Quiz: 6-5 Answers .

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Statistics, Graphs and Examples

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Implementation Workgroup

Implementation Workgroup. Constraining the CCDA User Experience Presentation. Udayan Mandavia, iPatientCare, Inc. With: Kedar Mehta and Arnaz Bharucha July 28, 2014. Background. iPatientCare EHR is one of the three CMS designated Test EHRs

284 views • 13 slides

Week 2: Asynchronous Architecture

Week 2: Asynchronous Architecture. Game Loop Design. Asynchronous Architecture Synchronous Loop. Quick prototype Complicated simulation code FPS bound Input lags with renderer Non-discrete Physics Only option when not threading Some cell phones & gaming systems

255 views • 12 slides

STATISTICS FOR BUSINESS

STATISTICS FOR BUSINESS. Chapter 4 : Discrete data and probability. The shopping mall. STATISTICS FOR BUSINESS ( Discrete data and probability). The shopping mall. Discrete data is composed of integer values , or whole numbers

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Categorical and discrete data. Non-parametric tests

Categorical and discrete data. Non-parametric tests. Non-parametric tests: estimate sample differences when the known distribution shapes cannot help, or even confuse. Metrics of arbitrary distibutions. Median: the value that "splits the sample in half"

1.04k views • 9 slides

Continuous and Discrete Probability Distributions

Continuous and Discrete Probability Distributions. Sections 7.1 and 8.1. Continuous vs. discrete. A discrete random variable has definite boundaries between the different outcomes. Continuous vs. discrete. A continuous random variable, has no distinct boundary between the outcomes.

201 views • 9 slides

Continuous and Discrete Probability Distributions

Continuous and Discrete Probability Distributions. Sections 7.1 and 8.1. Continuous vs. discrete. A discrete random variable has definite boundaries between the different outcomes. Continuous vs. discrete. A continuous random variable, has no distinct boundary between the outcomes.

220 views • 9 slides