'Discrete variables' presentation slideshows

Enrollment Fall 2005 (all students)

932 views • 79 slides

Discretely-Constrained MPECs for Electricity Markets

Steven A. Gabriel 1,2 , Florian Leuthold 3 1 Dept. of Civil & Env . Engineering, Co-Director, Engineering and Public Policy Program, University of Maryland, USA 2 German Institute for Economic Research (DIW), Berlin Germany

464 views • 40 slides

Surface-based Group Analysis in FreeSurfer

Surface-based Group Analysis in FreeSurfer. Outline. Processing Stages Command-line Stream Assemble Data Design/Contrast (GLM Theory) Analyze Visualize Interactive/Automated GUI (QDEC) Correction for multiple comparisons. Aging Exploratory Analysis. In which areas does thickness

396 views • 38 slides

Mark Hasegawa-Johnson jhasegaw@uiuc University of Illinois at Urbana-Champaign, USA

Landmark-Based Speech Recognition: Spectrogram Reading, Support Vector Machines, Dynamic Bayesian Networks, and Phonology. Mark Hasegawa-Johnson jhasegaw@uiuc.edu University of Illinois at Urbana-Champaign, USA. Lecture 9. Learning in Bayesian Networks.

491 views • 35 slides

Discrete Probability Distributions

Chapter 5. Discrete Probability Distributions. Objectives. In this chapter, you learn: The properties of a probability distribution. To compute the expected value and variance of a probability distribution. To compute probabilities from binomial, and Poisson distributions.

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Lesson 2 Exploring Data with Graphs

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Sociology 601, Class 4: September 10, 2009

Sociology 601, Class 4: September 10, 2009. Chapter 4: Distributions Probability distributions (4.1) The normal probability distribution (4.2) Sampling distributions (4.3, 4.4). 4.1: probability distributions.

419 views • 29 slides

Statistics: A Tool For Social Research

Statistics: A Tool For Social Research. Seventh Edition Joseph F. Healey. Chapter 1. Introduction. Chapter Outline. Why Study Statistics? The Role of Statistics in Scientific Inquiry The Goals of This Text Descriptive and Inferential Statistics Discrete and Continuous Variables

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Welcome to PMBA0608: Economics/Statistics Foundation

Welcome to PMBA0608: Economics/Statistics Foundation. Fall 2006 Session 7: September 30. How was the exam?. Any questions of exam questions?. Next Class. October 18 I will be in Eastern campus Local students can meet with me at 7:00 pm (half hour before class)

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AP Statistics B

AP Statistics B. March 1, 2012. AP Statistics B warm-ups Thursday, March 1, 2012.

323 views • 26 slides

Chapter 1: Introduction to Statistics

Chapter 1: Introduction to Statistics. Variables. A variable is a characteristic or condition that can change or take on different values. Most research begins with a general question about the relationship between two variables for a specific group of individuals. Population.

330 views • 25 slides

Categoric Variables

433 views • 20 slides

Quantitative Demand Analysis

Quantitative Demand Analysis. Headlines:. In 1989 Congress passed and president signed a minimum-wage bill. The purpose of this bill was to increase the purchasing power of unskilled workers. We know that the consequences of price floor is decrease in demand. Now lets quantify it.

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4.1 Mathematical Expectation

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FREQUENCY DISTRIBUTIONS

FREQUENCY DISTRIBUTIONS. What is a Frequency Distribution? What are Frequency Distributions Used For? Ways of Displaying Frequency Distributions Describing Frequency Distributions Frequency Distribution Statistics. What is a Frequency Distribution?.

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A control variable is one that must be kept constant for a fair test.

Control Variables. A control variable is one that must be kept constant for a fair test. You must make sure that you keep control variables constant throughout your experiment to ensure that you are carrying out a fair test. Example:.

3.63k views • 12 slides

4.1 Mathematical Expectation

1.28k views • 12 slides

Non response and missing data in longitudinal surveys

Non response and missing data in longitudinal surveys. Traditional ways of handling attrition and missing data. Weighting typically used for attrition Sample design and initial non-response provides basic weights

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Measuring Variation Patterns of distribution

Measuring Variation Patterns of distribution. Normal distributions Most common type to describe individuals w/in populations Bell shaped More are closer to the average than to the extremes Based on continuous variables Binomial distributions

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Discrete and Continuous Random Variables

Discrete and Continuous Random Variables. What is a random variable?. A variable whose value is a numerical outcome of a random phenomena Example: Flipping a coin 3 times. Let X be the number of heads. HHH X = 3 HTT X = 1 X can be 0, 1, 2, or 3 for this phenomena. Discrete Variables.

312 views • 6 slides