'Expected value' presentation slideshows

Regression for Data Mining

2.96k views • 103 slides

Sampling Error

Sampling Error. If probability methods are used, sampling is like drawing at random from a box, without replacement. The likely amount of chance (sampling) error in a simple random sample can be found if the population composition is known. Sampling Error.

1.99k views • 72 slides

Cost as the Dependent Variable (I)

Cost as the Dependent Variable (I). Paul G. Barnett, PhD VA Health Economics Resource Center. What is health care cost?. Cost of an intermediate product, e.g., chest x-ray a day of stay minute in the operating room a dispensed prescription Cost of a bundle of products Outpatient visit

1.16k views • 64 slides

Shelley Begley Application Development Engineer Agilent Technologies

Electromagnetic Properties of Materials: Characterization at Microwave Frequencies and Beyond. Shelley Begley Application Development Engineer Agilent Technologies. Agenda. Definitions Measurement Techniques Coaxial Probe Transmission Line Free-Space Resonant Cavity Summary.

766 views • 55 slides

A spatial integrated population model applied to black-footed albatross

A spatial integrated population model applied to black-footed albatross. Simon Hoyle Mark Maunder. Background. Black-footed albatross Phoebastria nigripes Breed on north-western Hawaiian islands Genetically distinct population on Torishima island

619 views • 47 slides

Data Analysis: Simple Statistical Tests

Data Analysis: Simple Statistical Tests. Goals. Understand confidence intervals and p-values Learn to use basic statistical tests including chi square and ANOVA . Types of Variables. Types of variables indicate which estimates you can calculate and which statistical tests you should use

994 views • 45 slides

Data Analysis: Simple Statistical Tests

Data Analysis: Simple Statistical Tests. Goals. Understand confidence intervals and p-values Learn to use basic statistical tests including chi square and ANOVA . Types of Variables. Types of variables indicate which estimates you can calculate and which statistical tests you should use

1.15k views • 45 slides

Ch.08 Revising Judgments in the Light of New Information Dr. Ayham Jaaron

Ch.08 Revising Judgments in the Light of New Information Dr. Ayham Jaaron. Introduction.

1.67k views • 38 slides

Chapter 2

Chapter 2. Probability Concepts and Applications. Probability. A probability is a numerical description of the chance that an event will occur. Examples: P(it rains tomorrow) P(flooding in St. Louis in September) P(winning a game at a slot machine)

389 views • 38 slides

Decision Analysis

Decision Analysis. OPS 370. Decision Theory. A. B. a. b. c. d. e. Decision Theory. A. a. b. c. . Decision Theory. Steps: 1. A. B. 2. A. 3. 4. 5. Payoff Table. Shows Expected Payoffs for Various States of Nature. Decision Environments. A. a. B. a. C.

581 views • 38 slides

Project Management with PERT/CPM

Project Management with PERT/CPM. PERT/CPM. PERT : program evaluation and review technique CPM : critical path method Use a project network, Activity-on-Node (AON): Nodes: activities, or tasks, to be performed Arcs: show immediate predecessors to an activity

2.53k views • 37 slides

Expected Value and Fair Games

461 views • 35 slides

Expected values, covariance, correlation and expected values

Expected values, covariance, correlation and expected values. Introduction to Bivariate Regression . Does talking about politics cause people to be more interested in politics? Or does an interest in politics cause people to talk about politics?. Is this a causal relationship?.

503 views • 24 slides

Fundamentals of Finance

Fundamentals of Finance. FINAL EXAM REVIEW. 12/10/2012. What to Study. Power Point Slides Self test questions (all covered chapters) All past quizzes All homework problems Review questions (all covered chapters) Prior exams (my office, see office hours)

226 views • 22 slides

Derivation of the Expected Value-Variance Frontier without a Risk-free Asset

Derivation of the Expected Value-Variance Frontier without a Risk-free Asset. Lecture X. Mathematical derivation without a Risk-free asset. General Formulation. Mean-variance frontier without a risk-free asset:. Lagrange Formulation. Looking at the constraints.

350 views • 21 slides

Business 90: Business Statistics Professor David Mease Sec 0 3 , T R 7 : 3 0- 8 : 4 5AM BBC 204

318 views • 17 slides

PharmaSim CONSUMER BEHAVIOR

PharmaSim CONSUMER BEHAVIOR. Consumer Product & Brand Management Marketing 3349. Segments Related to Consumer Needs. Illness Cold, Cough, Allergy Symptoms Aches, Nasal Congestion, Chest Congestion, Cough, Allergy Age Young Singles, Young Families, Mature Families, Empty Nesters, Retired

243 views • 11 slides

Item Analysis Using The Rasch Model

Item Analysis Using The Rasch Model. Terms and Meaning. The standard error (SE) is the standard deviation of the sampling distribution of a statistic. The standard error of a measure captures its precision in a particular context. The accuracy of a measure is captured by fit statistics. .

447 views • 11 slides

FARM AND RANCH CREDIT

FARM AND RANCH CREDIT. BASIC LENDING PRINCIPLES HUMAN/MANAGEMENT FACTORS FINANCIAL POSITION AND PROGRESS REPAYMENT CAPACITY COLLATERAL LOAN PURPOSE. HUMAN / MANAGEMENT FACTORS. CHARACTER HONESTY DETERMINATION TO MEET OBLIGATIONS PERFORMANCE RECORD WILLINGNESS TO COOPERATE.

216 views • 10 slides

OPERATIONS MANAGEMENT Quantitative Module A - Decision Making Tools

OPERATIONS MANAGEMENT Quantitative Module A - Decision Making Tools .

433 views • 10 slides