Statistică la învățătură-cls. a X-a

Oct 22, 2014

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Statistică la învățătură-cls. a X-a. Anul 2009-2010. Lista elevilor premianți. Popescu Elena Gavrilă Alexandra Pop Maria.

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Statistică la învățătură-cls. a X-a

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Statistică la învățătură-cls. a X-a Anul 2009-2010
Lista elevilor premianți • Popescu Elena • Gavrilă Alexandra • Pop Maria

sampling

Sampling error. StatisticA mathematical description of any characteristic that can be measured; say, the mean (arithmetic average)A mathematical way to describe the interplay between two or more characteristics; say, the correlation coefficient (r)Summary statistic: A statistic that gives an overall measure; say, the meanPopulation parameterA statistic of the population; say, the meanSample statisticSame, of a sampleSampling error: Unintended differences between a population parameter 9453

474 views • 18 slides

Ch13 statistic (108)

Ch13 statistic (108). 13.1 6 13.2 6 13.3 2 13.4 6 13.5 3 13.6 4 13.7 6 13.8 5. Secondary Storage Management. The Memory Hierarchy. The Memory Hierarchy. Computer systems have several different components in which data may be stored.

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EQT373 STATISTIC FOR ENGINEERS Design of Experiment (DOE)

EQT373 STATISTIC FOR ENGINEERS Design of Experiment (DOE). Noorulnajwa Diyana Yaacob School of Bioprocess Engineering Universiti Malaysia Perlis 30 April 2012 DKD 1. DOE Objectives. At the end of this class, the student will be able to :

346 views • 24 slides

Be More Than A Statistic

Be More Than A Statistic. More than 196 billion text messages were sent or received in the United States last year. At any given moment during daylight hours, over 800,000 vehicles are being driven by someone using a cellphone.

316 views • 19 slides

AP Statistics

AP Statistics. 9.1 Sampling Distribution. Learning Objectives. Know the difference between a statistic and a parameter Understand that the value of a statistic varies between samples Be able to describe the shape, center and spread of a given sampling distribution

318 views • 22 slides

Functions with R

Functions with R. The first step is to invoke the boot library > library(boot ) The boot function need the following arguments : b oot(data,statistic,R,argument s used by statistic ) Data is the data you want to apply your statistic to.

152 views • 8 slides

Ch.9: Introduction to the t - statistic

Ch.9: Introduction to the t - statistic. First of 3 chapters (9, 10, & 11). Chapter Overview. Problem with using the z statistic in an hypothesis test Introduction to the t-statistic The sampling distribution of t values (the t distribution) Hypothesis testing using the t statistic

436 views • 21 slides

Introduction to the t-statistic

Introduction to the t-statistic. Chapter 9. The problem with z-scores. Formula = mean of sample, minus what mean of population would be if the null were true, all divided by the standard error of the mean

275 views • 12 slides

Chapter 15

Chapter 15. Tests of Significance: The Basics. Significance Testing. Also called “hypothesis testing” Objective: to test a claim about parameter μ Procedure: State hypotheses H 0 and H a Calculate test statistic Convert test statistic to P-value and interpret

358 views • 18 slides

Statistic

Energy Consumption Water Consumption Municipal Solid W aste generated Hazardous Waste generated. Statistic. Energy Consumption. As a Goal 30 % Energy usage reduction by 2017

168 views • 4 slides

STATISTIC FOR COMPUTING (CSNB293)

STATISTIC FOR COMPUTING (CSNB293). MODULE 1 GRAPHICAL DATA REPRESENTATION. Variables. A variable is a characteristic that may changes under different circumstances Examples: Hair color – varies between individuals White blood cell count – varies between individuals

240 views • 17 slides

The CHI SQUARE Statistic

The CHI SQUARE Statistic. Tests for Goodness of Fit and Independence. Preview. Color is known to affect human moods and emotion. Sitting in a pale-blue room is more calming than sitting in a bright-red room

294 views • 18 slides

r-statistic performance in S2

r-statistic performance in S2. Laura Cadonati LIGO-MIT LSC meeting – LLO March 18, 2004. D t = + 10 ms. D t = - 10 ms. confidence versus lag. 15. Max confidence: C M ( t 0 ) = 13.2 at lag = - 0.7 ms. 10. confidence. 5. 0. -10. 0. 10. lag [ms].

257 views • 15 slides

To explore approaches for Statistic Data to serve Sustainable Urban Development though Case Study

To explore approaches for Statistic Data to serve Sustainable Urban Development though Case Study. Wang Jianguo Resident Mission of the PRC, Asian Development Bank 20 October 2008. Importance of Statistic Data for Urban Development. Basis of Urban Planning

318 views • 18 slides

STATISTICAL INFERENCE PART II POINT ESTIMATION

STATISTICAL INFERENCE PART II POINT ESTIMATION. SUFFICIENT STATISTICS. X, f(x; ), . X 1 , X 2 ,…,X n be a sample rvs. Y=U(X 1 , X 2 ,…,X n ) is a statistic. A sufficient statistic , Y is a statistic which contains all the information for the estimation of .

430 views • 28 slides

Network Statistic and Monitoring System

Network Statistic and Monitoring System. Wayne State University Division of Computing and Information Technology. Network Statistic and Monitoring System.  Contents > Introduction > Function > Demonstration > System Specification > Conclusion. Introduction.

260 views • 15 slides

Bio-Statistic KUEU 3146 & KBEB 3153 Bio-Statistic

Bio-Statistic KUEU 3146 & KBEB 3153 Bio-Statistic. Estimation: Binomial, Poisson, Normal & Student’s t Distribution. Binomial Distribution. Two outcomes i.e Yes/No, Head/Tail, Live/Die, success/fail etc Independent event Defined by 2 parameters: n,p Mean, μ =np

304 views • 15 slides

CS 3343: Analysis of Algorithms

CS 3343: Analysis of Algorithms. Lecture 14: Order Statistics. Order statistics. The i th order statistic in a set of n elements is the i th smallest element The minimum is thus the 1 st order statistic The maximum is the n th order statistic The median is the n/2 order statistic

444 views • 25 slides

Introduction to the t Statistic

Introduction to the t Statistic. What were the formulae used for the z statistic?. z = (M – μ) / σ m σ m = σ/√n σ = √(SS/n). What Do You Notice About These Formulae?. They are based on population parameters How often do you think these population parameters are known?

380 views • 25 slides

SAMPLING DISTRIBUTIONS

SAMPLING DISTRIBUTIONS. Chapter 7. 7.1 How Likely Are the Possible Values of a Statistic? The Sampling Distribution. Statistic and Parameter. Statistic – numerical summary of sample data: p-hat or xbar Parameter – numerical summary of a population: µ for example.

497 views • 35 slides

A C T I O N P L A N

A C T I O N P L A N. Title of Project: Identification of problem and solution in statistic collection from line Ministries Organization : National Institute of statistic

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Content and the Scan Statistic for the Enron Data

Content and the Scan Statistic for the Enron Data. John M. Conroy Institute for Defense Analyses Center for Computing Sciences Bowie, MD. Citations and Coauthors.

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Statistică la învățătură-cls. a X-a

Statistică la învățătură-cls. a X-a

Presentation Transcript

sampling

Ch13 statistic (108)

EQT373 STATISTIC FOR ENGINEERS Design of Experiment (DOE)

Be More Than A Statistic

AP Statistics

Functions with R

Ch.9: Introduction to the t - statistic

Introduction to the t-statistic

Chapter 15

Statistic

STATISTIC FOR COMPUTING (CSNB293)

The CHI SQUARE Statistic

r-statistic performance in S2

To explore approaches for Statistic Data to serve Sustainable Urban Development though Case Study

STATISTICAL INFERENCE PART II POINT ESTIMATION

Network Statistic and Monitoring System

Bio-Statistic KUEU 3146 &amp; KBEB 3153 Bio-Statistic

CS 3343: Analysis of Algorithms

Introduction to the t Statistic

SAMPLING DISTRIBUTIONS

A C T I O N P L A N

Content and the Scan Statistic for the Enron Data

Bio-Statistic KUEU 3146 & KBEB 3153 Bio-Statistic