“ Building Strong “ Delivering Integrated, Sustainable, Water Resources Solutions Statistics 101 Robert C. Patev NAD Regional Technical Specialist (978)

Slides:



Advertisements
Similar presentations
Chapter 3 Properties of Random Variables
Advertisements

Hydrologic Statistics Reading: Chapter 11, Sections 12-1 and 12-2 of Applied Hydrology 04/04/2006.
Exam One Review Quiz Psy302 Quantitative Methods.
Hydrologic Statistics
Continuous Probability Distributions.  Experiments can lead to continuous responses i.e. values that do not have to be whole numbers. For example: height.
FREQUENCY ANALYSIS Basic Problem: To relate the magnitude of extreme events to their frequency of occurrence through the use of probability distributions.
Review of Basic Probability and Statistics
Probability Densities
Lesson Fourteen Interpreting Scores. Contents Five Questions about Test Scores 1. The general pattern of the set of scores  How do scores run or what.
1 Engineering Computation Part 6. 2 Probability density function.
Basic Probability and Stats Review
Probability and Statistics Review
A random variable that has the following pmf is said to be a binomial random variable with parameters n, p The Binomial random variable.
2. Random variables  Introduction  Distribution of a random variable  Distribution function properties  Discrete random variables  Point mass  Discrete.
Copyright (c) 2004 Brooks/Cole, a division of Thomson Learning, Inc. Chapter 4 Continuous Random Variables and Probability Distributions.
Lecture II-2: Probability Review
Normal and Sampling Distributions A normal distribution is uniquely determined by its mean, , and variance,  2 The random variable Z = (X-  /  is.
NIPRL Chapter 2. Random Variables 2.1 Discrete Random Variables 2.2 Continuous Random Variables 2.3 The Expectation of a Random Variable 2.4 The Variance.
Continuous Probability Distribution  A continuous random variables (RV) has infinitely many possible outcomes  Probability is conveyed for a range of.
4-1 Continuous Random Variables 4-2 Probability Distributions and Probability Density Functions Figure 4-1 Density function of a loading on a long,
Hydrologic Statistics
Quiz 2 Measures of central tendency Measures of variability.
Chapter 3 Basic Concepts in Statistics and Probability
PROBABILITY & STATISTICAL INFERENCE LECTURE 3 MSc in Computing (Data Analytics)
Further distributions
Statistics for Engineer Week II and Week III: Random Variables and Probability Distribution.
Moment Generating Functions
Review of Probability Concepts ECON 4550 Econometrics Memorial University of Newfoundland Adapted from Vera Tabakova’s notes SECOND.
Describing Behavior Chapter 4. Data Analysis Two basic types  Descriptive Summarizes and describes the nature and properties of the data  Inferential.
CPSC 531: Probability Review1 CPSC 531:Probability & Statistics: Review II Instructor: Anirban Mahanti Office: ICT 745
Review of Probability Concepts ECON 6002 Econometrics Memorial University of Newfoundland Adapted from Vera Tabakova’s notes.
ENGR 610 Applied Statistics Fall Week 3 Marshall University CITE Jack Smith.
Probability & Statistics I IE 254 Summer 1999 Chapter 4  Continuous Random Variables  What is the difference between a discrete & a continuous R.V.?
4-1 Continuous Random Variables 4-2 Probability Distributions and Probability Density Functions Figure 4-1 Density function of a loading on a long,
Introduction to Statistics Santosh Kumar Director (iCISA)
Random Variables (1) A random variable (also known as a stochastic variable), x, is a quantity such as strength, size, or weight, that depends upon a.
Exam 2: Rules Section 2.1 Bring a cheat sheet. One page 2 sides. Bring a calculator. Bring your book to use the tables in the back.
Describing Data Descriptive Statistics: Central Tendency and Variation.
BASIC STATISTICAL CONCEPTS Chapter Three. CHAPTER OBJECTIVES Scales of Measurement Measures of central tendency (mean, median, mode) Frequency distribution.
Probability and Distributions. Deterministic vs. Random Processes In deterministic processes, the outcome can be predicted exactly in advance Eg. Force.
Probability distributions
Review of Probability Concepts Prepared by Vera Tabakova, East Carolina University.
Section 5 – Expectation and Other Distribution Parameters.
Chapter 20 Statistical Considerations Lecture Slides The McGraw-Hill Companies © 2012.
Chapter 31Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012 John Wiley & Sons, Inc.
CHAPTER Discrete Models  G eneral distributions  C lassical: Binomial, Poisson, etc Continuous Models  G eneral distributions 
Psychology’s Statistics Appendix. Statistics Are a means to make data more meaningful Provide a method of organizing information so that it can be understood.
LESSON 5 - STATISTICS & RESEARCH STATISTICS – USE OF MATH TO ORGANIZE, SUMMARIZE, AND INTERPRET DATA.
Statistics -Continuous probability distribution 2013/11/18.
Random Variables By: 1.
MECH 373 Instrumentation and Measurements
Statistical Modelling
Review 1. Describing variables.
IEE 380 Review.
ETM 607 – Spreadsheet Simulations
Statistical Hydrology and Flood Frequency
Univariate Statistics
Chapter 5 Statistical Models in Simulation
Review of Probability Concepts
Moment Generating Functions
MEGN 537 – Probabilistic Biomechanics Ch.3 – Quantifying Uncertainty
Probability Review for Financial Engineers
Hydrologic Statistics
Continuous Probability Distributions Part 2
Continuous Probability Distributions Part 2
Continuous Probability Distributions Part 2
Chapter 3 : Random Variables
Chapter 2. Random Variables
Continuous Probability Distributions Part 2
1/2555 สมศักดิ์ ศิวดำรงพงศ์
Presentation transcript:

“ Building Strong “ Delivering Integrated, Sustainable, Water Resources Solutions Statistics 101 Robert C. Patev NAD Regional Technical Specialist (978)

“ Building Strong “ Delivering Integrated, Sustainable, Water Resources Solutions Random Variables What’s a random variable? –A quantity that can assume a specific value, or lie within a specified range of values, with a specified probability –A function defined on a sample space that assigns a specific probability to each value or range of values

“ Building Strong “ Delivering Integrated, Sustainable, Water Resources Solutions Discrete functions –Probability mass function, pmf Continuous functions –Probability density function, pdf –Cumulative density function, CDF Statistics

“ Building Strong “ Delivering Integrated, Sustainable, Water Resources Solutions Example of pmf Statistics

“ Building Strong “ Delivering Integrated, Sustainable, Water Resources Solutions Example of pdf t, yearspdf Statistics

“ Building Strong “ Delivering Integrated, Sustainable, Water Resources Solutions Example of CDF t, yearspdfcdf Statistics

“ Building Strong “ Delivering Integrated, Sustainable, Water Resources Solutions Statistics –Commonly used terms Mean Standard deviation or variance Coefficient of variation Median Skewness Correlation Distributions Types Statistics

“ Building Strong “ Delivering Integrated, Sustainable, Water Resources Solutions Mean –The average of a set of values –Excel command – AVERAGE Expected value –the centroid of the probability distribution on a random variable Mean and Expected Value

“ Building Strong “ Delivering Integrated, Sustainable, Water Resources Solutions Variance –The average squared deviation of values from the mean or expected value Variance

“ Building Strong “ Delivering Integrated, Sustainable, Water Resources Solutions Standard Deviation Standard Deviation,  –Spread of data about the mean value –A measure of the uncertainty, or “width” of a distribution –Square root of the variance –EXCEL command – STDEV or STDEVP

“ Building Strong “ Delivering Integrated, Sustainable, Water Resources Solutions Coefficient of Variation (COV) COV, V x –Standard deviation divided by expected value –A dimensionless value, often expressed as a percentage

“ Building Strong “ Delivering Integrated, Sustainable, Water Resources Solutions Median –e.g., median income, median age –Rank value –For odd n, value with rank of (n+1)/2 –For even n, average of value with rank n/2 or (n/2) + 1 –Used to limit extreme values –50th percentile –Excel command – MEDIAN Median

“ Building Strong “ Delivering Integrated, Sustainable, Water Resources Solutions A measure of the asymmetry of the probability distribution of a random variable Skewness x f(x) Right

“ Building Strong “ Delivering Integrated, Sustainable, Water Resources Solutions Correlation of Random Variables –Measures of the tendency for two random variables to assume values independently, or values with some relationship to each other –Range is from 1 to –1 1 is perfectly correlated positive -1 is perfectly correlated negative 0 is no correlation Correlation

“ Building Strong “ Delivering Integrated, Sustainable, Water Resources Solutions Random Variable A Random Variable B Negative Random Variable A Random Variable B Positive Correlation

“ Building Strong “ Delivering Integrated, Sustainable, Water Resources Solutions Examples of Distribution Types –Discrete Binomial Poisson –Continuous Normal Lognormal Exponential Weibull –Most Commonly Used »Uniform »Normal »Lognormal Statistics

“ Building Strong “ Delivering Integrated, Sustainable, Water Resources Solutions Standard Normal Standard Normal Variate –Yields a normal distribution with a mean of 0 and a standard deviation of 1 –N (0,1) or  –Useful in converting reliability index to probability of unsatisfactory performance –Excel command - NORMSDIST

“ Building Strong “ Delivering Integrated, Sustainable, Water Resources Solutions Standard Normal Distribution –Example Reliability index,  2.0 N(0,1) = P UP = 1 – = Standard Normal N (0,1)