Hypsometry of canyons and gullies in the central US Atlantic slope

Slides:



Advertisements
Similar presentations
E(X 2 ) = Var (X) = E(X 2 ) – [E(X)] 2 E(X) = The Mean and Variance of a Continuous Random Variable In order to calculate the mean or expected value of.
Advertisements

Normal Distribution Sampling and Probability. Properties of a Normal Distribution Mean = median = mode There are the same number of scores below and.
USING DECISION SUPPORT SYSTEM TECHNIQUE FOR HYDROLOGICAL RISK ASSESSMENT CASE OF OUED MEKERRA IN THE WESTERN OF ALGERIA M. A. Yahiaoui Université de Bechar.
6. Gray level enhancement Some of the simplest, yet most useful, image processing operations involve the adjustment of brightness, contrast or colour in.
Polygons – Concave and Convex Turning Point Quiz Copyright © 2010 Kelly Mott.
4. Convergence of random variables  Convergence in probability  Convergence in distribution  Convergence in quadratic mean  Properties  The law of.
Probability Distributions
I.1 ii.2 iii.3 iv.4 1+1=. i.1 ii.2 iii.3 iv.4 1+1=
Introduction to Educational Statistics
I.1 ii.2 iii.3 iv.4 1+1=. i.1 ii.2 iii.3 iv.4 1+1=
Chapter 2 CREATING AND USING FREQUENCY DISTRIBUTIONS.
Section Copyright © 2014, 2012, 2010 Pearson Education, Inc. Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series.
Frequency Distributions and Percentiles
UNIT FOUR/CHAPTER NINE “SAMPLING DISTRIBUTIONS”. (1) “Sampling Distribution of Sample Means” > When we take repeated samples and calculate from each one,
Terrain Mapping and Analysis
Introductory Statistics for Laboratorians dealing with High Throughput Data sets Centers for Disease Control.
MATHEMATICS CURRICULUM FOR SA I. DIVISION OF MARKS UNITMARKS NUMBER SYSTEMS11 ALGEBRA23 GEOMETRY17 TRIGONOMETRY22 STATISTICS17 TOTAL90 FIRST TERM.
Find the Perimeter and Area:
ROC 1.Medical decision making 2.Machine learning 3.Data mining research communities A technique for visualizing, organizing, selecting classifiers based.
A P STATISTICS LESSON 2 – 2 STANDARD NORMAL CALCULATIONS.
These are mathematical models for distributions.
1 Chapter 7 Sampling Distributions. 2 Chapter Outline  Selecting A Sample  Point Estimation  Introduction to Sampling Distributions  Sampling Distribution.
Chapter 3 – Graphical Displays of Univariate Data Math 22 Introductory Statistics.
 Two basic types Descriptive  Describes the nature and properties of the data  Helps to organize and summarize information Inferential  Used in testing.
Indifference Curves Locus of points representing different bundles of two goods, each of which yields the same level of total utility. It is a graphical.
1 Chi-square Test Dr. T. T. Kachwala. Using the Chi-Square Test 2 The following are the two Applications: 1. Chi square as a test of Independence 2.Chi.
3.4 Slope and Rate of Change Math, Statistics & Physics 1.
4.3 Probability Distributions of Continuous Random Variables: For any continuous r. v. X, there exists a function f(x), called the density function of.
ΟΡΓΑΝΩΣΗ ΚΑΙ ΔΙΟΙΚΗΣΗ ΕΠΙΧΕΙΡΗΣΕΩΝ 3 Ο ΜΑΘΗΜΑ. ΟΙ ΜΕΓΑΛΕΣ ΕΠΙΧΕΙΡΗΣΕΙΣ Η δημιουργία μεγάλων επιχειρήσεων είναι ένα από τα χαρακτηριστικά του 20 ου αιώνα.
MANDIBULAR MOLARS. General Features The three mandibular molars resemble each other in morphology two well-developed roots ; Mesial and Distal In mandibular.
Descriptive Statistics
The Normal distribution
Normal distributions x x
Different Types of Data
Active Learning Lecture Slides
Lecture Slides Essentials of Statistics 5th Edition
11. The Normal distributions
Section 3.4 Day 2.
Statistical Intervals Based on a Single Sample
Basic Estimation Techniques
4.3 Probability Distributions of Continuous Random Variables:
Review of Descriptive Statistics
The Standard Deviation as a Ruler and the Normal Model
APPROACHES TO QUANTITATIVE DATA ANALYSIS
9 Deflection of Beams.
Sampling Distributions and The Central Limit Theorem
Notes 13-1 Basic Statistics
Elementary Statistics: Picturing The World
Test for Normal Distribution
Basic Estimation Techniques
Neil C. Mitchell, SEAES, The University of Manchester, UK
Stochastic Hydrology Hydrological Frequency Analysis (II) LMRD-based GOF tests Prof. Ke-Sheng Cheng Department of Bioenvironmental Systems Engineering.
Theme 5 Standard Deviations and Distributions
Warm-up We are going to collect some data and determine if it is “normal” Roll each pair of dice 10 times and record the SUM of the two digits in your.
NORMAL PROBABILITY DISTRIBUTIONS
Bar charts and Histograms
Major Scales at the nut C F G C Box A G C D G VII D G A D F Bb C F X A
ОПЕРАТИВНА ПРОГРАМА “ИНОВАЦИИ И КОНКУРЕНТОСПОСОБНОСТ“ „Подобряване на производствения капацитет в МСП“
Area of a rectangle Tuesday, 05 February 2019 Definition:
4.3 Probability Distributions of Continuous Random Variables:
QUANTITATIVE ANALYSIS OF SUBMARINE CHANNEL NETWORKS
Solving Equations 3x+7 –7 13 –7 =.
Are You a Data Detective?
Binomial Distribution: Inequalities for cumulative probabilities
Graphing Rational Functions
Measurement and Geometry 25
Making Use of Associations Tests
Introduction to Sampling Distributions
Sampling Distributions and The Central Limit Theorem
Biostatistics Lecture (2).
Presentation transcript:

Hypsometry of canyons and gullies in the central US Atlantic slope Dina Vachtman and Neil C. Mitchell, The University of Manchester, UK Hypsometric curves represent the distribution of area with elevation in landscapea. Such curves calculated for the Atlantic slope are treated as cumulative probability functions so that gross canyon shapes can be parameterised in terms of simple statistics (skewness, kurtosis and integral). Based on such statistical attributes, we have identified four hypsometric curve types: toeless concave, S-shaped, flattened-J-shaped and convex. Toeless concave S-shaped J-shaped Convex These types turn out to correspond remarkably well to network geometries in plan-view. Narrow networks (straight trellis patterns - types I, II) correspond to toeless concave and S-shaped hypsometric curves. In contrast, networks with smaller aspect ratios and more highly branched (types III, IV) correspond with flattened-J-shaped and convex curves. These linkages have been surprising and may suggest an underlying control of erosion process on large-scale form, presently being investigated.