You should be able to show that A 0 is - 15,000 years. That means it will take 15,000 years for the lake to fill up. -15,000 present day depth at age =

Slides:



Advertisements
Similar presentations
Point/Slope Form Think what the formula is, then click on the name. Next Page.
Advertisements

Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. 1 ~ Curve Fitting ~ Least Squares Regression Chapter.
Lithospheric Plates The lithosphere can be defined thermally by an isotherm at the base of the lithosphere which should be around 1350 o C. Mantle rocks.
Tom Wilson, Department of Geology and Geography tom.h.wilson tom. Department of Geology and Geography West Virginia University Morgantown,
Section 4.2 Fitting Curves and Surfaces by Least Squares.
Stat 112: Lecture 15 Notes Finish Chapter 6: –Review on Checking Assumptions (Section ) –Outliers and Influential Points (Section 6.7) Homework.
Least Square Regression
The Islamic University of Gaza Faculty of Engineering Civil Engineering Department Numerical Analysis ECIV 3306 Chapter 17 Least Square Regression.
C82MCP Diploma Statistics School of Psychology University of Nottingham 1 Linear Regression and Linear Prediction Predicting the score on one variable.
Chapter 12 Section 1 Inference for Linear Regression.
Graph Linear Equations
Lesson 7.1.  In Chapter 1, you studied arithmetic sequences, which have a common difference between consecutive terms. This common difference is the.
Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. 1 ~ Curve Fitting ~ Least Squares Regression Chapter.
Log relationships, trig functions … & computer lab
Transforming to achieve linearity
Tom.h.wilson Department of Geology and Geography West Virginia University Morgantown, WV.
Basic Review continued tom.h.wilson Department of Geology and Geography West Virginia University Morgantown, WV.
Earthquakes, log relationships, trig functions tom.h.wilson Department of Geology and Geography West Virginia University Morgantown,
1 The graph of y = 2x + 3 is shown. You can see that the line’s y -intercept is 3, and the line’s slope m is 2 : m =2 = rise run = 2121 Slope-Intercept.
Chapter 11 Motion.
Example - if k = 1500 years/m calculate sediment age at depths of 1m, 2m and 5.3m. Repeat for k =3000 years/m 1m 2m 5.3m Age = 1500 years Age = 3000 years.
Calculus The Computational Method (mathematics) The Mineral growth in a hollow organ of the body, e.g. kidney stone (medical term)
The Examination of Residuals. Examination of Residuals The fitting of models to data is done using an iterative approach. The first step is to fit a simple.
Toward urgent forecasting of aftershock hazard: Simultaneous estimation of b-value of the Gutenberg-Richter ’ s law of the magnitude frequency and changing.
Direct Relationships. Relationships When a certain quantity (say temperature) has an effect on another quantity (say the volume of a gas), there is a.
Summarizing Bivariate Data
Go to Table of Content Single Variable Regression Farrokh Alemi, Ph.D. Kashif Haqqi M.D.
Basic Review tom.h.wilson Department of Geology and Geography West Virginia University Morgantown, WV.
CHAPTER 3 Model Fitting. Introduction Possible tasks when analyzing a collection of data points: Fitting a selected model type or types to the data Choosing.
Inference for Regression Simple Linear Regression IPS Chapter 10.1 © 2009 W.H. Freeman and Company.
Tom Wilson, Department of Geology and Geography Exponentials and logarithms – additional perspectives tom.h.wilson Department of Geology.
Tom Wilson, Department of Geology and Geography Environmental and Exploration Geophysics II tom.h.wilson Department of Geology.
Line of Best Fit 4.2 A. Goal Understand a scatter plot, and what makes a line a good fit to data.
Log relationships, trig functions, earthquakes & computer lab tom.h.wilson Department of Geology and Geography West Virginia University.
Correlation – Recap Correlation provides an estimate of how well change in ‘ x ’ causes change in ‘ y ’. The relationship has a magnitude (the r value)
Tom.h.wilson Department of Geology and Geography West Virginia University Morgantown, WV.
Geology Geomath Tom Wilson, Department of Geology and Geography tom.h.wilson Department of Geology and Geography West Virginia.
Basic Review tom.h.wilson Department of Geology and Geography West Virginia University Morgantown, WV.
Log relationships, trig functions, earthquakes & computer lab tom.h.wilson Department of Geology and Geography West Virginia University.
Basic Review continued tom.h.wilson Department of Geology and Geography West Virginia University Morgantown, WV.
The geologist’s use of math often turns out to be a periodic and necessary endeavor. As time goes by you may find yourself scratching your head pondering.
Pre-Algebra 11-2 Slope of a Line 11-2 Slope of a Line Pre-Algebra Homework & Learning Goal Homework & Learning Goal Lesson Presentation Lesson Presentation.
Basic Review - continued tom.h.wilson Department of Geology and Geography West Virginia University Morgantown, WV.
Lines of Best Fit When data show a correlation, you can estimate and draw a line of best fit that approximates a trend for a set of data and use it to.
Environmental and Exploration Geophysics I tom.h.wilson Department of Geology and Geography West Virginia University Morgantown,
Basic Review continued tom.h.wilson Department of Geology and Geography West Virginia University Morgantown, WV.
Basic Review tom.h.wilson Department of Geology and Geography West Virginia University Morgantown, WV.
The Computational Method (mathematics)
Basic Estimation Techniques
Lines of Best Fit When data show a correlation, you can estimate and draw a line of best fit that approximates a trend for a set of data and use it to.
Using Slope-Intercept Form
Basic Estimation Techniques
Linear and Non-Linear Functions
Geology Geomath Power Laws and Estimating the coefficients of linear, exponential, polynomial and logarithmic expressions tom.h.wilson
Geology Geomath Computer lab continued.
Geology Geomath Segment II Introduction tom.h.wilson
Geology Geomath Estimating the coefficients of linear, exponential, polynomial, logarithmic, and power law expressions tom.h.wilson
Geology Geomath Basic Review continued tom.h.wilson
No notecard for this quiz!!
Earthquakes, log relationships, trig functions
Linear regression Fitting a straight line to observations.
Chapter 2 - Recall that chapters 1 &2 have been posted on class web page Common relationships between geologic variables. What kind of mathematical model.
Geology Geomath Estimating the coefficients of linear, exponential, polynomial, logarithmic, and power law expressions tom.h.wilson
DSS-ESTIMATING COSTS Cost estimation is the process of estimating the relationship between costs and cost driver activities. We estimate costs for three.
Learning Targets Students will be able to: Compare linear, quadratic, and exponential models and given a set of data, decide which type of function models.
A. Draw a trend line. It will be easier to write an equation
Geology Geomath Estimating the coefficients of linear, exponential, polynomial, logarithmic, and power law expressions tom.h.wilson
Homework: pg. 276 #5, 6 5.) A. The relationship is strong, negative, and curved. The ratios are all Since the ratios are all the same, the exponential.
Objectives Compare linear, quadratic, and exponential models.
Presentation transcript:

You should be able to show that A 0 is - 15,000 years. That means it will take 15,000 years for the lake to fill up. -15,000 present day depth at age = 0.

These compaction effects make the age-depth relationship non-linear. The same interval of depth  D at large depths will include sediments deposited over a much longer period of time than will a shallower interval of the same thickness.

The relationship becomes non-linear. The line y=mx+b really isn’t a very good approximation of this age depth relationship. To characterize it more accurately we have to introduce non-linearity into the formulation. So let’s start looking at some non-linear functions. Compare the functions and (in red) What kind of equation is this?

The increase of temperature with depth beneath the earth’s surface is a non-linear process. Waltham presents the following table

We see that the variations of T with Depth are nearly linear in certain regions of the subsurface. In the upper 100 km the relationship Can we come up with an equation that will fit the variations of temperature with depth - for all depths? Let’s try a quadratic. From km the relationship provides a good approximation. works well.

Either way, the quadratic approximations do a much better job than the linear ones, but, there is still significant error in the estimate of T for a given depth. Can we do better?

The temperature variations rise non-linearly toward a maximum value (there is one bend in the curve), however, the quadratic equation (second order polynomial) does not do an adequate job of defining these variations with depth. Noting the number of bends in the curve might provide you with a good starting point. You could then increase the order to obtain further improvements.

Waltham offers the following 4 th order polynomial as a better estimate of temperature variations with depth.

Power Laws - A power law relationship relevant to geology describes the variations of ocean floor depth as a function of distance from a spreading ridge (x). What physical process do you think might be responsible for this pattern of seafloor subsidence away from the spreading ridges?

The porosity-depth relationship is often stated using a base different than 2. The base which is most often used is the natural base e and e equals In the geologic literature you will often see the porosity depth relationship written as  0 is the initial porosity, c is a compaction factor and z - the depth. Sometimes you will see such exponential functions written as In both cases, e=exp=

Waltham writes the porosity-depth relationship as Note that since z has units of kilometers (km) that c must have units of km -1 and must have units of km. Note that in the above form when z=, represents the depth at which the porosity drops to 1/e or of its initial value. In the formc is the reciprocal of that depth.

Observational data for earthquake magnitude (m) and frequency (N, number of earthquakes per year with magnitude greater than m) What would this plot look like if we plotted the log of N versus m?

This looks like a linear relationship. Recall the formula for a straight line?

The Gutenberg-Richter Relation -b is the slope and c is the intercept.

Finish reading Chapters 1 and 2 (pages 1 through 38) of Waltham Tuesday, 29 th - Hand in the basic review problems