'Quadratic model' presentation slideshows

Polynomials

1.23k views • 87 slides

Time series

Time series. Model assessment. Tourist arrivals to NZ. Period is quarterly. Draw graph of raw data. Write down the components of the time series in context. Identify and discuss any trend(s) in your series. The number of tourists arriving in NZ increases with time.

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Example 2

Example 2. The following table gives the mileage y, in miles per gallon, of a certain car at various speeds x (in miles per hour). a) Use a graphing utility to create a scatter plot of the data.

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Time Trends

Time Trends. Simplest time trend is a linear trend Examine National Population data set. How well does a linear model work? Did you examine the residuals plots?. Time Trends. Examine National Population data set.

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Chapter 10 Optimization Designs

Chapter 10 Optimization Designs. C. S. R. O. R. Optimization Designs. Focus : A Few Continuous Factors Output : Best Settings Reference : Box, Hunter & Hunter Chapter 15. Optimization Designs. C. S. R. O. 2 k with Center Points Central Composite Des. Box-Behnken Des. R.

582 views • 42 slides

Mortality Measurement Beyond Age 100

Mortality Measurement Beyond Age 100. Dr. Natalia S. Gavrilova, Ph.D. Dr. Leonid A. Gavrilov, Ph.D. Center on Aging NORC and The University of Chicago Chicago, Illinois, USA.

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Polynomial Regression and Transformations

Polynomial Regression and Transformations. STA 671 Summer 2008. Review. The estimated residuals e 1 ,…,e n provide the best method for checking the assumptions. Remember the residuals ε i ~ N(0, σ ). The estimated residuals should be close to that.

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Semiconductor Devices III

Semiconductor Devices III. Physics 355. Transistors in CPUs.

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Computing for Research I Spring 2014

Computing for Research I Spring 2014. Stata Graphics February 24. Primary Instructor: Elizabeth Garrett-Mayer. Basic syntax for commands. p refix: command varlist , options Examples: regress y x , level(90) by race: sum y x , detail t test y , by(x) unequal.

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Evaluating Theoretical Models

Evaluating Theoretical Models. R-squared represents the proportion of the variance in Y that is accounted for by the model.

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Evaluating Theoretical Models

Evaluating Theoretical Models. R-squared represents the proportion of the variance in Y that is accounted for by the model.

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Model Building

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5.1 Modeling Data with Quadratic Functions

5.1 Modeling Data with Quadratic Functions. Objectives: To identify quadratic functions and graphs and to model data with quadratic functions. Critical Thinking:. Investigate: As the side lengths of a square increase by 1, what happens to its perimeter and its area?

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Finding Quadratic Models

Section 7.7. Finding Quadratic Models. Example. The numbers of house calls paid by Medicare are shown in the table for various years.

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Notes

Notes. Extra class this Friday 1-2pm If you want to receive emails about the course (and are auditing) send me email. From last time. Steepest Descent: Start with guess Until converged: Find direction Choose step size Next guess is

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ALGEBRA 2 LESSON 6-1

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Notes Over 5.8

Notes Over 5.8. Writing a Quadratic Function in Vertex Form. Write a quadratic function in vertex form for the parabola. Notes Over 5.8. Writing a Quadratic Function in Vertex Form. Write a quadratic function in vertex form for the parabola. Notes Over 5.8.

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EXAMPLE 3

A study compared the speed x (in miles per hour) and the average fuel efficiency y (in miles per gallon) of cars. The results are shown in the table. Use a graphing calculator to find a model for the data. EXAMPLE 3. Use a quadratic model. Fuel Efficiency.

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F ACTORING A Q UADRATIC T RINOMIAL

F ACTORING A Q UADRATIC T RINOMIAL. To factor quadratic polynomials whose leading factor is not 1:. b = m q + p n. Find the factors of a ( m and n ). a = mn. Find the factors of c ( p and q ). a x 2 + b x + c = ( m x + p )( n x + q ). The sum of the outer and

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2.8 Exploring Data: Quadratic Models

2.8 Exploring Data: Quadratic Models. Students will classify scatter plots. Students will use scatter plots and a graphing utility to find quadratic models for data. Students will choose a model that best fits a set of data. Example 1.

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