- 54 Views
- Uploaded on
- Presentation posted in: General

Applications

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

- Da Brat
- Shawntae Harris
- Ke$ha
- Ashley Tisdale
- Rebecca Black

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

- average score
- median score
- standard deviation
- mean score

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

- .
- .
- .
- .

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

- )
- )
- )
- )

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

- -136
- 400
- 536

is regressed with least squares regression to a straight line to give y=-116+32.6x. The observed value of y at x=20 is

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

- -136
- 400
- 536

is regressed with least squares regression to a straight line to give y=-116+32.6x. The predicted value of y at x=20 is

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

- -136
- 400
- 536

is regressed with least squares regression to a straight line to give y=-116+32.6x. The residual of y at x=20 is

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

When transforming the data to find the constants of the regression model y=aebx to best fit (x1,y1), (x2,y2),……….. (xn,yn), the sum of the square of the residuals that is minimized is

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

for concrete in compression, where

is the stress and

is the strain, the model is rewritten as

- )
- )
- )
- )

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

- none of data points fall exactly on the straight line
- the slope of the straight line is zero
- all the data points fall on the straight line

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

The case where the coefficient of determination for regression of n data pairs to a general straight line is zero if the straight line model

- has zero intercept
- has zero slope
- has negative slope
- has equal value for intercept and the slope

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

- -1 and 1
- 0 and 1
- -2 and 2

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

- -1 and 1
- 0 and 1
- -2 and 2

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

- -0.25
- -0.50
- 0.00
- 0.25
- 0.50

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

- Very strong
- Strong
- Moderate
- Weak
- Very Weak

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

If the coefficient of determination for a regression line is 0.81, then the percentage amount of the original uncertainty in the data explained by the regression model is

- 9
- 19
- 81

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

- 85
- 90
- 95
- 100

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

- 4.0
- 7.0
- 7.5
- 10.0

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

- 27.480
- 28.956
- 32.625
- 40.000

is regressed with least squares regression to y=a1x. The value of a1 most nearly is

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

A scientist finds that regressing y vs x data given below to straight-line y=a0+a1xresults in the coefficient of determination, r2 for the straight-line model to be zero.

- -2.444
- 2.000
- 6.889
- 34.00

The missing value for y at x=17 most nearly is

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

A scientist finds that regressing y vs x data given below to straight-line y=a0+a1xresults in the coefficient of determination, r2 for the straight-line model to be one.

- -2.444
- 2.000
- 6.889
- 34.00

The missing value for y at x=17 most nearly is

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate

- -47.9
- -47.4
- 15.6
- 28.2

http://numericalmethods.eng.usf.edu

Transforming Numerical Methods Education for the STEM Undergraduate