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Chapter 1: Modeling with Functions and Regression Equations

In this chapter, we learned about using models and equations to graph and solve real world situations and problems. This way we could have a better understand of the information you are trying to find by using numerical, algebraic, and graphical models. There are many different types of functions through out this chapter that we had to graph. One of those that we had to graph was linear regression where the graph would display correction coefficient (r) or coefficient of determination (R^{2).
To solve my problem you first have to set your calculator to find correlation coefficient. To do this you have to:}

^{1. Push [2nd] then ["O"] since you want CATALOG.
2. Scroll down until you get to [DiagnosticOn].}

^{3. Hit [ENTER] twice.}

^{Now you have set up the correlation coefficient.
Next, you have set your table and graphs for finding the linear regression.
1. Push [STAT] and pick [EDIT].
2. Now you see two vertical columns and so I input my x values into }^{L1 and y values into L2 .
3. Next, go to [STAT], then hit right to get [CALC] and hit enter.}

^{4. Select [LinReg AX+B] and push enter.
5. Now you press [2nd] and L1 [,] then you repeat the same process for L2.}

^{6. After, you press [VARS] and move to the right to get [Y-VARS] and select [FUNCTION].
7. You will have a screen displayed with y=, a=, b=, }R^{2=.} ^{and r=.}

^{8. Then, you push [Enter] and [GRAPH].
9. Push [ZOOM] and then push [ZOOMSTAT].
} 10. Finally, you can push [Y=] to see your equation.

In conclusion, my predictions were incorrect because my calculations were no where close to the actual prices. The regression equation doesn't model the data very well since the regression line is no where close or fit my data. The correlation coefficient is r= .9319902374 and the coefficient of determination is R^{2}= .8686058026.

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