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Do Now: 1.3, 4.3 Practice 1.) Solve the equation in the complex number system. 2.) Graph using its vertex and intercepts. Determine the domain and range.

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Presentation on theme: "Do Now: 1.3, 4.3 Practice 1.) Solve the equation in the complex number system. 2.) Graph using its vertex and intercepts. Determine the domain and range."— Presentation transcript:

1 Do Now: 1.3, 4.3 Practice 1.) Solve the equation in the complex number system. 2.) Graph using its vertex and intercepts. Determine the domain and range and where the function increases and decreases.

2 Academy Algebra II/Trig 4.4: Quadratic Models HW: p.311 (8, 12, 19, 28) Quiz 1.3, 4.3, 4.4: Wednesday

3 p.306 example 2 A farmer has 2000 yards of fence to enclose a rectangular filed. What are the dimensions of the rectangle that encloses the most area?

4 p.307 example 3: A projectile is fired from a cliff 500 ft above the water at an inclination of 45 o to the horizontal, with a velocity of 400 feet per second. The height h of the projectile is given by, where x is the horizontal distance of the projectile from the base of the cliff. (a)Find the maximum height of the projectile. (b) How far from the base of the cliff will the projectile strike the water?

5 p.307 example 3: (a)Find the maximum height of the projectile. (b) How far from the base of the cliff will the projectile strike the water?

6 Regression Example: The price per share of a stock is given in the table above. (a) Calculate a regression equation for the data. (b) Use the equation to predict the price in week 7.

7 Regression Example: Data matrix editor  open a data file. F1  clear editor (if you need to delete all numbers). Input data, then setup plots by pressing F2, then F1 for define. View graph  press graph, zoomdata. Now that you have determine the graph is a parabola, we can find the quadratic regression. Go back to data. F5 (calc)  calculation type is quadreg  define x and y, store to y1(x).

8 Regression Example: The price per share of a stock is given in the table above. (a) Calculate a regression equation for the data. (b) Use the equation to predict the price in week 7.


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