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Answers Included!. Questions 8 & 10. Training New Employees. Relax! We already d id all the work for you. 1 st and only edition. Presenter Name Presentation Date. Mitchell P2 8-5 Modelling With Combined Functions. Question 8. . Analyzing the Question. .

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training new employees

Answers Included!

Questions 8 & 10

Training New Employees

Relax! We already

did all the work for you.

1st and only edition

Presenter Name

Presentation Date

Mitchell P2 8-5

Modelling With

Combined Functions

slide3

Analyzing the Question

.

Take away irrelevant/unimportant information

slide4

Preparing to Graph

  • Separate each part of skier’s run into separate instances
  • Graph each one individually before combining them all
  • Make height of hill 60m, as it is the easiest number to work with
slide6

Meaning of the Graph:

Skier is going downhill

Skier riding up chairlift

Skier waiting for chairlift

slide7

Algebraic Expressions

  • Unfortunately, we don’t know any algebraic expressions that result in such a graph
  • Instead, make 3 different equations for each interval!
slide8

Algebraic Expressions:

Negative Slope of 1m/s

Hill height is 60m

Positive Slope of .5m/s

Crosses t – intercept at 120

Constant height of 0

slide10

Analyzing the Question

Requires - Scatter Plot - Graphing Calculator

- Thinking Cap

slide11

Scatter Plot

  • Nothing really to it, just plot the points on a graph with a reasonable scale and axis titles
slide12

Regression

  • As you can see, the imaginary curve of best fit does not resemble cubic or linear regressions
  • Therefore, comparing logarithmic and quadratic regression would be the best approach here
slide14

Outlier in 1966

  • As you can tell from the data, in 1966 there were only 6 hockey teams
  • This information functions as an outlier negatively affects the curve of best fit
  • Removing the outlier from your data can make a very noticeable impact on regression

N(t) without outlier

N(t) with outlier

slide15

Outlier in 1966 Cont’d

N(t) without outlier

N(t) with outlier