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Quick Start Expectations1. Fill in planner and HWRS
HW: p.100, #6-8, 19, 20, 25
2. Get a signature on HWRS
3. On desk: calculator, journal, HWRS, pencil, pen
4. Warm Up: next slide… back of HWRS
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Warm Up1). 5n – 9 = -16 + 6n 2.) 5x – 5 = 3x – 9
3.) 7 - 2x = x - 14
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A correlation of 1 means that there is a perfect linear relationship between two variables with a positive slope.
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-10.4
-0.4 -0.8 0.0
0.8
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Yes. These data points are tightly clustered in an upward sloping linear trend, so a linear model would give accurate predictions.
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The correlation coefficient is closest to r = 1.
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Yes. As a roller coaster drops, its speed increases. So, the longer the drop is, the faster the coaster will travel.Coasters with longer drops will be able to achieve greater speeds.
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The points are less tightly clustered in an upward sloping trend, so a linear model is going to be less reliable as a predictor of top speed for a given track length.
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The correlation coefficient is closest to r = 0.5.
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No. A coaster could have a long track, but height doesn’t change much. Without large drops, coasters would not achieve high speeds.
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The points are less tightly clustered than in question C, so a linear model will not be a reliable predictor of top speed for a given ride time.
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The correlation coefficient is closest to r = 0 … possibly 0.5
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No Outlier
NoNo
OutlierNo
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Answers vary…
(2800, 120)
(1300, 100)
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These data points are tightly clustered in a downward sloping linear trend, so a linear model would give accurate predictions of number of riders based on rider age.
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No.Although the data have a correlation, the variables do not have a causal relationship.
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4. Are any of the data points outliers? If so, estimate the coordinates of those points.
The correlation coefficient is closest to r = -1
(14, 45) (16, 60) (17, 70)(72, 2) (77, 2) (80, 1)
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Yes, it is possible to have a strong correlation coefficient that indicates a strong relationship even when there are a few outliers.