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Seminar_2_Statdisk_rmorel01_Seminar_2_Statdisk_Assignment_Rob_Morell
Course: FLASH 101, Fall 2011School: Baker MI
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Word Count: 253
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job Excellent Robthis is laid out beautifully. You took a wrong turn to find the best predictive value thoughsee below. It is always good to provide a nice concise summary statement in problems such as this: The best predicted breaking distance for a 4,000lb car = 136.781 feet. See below for other feedback, esp for the last two questions. Score = 5 1 = 4 Seminar 2 Statdisk Assignment Name: Rob Morell 1) 2. Using...
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job Excellent Robthis is laid out beautifully. You took a wrong turn to find the best
predictive value thoughsee below. It is always good to provide a nice concise summary
statement in problems such as this: The best predicted breaking distance for a 4,000lb car
= 136.781 feet. See below for other feedback, esp for the last two questions.
Score = 5 1 = 4
Seminar 2 Statdisk Assignment
Name: Rob Morell
1)
2. Using the prediction procedure, find the best predicted braking distance for a car that weighs
4000 lbs.
For #2, first we need to find r the linear correlation coefficient for the data set.
r for the weight and braking distances = -0.0867286
Next we need to find the critical value, so refer to Table A-6. We have paired data and n =
32.
Critical value = 0.3493697
Does the linear for correlation the data support a linear correlation?
The absolute value of r = -0.0867286 is less than the critical value r = 0.3493697 There is
not a linear correlation between the weight and braking distance.
If there is a linear correlation, then we input the necessary data into the prediction
equation to find the best predicted value for braking distance for a vehicle weighing 4000
lbs. yhat = b0 + b1x
If there is not a linear correlation, then we use the sample mean for y as the best
predicted braking distance. You'll need to calculate that.
3. Just for practice, find the regression equation, letting the first variable be the predictor (x)
variable. yhat = b0 + b1x
Y = b0 + b1x
y = 141.244 + -0.0012379*4000
y=141.244 + -4.9516
y=141.244 - 4.9516= 136.2924
y=136.2924
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