Linear Regression Quiz
. Which of the following is a reason regression models are helpful? Enables us to make
predictions of the models.
. Which of the following would be a good fit for a linear regression? Linear relationship
between the horsepower of a motorboat engine and its price.
. The scatter plot contains a linear regression comparing the horsepower to price of one
manufacturer's outboard motorboat engines. What would you expect a 20 HP engine to
cost? $4300 |
. The scatter plot contains a linear regression comparing the horsepower to price of one
manufacturer's outboard motorboat engines. What would you expect a 45 HP engine to
cost? $8400
. When you were using the scatter plot, how did you estimate the price of 20 HP and 45 HP
engines? You interpolated the price of the 20 HP engine and extrapolated the price
of the 45 HP engine.
. The linear correlation between the horsepower of an engine and its price is 0.99. How
would you describe this relationship? Strong positive
Understanding Linear Regressions Quiz
. Regression lines enable us to predict the value of the variable on the y-axis from the value
of the variable on the x-axis because the value of the variable on the x-axis causes the
value of the variable on the y-axis. False
. The distance between each datapoint and the regression line is referred to as the?
Residual
. Looking at the scatterplot which compares the horsepower of a manufacturer's motorboat
engine to its price, we can see that the 15 HP engine has a price of $3,680 when we would
expect the price to be $3,462. What is the residual? $218
The equation of the regression line predicting the price of an engine from its horsepower
can be written in slope-intercept form as y = 167.45x + 950.16. What is the expected value
of a 25-horsepower engine? Round your answer to the nearest dollar. Y=1677.45 (25) +
950.16 = 5136
. If the residual at 25 HP is equal to -$386, then the expected price is? use the formula
residual = observed value minus expected value? Is $386 above the observed
price.
, The Correlation Coefficient Quiz Mod 6
. A marketing team at a major car manufacturer needs to make a recommendation to the
manufacturer's engineering team on where to focus on improving a car model. The
marketing team is considering a recommendation to reduce weight to improve miles per
gallon. If the marketing team performs a correlation analysis and determines that r = -
0.72, what does this mean? There is negative correlation.
What does r = -0.72 tell us about the strength of the relationship between weight and
miles per gallon? The correlation is moderate.
. Excited that it has found a moderate (almost strong) relationship between weight and
miles per gallon, the marketing team next compares miles per gallon to MSRP and
determines that r = -0.62, what does this suggest about the relationship? Moderate
negative
. The marketing team is surprised that the correlation between miles per gallon (a good
thing) and MSRP is negative. Which of the following is a likely explanation? There is
another variable, which is negatively correlated with miles per gallon, that has a
greater influence on MSRP.
. Next, the marketing team compares the correlation coefficient of the time it takes to
accelerate from 0-60 mph to MSRP and determines that r =-0.77. What does this say
about the relationship between acceleration and MSRP? (Note that a lower time to go
from 0 to 60 mph means a faster acceleration.) Moderate negative
. Based on the findings, the marketing team concludes that faster acceleration is correlated
with higher willingness to pay and lower miles per gallon. If the team believes the
manufacturer's car would be best targeted towards an economical segment of the market,
what recommendation should it make to engineering? Focus on increasing miles per
gallon, potentially by reducing weight which may result in better gas mileage.
. Which of the following is a reason regression models are helpful? Enables us to make
predictions of the models.
. Which of the following would be a good fit for a linear regression? Linear relationship
between the horsepower of a motorboat engine and its price.
. The scatter plot contains a linear regression comparing the horsepower to price of one
manufacturer's outboard motorboat engines. What would you expect a 20 HP engine to
cost? $4300 |
. The scatter plot contains a linear regression comparing the horsepower to price of one
manufacturer's outboard motorboat engines. What would you expect a 45 HP engine to
cost? $8400
. When you were using the scatter plot, how did you estimate the price of 20 HP and 45 HP
engines? You interpolated the price of the 20 HP engine and extrapolated the price
of the 45 HP engine.
. The linear correlation between the horsepower of an engine and its price is 0.99. How
would you describe this relationship? Strong positive
Understanding Linear Regressions Quiz
. Regression lines enable us to predict the value of the variable on the y-axis from the value
of the variable on the x-axis because the value of the variable on the x-axis causes the
value of the variable on the y-axis. False
. The distance between each datapoint and the regression line is referred to as the?
Residual
. Looking at the scatterplot which compares the horsepower of a manufacturer's motorboat
engine to its price, we can see that the 15 HP engine has a price of $3,680 when we would
expect the price to be $3,462. What is the residual? $218
The equation of the regression line predicting the price of an engine from its horsepower
can be written in slope-intercept form as y = 167.45x + 950.16. What is the expected value
of a 25-horsepower engine? Round your answer to the nearest dollar. Y=1677.45 (25) +
950.16 = 5136
. If the residual at 25 HP is equal to -$386, then the expected price is? use the formula
residual = observed value minus expected value? Is $386 above the observed
price.
, The Correlation Coefficient Quiz Mod 6
. A marketing team at a major car manufacturer needs to make a recommendation to the
manufacturer's engineering team on where to focus on improving a car model. The
marketing team is considering a recommendation to reduce weight to improve miles per
gallon. If the marketing team performs a correlation analysis and determines that r = -
0.72, what does this mean? There is negative correlation.
What does r = -0.72 tell us about the strength of the relationship between weight and
miles per gallon? The correlation is moderate.
. Excited that it has found a moderate (almost strong) relationship between weight and
miles per gallon, the marketing team next compares miles per gallon to MSRP and
determines that r = -0.62, what does this suggest about the relationship? Moderate
negative
. The marketing team is surprised that the correlation between miles per gallon (a good
thing) and MSRP is negative. Which of the following is a likely explanation? There is
another variable, which is negatively correlated with miles per gallon, that has a
greater influence on MSRP.
. Next, the marketing team compares the correlation coefficient of the time it takes to
accelerate from 0-60 mph to MSRP and determines that r =-0.77. What does this say
about the relationship between acceleration and MSRP? (Note that a lower time to go
from 0 to 60 mph means a faster acceleration.) Moderate negative
. Based on the findings, the marketing team concludes that faster acceleration is correlated
with higher willingness to pay and lower miles per gallon. If the team believes the
manufacturer's car would be best targeted towards an economical segment of the market,
what recommendation should it make to engineering? Focus on increasing miles per
gallon, potentially by reducing weight which may result in better gas mileage.
