Scatterplots & Correlation
Explain/define what a response variable is.
A response variable measures an outcome of a study.
Define extrapolation.
Extrapolation is the use of a regression line for prediction outside the interval of x values used to obtain the line.
How do you choose which model of transformation to use?
The model with the most randomly scattered residual plot.
__________ doesn't imply causation.
Correlation
You have data for many years on the average price of a barrel of oil and the average retail price of a gallon of unleaded regular gasoline. If you want to see how well the price of oil predicts the price of gas, then you should make a scatterplot with ____________ as the explanatory variable.
the price of oil
What are the three types of influential points?
High leverage, outlier, and both.
Name a transformation model.
Power, logarithm, or exponential.
Correlation & least-squares regression line are resistant.
True or False.
False. They are not resistant.
Page 172 #11 in your textbook.
For both groups of athletes, there is a moderately strong positive, linear association between height and weight; however, athletes who participate in the shot put, discus throw, and hammer throw tend to weigh more than other track and field athletes of the same height.
How do you interpret the slope?
For every 1 unit increase in explanatory variable, our model predicts an average increase/decrease of slope in response variable.
Curved relationships between two quantitative variables can sometimes be changed into linear relationships by _________________________.
by transforming one or both of the variables
Correlation (r) measures the ____________ and _____________ of the association between two quantitative variables x and y.
strength & direction
In a scatterplot of the average price of a barrel of oil and the average retail price of a gallon of gas, you expect to see:
a) very little association
b) a weak negative association
c) a strong negative association
d) a weak positive association
e) a strong positive association
e) a strong positive association
Page 205 #40 in your textbook.
The predicted average amount of gas usage when the average temperature was 46.4 F is predicted y = 1425 - 19.87(46.4) = 503.032 cubic feet. The residual = actual y - predicted y = 490 - 503.032 = -13.032. Interpretation: The actual mean amount of gas consumed in the month of march was 13.032 cubic feet less than predicted by the regression line with x = 46.4 F.
Page 231 #87 in your textbook.
334.97 grams is the predicted brain weight of Bigfoot.
Define what a regression line is.
Is a line that models how a response variable y changes as an explanatory variable x changes.