A graph that involves many different data points and compares two quantitative variables
What is a Scatterplot?
100
The correct form of the equation of a regression line
What is y = a + bx?
100
The equation y = -41.43 + 0.1249x describes the number of manatees killed, versus yearly boat registrations (in thousands).
This number represents the number of manatees killed when there were 716,000 powerboats registered (use 716)
What is 48 manatees?
100
As study time increases, test scores increase.
This is an example of this type of correlation
What is positive correlation?
100
This is an example of a moderate-strength correlation
What is any answer between .4 and .6 or -.4 and -.6?
200
A variable that measures the outcome of a study
What is a response variable?
200
This number always represents the amount which y changes when x increases
What is the slope?
200
Your least squares regression line predicts a y value of 25, but during your study you observe a value of 20.
This number represents the residual
What is -5?
200
As an NFL football player's weight increases, their sprinting time decreases.
This is an example of this type of correlation.
What is negative correlation?
200
Someone says " There is a strong correlation between the number of firefighters at a fire and the amount of damage the fire does. So sending more firefighters just causes more damage" This reasoning is wrong because...
What is that more serious fires require more firefighters, so seriousness of a fire is a lurking variable?
300
The variable that helps explain or influences change in another variable
What is the explanatory variable?
300
The use of a regression line for predicting outside the range of values used to obtain the regression line equation
What is Extrapolation?
300
This is the Scatterplot of (2, 6), (4,26), (5,50),(6,100) and (8,380) and the type of relationship between x and y
See graph; What is exponential relationship
300
The correlation between people who wear blue to work and the amount of time wasted at work is 0.33
Describe what is wrong with this statement.
What is that wearing blue is not quantitative, so it can not be measured, therefore we can not calculate a correlation
300
To test whether data increases exponentially, we check rations between consecutive y values to see if they are about the same. The four ratios for the data (10,32), (20, 50), (30, 71), (40, 113), (50, 162) rounded to the nearest 10 are....
1.56, 1.42, 1.59, 1.43
400
This measures the direction and strength between two quantitative variables
What is correlation?
400
Type of regression for which a linear equivalent is a graph of x versus Log (y)
What is exponential regression
400
This is the equation that relates x and y for the data (2, 6), (4,26), (5,50),(6,100) and (8,380)
What is y = 1.57(1.99^x)
400
This is the difference between r = -.2 and r = .99
What is that r=-.2 is a very weak negative correlation and r=.99 is a very strong positive correlation
400
Match the statements with their respective correlation:
1)A Weak, negative correlation
2)An impossible correlation
3)The correlation between hours worked and your salary if you make $10 per hour
4)A moderate positive correlation
a)r=.53 b)r=-0.12 c)r = 1 d)r = -2.2
What is 1)b 2)d 3)c 4)a
500
The difference between an observed value and the value predicted by the regression line
What is a residual?
500
A plot of Log(y) versus Log (x) has LSRL y = 1.5 + 0.3 x
The equation of the power regression model is...
What is y = (10^1.5)x^.3 =31.6x^.3
500
This is the scatterplot of the linear equivalent of the data (2, 6), (4,26), (5,50),(6,100) and (8,380)
See graph
500
Your friend finished their Statistics homework and you offer to check it. You notice one answer reads, "The correlation between drive times to work and money spent on gas is 1.05"
Describe what you would tell this friend
What is that 1.05 is an impossible correlation answer?
500
Create a residual plot for the data (2, 6), (4,26), (5,50),(6,100) and (8,380). What does this plot suggest about the linearity of the data?
See Graph. Because of the curved pattern in the residual plot, a LSRL is not the appropriate model.