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Intro to Stat Linear Regression review

Total questions: 48

Worksheet time: 2hrs 9mins

Name
Class
Date
1.
Describe the correlation in the graph shown.
a)
Strong Negative
b)
Strong Positive
c)
Weak Negative
d)
Weak Positive
2.
The equation of the least squares regression line is y (hat) = 1.3 + 0.73x.  What is the residual for the point (4,7)?
a)
2.78
b)
3.00
c)
4.00
d)
4.22
3.
A perfect positive correlation has a correlation coefficient of ____. 
a)
1
b)
-1
c)
0
4.
The table represents a used car salesman's monthly salary including commission made on the sale of cars.  What is the slope and what does it represent?
a)
The slope is $850/car and it represents the commission per car sold.
b)
The slope is $425/car and it represents the commission per car sold.
c)
The slope is $1500 and it represents the monthly salary before commission.
d)
The slope is $850 and it represents the monthly salary before commission.
5.
The graph represents the height of a burning candle.  What is the meaning of the slope?
a)
the time it takes to burn the entire candle
b)
the change in the height of the candle each hour it is burning
c)
the different heights of the candle
d)
the original height of the candle
6.
r = 0.3 indicates what kind of relationship?
a)
Strong positive 
b)
Weak positive
c)
Strong negative
d)
Weak negative 
7.
r = -0.89 indicates what kind of relationship?
a)
Strong positive 
b)
Weak positive 
c)
Strong negative 
d)
Weak negative 
8.
r2 represents:
a)
Coefficient of Delegation
b)
Correlation Coefficient
c)
Correlation of Determination
d)
Coefficient of Determination
9.
The _________________ ____________________ measures the strength of the relationship between 2 variables.
a)
Correlation Coefficient
b)
Causation
c)
Independent Variable
10.
The correlation coefficient, r, is always between ___ and ___.
a)
0 and 1
b)
-1 and 1 
c)
-1 and 0
11.
Determine the Correlation Coefficient and decide whether the relationship between the variables is weak, moderate, or strong.
a)
-0.19 weak
b)
-0.19 moderate
c)
0.04 weak
d)
0.04 strong
12.
Find the equation of the line of best fit for this table.
a)
y(hat) = 6.47 - 0.18x 
b)
y(hat) = -0.18 + 6.47x 
c)
y(hat) = -0.19 + 0.04x 
d)
y(hat) = -0.18x - 0.19
13.
How do you calculate a residual?
a)
Actual - Predicted
b)
Predicted - Actual
14.
What would the correlation between elevation and temperature be?
a)
none
b)
cannot be determined
c)
positive correlation
d)
negative correlation
15.

Use the data to calculate the prediction line and use the equation to predict the number of prom tickets sold on day 6.

a)

y(hat) = 4.54 + 27.31x ; prom tickets are estimated to be about 58.93

b)

y(hat) = 27.31 + 4.54x ; prom tickets are estimated to be about 54.55

c)

y(hat) = .97 + 4.54x ; prom tickets are expected to be about 41.24

16.

r2 = 0.83 means

a)

My data is very accurate. We have a 17% uncertainty.

b)

My data is 17% correct.

c)

83% of the variability in y can be explained by x. Only 17% is unexplained.

d)

My data is very accurate. I have 17% accuracy.

17.

The coefficient of determination is a percentage "r2" such that:

a)

0 ≤ r2 ≤ 1

b)

-1 < r2 < 1

c)

0 < r2 < 2

d)

-1 < r2 <0

18.

r2 = 0.24 means

a)

76% of the variability in y is unexplained. This is not good.

b)

My data is 24% correct.

c)

My data is flawed. I have 24% uncertainty.

d)

My data is very accurate. I have 76% accuracy.

19.
What does a correlation coefficient of
r = 0.99999 mean?
a)
strong positive correlation
b)
strong negative correlation
c)
weak positive correlation
d)
weak negative correlation
20.
What type of association does this graph have?
a)
positive 
b)
negative
c)
none
d)
all of the above
21.
What type of correlation would the variable have?
The outside temperature and the amount of layers you wear. 
a)
Positive correlation
b)
Negative correlation
c)
No correlation
22.
Data was collected on the weight of a male  laboratory rat for the first 25 weeks after its birth. The linear regression equation is 
y= 40x+100, where x is number of weeks and y is weight in grams. 
What does the y-intercept mean in context of the problem?
a)
The predicted weight of the rat in year 0. 
b)
The predicted weight of the rat at birth. 
c)
The current weight of the rat. 
d)
The average increase in the rat's weight. 
23.
The linear regression equation is y = 61.93x - 1.79.  Use the equation to predict how far this person will travel after 10 hours of driving.
a)
10 miles
b)
617.5 miles
c)
0.19 miles
d)
500 miles
24.
The linear regression equation is y = 61.93x - 1.79.  According to the model, the slope can be interpreted as:
a)
After 0 hours of driving, they went 61.93 miles.
b)
They drove at a speed of 61.93 miles per hour.
c)
They drove 61.93 miles total.
d)
They drove 61.93 hours total.
25.

A restaurant sells pizza for the prices in the data table. Calculate the linear regression equation of the data.

a)

y = 12 + 1.5x

b)

y = 12x + 1.5

c)

y = 0.67x - 8

d)

y = -8x + 0.67

26.
The scatter plot shows the relationship between the number of chapters and the total number of pages for several books.  Use the trend line to predict how many chapters would be in a book with 180 pages. 
a)
12 chapters
b)
15 chapters
c)
18 chapters
d)
21 chapters
27.

Estimate the correlation coefficient for this scatterplot.

a)

r = 1.2

b)

r = 0.89

c)

r = 0

d)

r = -0.89

28.

The residual plots from five different least squares regression lines are shown below. Which of the plots shows the strongest evidence that its regression line is an appropriate model for the data and is consistent with the assumptions required for inference for regression?

a)
b)
c)
d)
e)
29.

The equation of the least squares regression line for a set of data is y=0.68+1.21x. What is the residual for the point (3, 4)?

a)

-0.31

b)

-0.68

c)

-1.52

d)

-3.63

e)

-4.31

30.
Which scatter plot shows no relationship?
a)
Graph A
b)
Graph B
c)
Graph C
d)
Graph D
31.

What is the slope of this prediction equation?

a)

1344

b)

19

c)

-19

d)

-19x

32.

What is the y-intercept of the prediction equation?

a)

-149

b)

149

c)

4.4

d)

4.4x

33.

predicted math grade = 65 + 2.56(study hours)


What does the slope mean in context?

a)

The model predicts an increase of 2.56 points in the math grade per hour studied, on average.

b)

The model predicts an increase of 65 points in the math grade per hour studied, on average.

c)

The model predicts an increase of 2.56 study hours per math grade, on average.

d)

The model predicts an increase of 2.56 study hours, on average.

34.

predicted cost = 3 + 4.1(length of movie in hours)


According to this prediction model, how much do you expect to pay for a movie if the movie is 1.5 hours long?

a)

$3

b)

$7.10

c)

$9.15

d)

$4.10

35.

which value of x has the greatest residual?

a)

5

b)

2

c)

1

d)

3

36.
Shown is a residual plot. Would a linear regression model of the data be most appropriate?
a)
YES
b)
NO
37.
What should a residual plot look like?
a)
Distinct Pattern
b)
Curve
c)
Random
38.
After performing analyses on a set of data, Mrs. Schoeneck examined the scatter plot of the residual values for each analysis. Which scatter plot indicated the best linear fit for the data?
a)
A
b)
B
c)
C
39.

The scatter plot shows the number coffee shops in different cities and the number of violent crimes. Which of the following is NOT true?

a)

A) As the number of coffee shops increase, violent crimes appears to increase.

b)

B) The line of best fit (regression line) shows a positive correlation

c)

C) The data has a positive correlation coefficient

d)

D) An increase in coffee shops causes an increase in violent crimes

40.
The correlation coefficient is a number "r" such that: 
a)
-1<r<1
b)
-1>r>1
c)
-1≤r≤1
d)
-1≥r≤1
41.

The results of a linear regression are shown.

Which phrase best describes the relationship between x and y?

a)

strong negative correlation

b)

strong positive correlation

c)

weak negative correlation

d)

weak positive correlation

42.

Which graph most clearly shows a negative correlation between the x- and y−values?

a)
b)
c)
43.

Which graph most clearly shows a no correlation between the x- and y−values?

a)
b)
c)
44.

What does a correlation coefficient of r=−0.01

imply about the graph of a data set? Select all that apply.

a)

A linear model is not a good fit for the data.

b)

A linear model is a good fit for the data.

45.

Which correlation coefficient is most accurate for this data set?

a)

r = - 0.3

b)

r = 0.99

c)

r = -0.99

46.

The linear regression equation that best represents the line of best fit for the data is y=20.8x-35. What does the slope represent?

a)

The number of bacteria increase by 20.8 per hour

b)

The number of bacteria increase by 20.8 per minute

c)

The number of bacteria decrease by 35 per hour

d)

The number of bacteria decrease by 35 per minute

47.

The linear regression equation that best represents the line of best fit for the data is y= -35 + 20.8x. Use the equation to predict the number of bacteria in 24 hours.

a)

35

b)

277

c)

464

d)

819

48.

A person travels by car. They record their miles driven in a data table. Calculate the linear regression equation of this data.

a)

y = - 1.79 + 61.93x

b)

y = 61.93 - 1.79x

c)

y = 0.016x + 0.03

d)

y = 0.0160 - .03x

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