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Correlation and regression

Total questions: 50

Worksheet time: 52mins

Name
Class
Date
1.

Number of steps taken per day and number of kilometers walked per day. r=.92r=.92  

a)

strong positive

b)

strong negative

c)

weak positive

d)

weak negative

2.

Estimate the correlation coefficient for this scatterplot.

a)

A) r = -0.9

b)

B) r = 1

c)

C) r = 0.9

d)

D) r = -1

3.

As x increases, y decreases.

a)

A) no correlation

b)

B) negative correlation

c)

C) correlation coefficient

d)

D) positive correlation

4.

As x increases, y increases

a)

A) correlation coefficient

b)

B) causation

c)

C) positive correlation

d)

D) negative correlation

5.

A line of best fit has been drawn on the scatter plot below. The relationship between these variables can be described as having

a)

negative correlation

b)

no correlation

c)

positive correlation

d)

zero correlation

6.
A restaurant sells pizza for the prices in the data table.  Calculate the linear regression equation of the data.
a)
y = 1.5x + 12
b)
y = 12x + 1.5
c)
y = 0.67x - 8
d)
y = -8x + 0.67
7.

Find the equation of the line of best fit for the given data

a)

y = 163.41x+1.49

b)

y =- 163.41x+ 4.19

c)

y =- 4.19x+163.41

d)

y = 4.19x -163.41

8.

What type of correlation best describes the scatterplot shown.

a)

positive, weak

b)

positive, strong

c)

negative, weak

d)

no correlation

9.

What type of correlation best describes the scatter plot shown?

a)

positive, weak

b)

positive, strong

c)

negative, weak

d)

negative, strong

10.

What correlation coefficient would be describe the correlation?

a)

0

b)

-0.999

c)

0.978

d)

0.2

11.

Which correlation coefficient best describes the correlation shown?

a)

0

b)

-0.75

c)

-0.3

d)

0.3

12.

Data is analyzed comparing hours studied and grades. It is determined that the correlation coefficient is 0.92. What does this mean?

a)

There is a strong positive correlation between studying and grades.

b)

There is a strong negative correlation between studying and grades.

c)

There is a weak positive correlation between studying and grades.

d)

There is a weak negative correlation between studying and grades.

13.

Estimate the correlation coefficient for this scatterplot.

a)

A) r = 1.2

b)

B) r = 0.89

c)

C)r = 0

d)

D) r = -0.89

14.

Estimate the correlation coefficient for this scatterplot.

a)

A) r = -0.9

b)

B) r = 1

c)

C) r = 0.9

d)

D) r = -1

15.

Which scatter diagram shows the strongest positive correlation?

a)
b)
c)
d)
16.
r=0.3
a)
Strong positive 
b)
Weak positive
c)
Strong negative
d)
Weak negative 
17.

Given that the scatter diagram has a product moment correlation coefficient of 0.9, what can you conclude?

a)

There is a weak negative linear correlation between x and y

b)

There is a strong negative linear correlation between x and y

c)

There is a strong positive linear correlation between x and y

d)

There is a weak positive linear correlation between x and y

18.

The product moment correlation coefficient between x and y is 0.98.

This means that x direct cause y (or vice versa).

a)

True

b)

False

19.

For an estimate to be reliable, .......

(choose all that applies)

a)

r is near to 1 or -1

b)

it is an extrapolation

c)

it is an interpolation

d)

x must be the independent variable.

20.

What type of association is represented by the scatter plot

a)

Positive

b)

Negative

c)

None

21.
Is the association a positive or negative association?
a)
Positive
b)
Negative
22.

Describe the association for the scatterplot based on data plotted.

a)

As the weeks increase, the amount of money on the gift card increases.

b)

As the weeks decrease, the amount of money on the gift card increases.

c)

There is no relationship between the time in weeks and the amount of dollars.

d)

As the weeks increase, the amount of money on the gift card decreases.

23.

What type of correlation (association)?

The outside temperature and the amount of layers you wear.

a)

A) Positive correlation

b)

B) Negative correlation

c)

D) No correlation

24.

As x increases, y decreases.

a)

A) no correlation

b)

B) negative correlation

c)

C) correlation coefficient

d)

D) positive correlation

25.

As x increases, y increases

a)

A) correlation coefficient

b)

B) causation

c)

C) positive correlation

d)

D) negative correlation

26.

What is missing from this graph?

a)

suitable title

b)

units of x and y axis

c)

regression line

d)

all of these

27.

What does this graph show?

a)

There is no correlation between fork length and total length.

b)

There is a positive correlation between fork length and total length.

c)

There is a negative correlation between fork length and total length.

d)

There is a week correlation between fork length and total length.

28.

What is the equation of the regression line?

a)

0.986

b)

2527

c)

total length (cm) = 1.1forklength (cm) + 4.1

d)

4.1

29.

What is the correlation coefficient of the regression line?

a)

0.986

b)

2527

c)

total length (cm) = 1.1forklength (cm) + 4.1

d)

4.1

30.

What is the gradient of the regression line?

a)

1.1

b)

2527

c)

total length (cm) = 1.1forklength (cm) + 4.1

d)

4.1

31.

The correlation coefficient of the regression line is 0.986. What does that mean?

a)

There is a very strong, positive correlation between the variables.

b)

There is a very strong, negative correlation between the variables.

c)

There is a weak, negative correlation between the variables.

d)

As fork length increases, so does total length.

32.

Estimate the correlation coefficient for this scatterplot.

a)

A) r = 1.2

b)

B) r = 0.89

c)

C)r = 0

d)

D) r = -0.89

33.

Describe the correlation in the graph shown.

a)

A) Strong Negative

b)

B) Strong Positive

c)

C) Weak Negative

d)

D) No Correlation

34.

Estimate the correlation coefficient for this scatterplot.

a)

A) r = -0.9

b)

B) r = 1

c)

C) r = 0.9

d)

D) r = -1

35.

What type of correlation does this graph show?

a)

A) Positive

b)

B) negative

c)

C) none

d)

D) all of the above

36.
As the age of the car increases, its value decreases. Which scatterplot represents this relationship?
a)
A
b)
B
c)
C
d)
D
37.

Write the equation for the linear regression shown.

a)

y=5.11x+3.23y=-5.11x+3.23

b)

r=0.8r=0.8

c)

 \

d)

y=0.64x+0.8y=0.64x+0.8

38.

Write the equation for the linear regression shown.

a)

y=ax+by=ax+b

b)

y=0.6x+0.1y=0.6x+0.1

c)

y=0.72x+ry=0.72x+r

d)

y=0.1x+0.6y=0.1x+0.6

39.

What is a scatter plot?

a)

A graph that shows the relationship of two data sets

b)

A graph that shows information that is connected in some ways

c)

A graph drawn using rectangular bars to show how large each value is

d)

A graph that shows data changing over time

40.

A scatter diagram may reveal

a)

the strength of a relationship.

b)

the direction of a relationship.

c)

the form of a relationship.

d)

all of the above.

41.
Which scatter plot shows no relationship?
a)
Graph A
b)
Graph B
c)
Graph C
d)
Graph D
42.

When the values of two variables move in the same direction, correlation is said to be

a)

Linear

b)

Non-linear

c)

Positive

d)

Negative

43.

The value of the coefficient of correlation r lies between:

a)

0 and 1

b)

-1 and 0

c)

-1 and +1

d)

-0.5 and +0.5

44.

. ________measures the strength of the linear relationship between the dependent and the independent variable.

a)

Correlation Coeeficient

b)

Distance value

c)

Y Intercept

d)

Residual

45.

The value of the ‘coefficient of determination’ (r2) ranges from -1 to +1

a)

True

b)

False

46.

Coefficient of correlation of -0.90 and +0.90 have equal strength

a)

True

b)

False

47.

In a simple linear regression analysis, the correlation coefficient (r) and the slope (m) __________ have the same sign.

a)

always

b)

never

c)

sometimes

48.

The ___________of the simple linear regression model is the value of y when the mean value of x is zero.

a)

correlation coefficient

b)

slope

c)

y intercept

d)

coefficient of determination

49.
What graph best shows correlation? 
a)
Bar Graph
b)
Histogram
c)
Ogive
d)
Scatterplot
50.

The regression equation always passes through:

a)

(X, Y)

b)

(a, b)

c)

(X̅ ,ȳ)

d)

(X̅, Y)