Question

A company would like to examine the linear relationship between the age and credit score of an individual. The following table shows the credit scores and ages of 5 randomly selected people. These data have a sample correlation coefficient, rounded to three decimal places, of 0.953 Using this data alaph=0.10, test if the population correlation coefficient between a person's age and credit score is different than zero. What conclusions can you draw? find pvalue and test stat

Age Credit_Score

39 670

26 650

50 755

22 610

35 665

t stat=

p-value=

Answer #1

The statistical software output for this problem is:

Hence,

t = **5.43**

p-value = **0.0123**

A company that develops credit score models would like to
examine the relationship between the age and credit score of an
individual. The accompanying table shows the credit scores and ages
of 10 randomly selected people. Determine the sample correlation
coefficient between a person's age and credit score.
Age Credit_Score
37 670
24 655
54 770
27 615
32 670
46 795
34 720
59 760
40 680
42 610
r=? (Round to three decimal places as needed.)

Fair Isaac, the company that developed the credit score (FICO)
model used by most lenders today, would like to test the linear
relationship between age and credit score of an individual. The
follow table shows the credit scores and ages of 10 randomly
selected individuals:
AGE: 36 24 54 28 31 47 35 59 40 42
FICO: 675 655 760 615 660 790 720 760 685 610
Using XLS, calculate the correlation coefficient for this
sample. Test to see if...

We are interested in studying the linear relationship between
someone's age and how much they spend on travel. The following data
is provided:
Amount Spent on Travel
Age
850
39
997
43
993
50
649
59
1265
25
680
38
Find SSE.
a.
153,844.05
b.
111,147.2
c.
264,991.33
d.
667.33
We are interested in studying the linear relationship between
someone's age and how much they spend on travel. The following data
is provided:
Amount Spent on Travel
Age
850
39...

We are interested in studying the linear relationship between
someone's age and how much they spend on travel. The following data
is provided:
Amount Spent on Travel
Age
850
39
997
43
993
50
649
59
1265
25
680
38
Find the test statistic for testing is b1 is significant or
not.
a.
1.70
b.
4.38
c.
-1.70
d.
-7.59

A store manager wishes to find out whether there is a
relationship between the age of her employees and the number of
sick days they take each year. The data for the sample follow. Test
the hypothesis at α =0.05. Use Table I.
Age, x
18
26
39
48
53
58
Days, y
16
12
9
5
6
2
Find the correlation coefficient (r).
a.
-0.979
b.
0.979
c.
0.911
d.
-0.911
he critical values are:
a.
±0.811
b.
±0.878...

Research into the relationship between hours of study and grades
show widely different conclusions. A recent survey of graduates who
wrote the Graduate Management Admissions Test (GMAT) had the
following results.
Hours Studied Average Score
(Midpoint)
64 350
72 450
79 550
106 650
99 750
The Excel output for this regression is as following
SUMMART OUTPUT
____________________________
Regression Statistics
____________________________
Multiple R 0.919958
R Square 0.846322
Adjusted R Square 0.795097
Standard Error 71.57225
Observations 5
Anova
___________________________________________________________________________________________
...

PLEASE FILL IN THE BLANKS WITH THE PROPER TERM! THANKS
Key Terms
----------------------------------------------------------------------------------------------------------------------------
Positive relationship --- Occurs in so far as pairs of
observations tend to occupy similar relative positions in their
respective distribution.
Negative relationship --- Occurs in so far as pairs of
observations tend to occupy dissimilar relative positions in their
respective distribution.
Scatterplot --- a graph containing a cluster of dots
that represents all pairs of observations.
Person correlation coefficient --- A number between –1
and +1...

Question 6
An investigator is looking at the relationship between
periodontal disease and the onset of hypertension. Suppose the
investigator decides to look at height as a variable that may
confound the relationship between exposure and case status in his
study. After collecting information about the height of each
participant, he assembles a database that approximates height with
the normal distribution.
A) Assuming the mean of the distribution is 176.2 cm with a
standard deviation of 17.5 cm, what are...

1. For a pair of sample x- and y-values, what is the difference
between the observed value of y and the predicted value of y? a) An
outlier b) The explanatory variable c) A residual d) The response
variable
2. Which of the following statements is false:
a) The correlation coefficient is unitless. b) A correlation
coefficient of 0.62 suggests a stronger correlation than a
correlation coefficient of -0.82. c) The correlation coefficient,
r, is always between -1 and 1....

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