Question

The data represent number of flash drives sold per day at a local computer shop and their prices.

Price (x) Units Sold (y)

$34 ................ 3

36 ................. 4

32 ................ 6

35 ............... 5

30 ............... 9

38 .............. 2

40 .............. 1

A.) Develop a least-squares regression line and explain what the slope of the line indicates.

B.) Compute the coefficient of determination and comment on the strength of relationship between x and y.

C.) Compute the sample correlation coefficient between the price and the number of flash drives sold. Use (= 0.01 to test the relationship between x and y.

Answer #1

A coffee shop takes daily data on the high temperature for the
day in degrees F, and the number of cups of hot chocolate sold.
They construct a scatterplot and examine the linear
relationship.The least squares regression line equation is:
y=76.42-1.38x
1.Using the slope value, describe the relationship in context.
2.Can this line equation be used to make a prediction for number of
cups of hot chocolate sold when it's 60 degrees F outside?
Explain.3.The coffee shop took similar data...

Part 2 (Numerical Descriptive Techniques)
The following data represent the ages of a sample of 25
employees from a government department. Enter this data on a sheet
called Employee Data.
31
43
56
23
49
42
33
61
44 28
48
38
44
35
40
64
52
42
47 39
53
27
36
35 20
Find the median age.
Find the lower quartile of the ages.
Find the upper quartile of the ages.
Compute the range and...

The following is a set of data from a sample of n=11 items.
Complete parts (a) through (c):
X Y
34 17
16 8
6 3
40 20
14 7
30 15
8 4
38 19
36 18
36 18
8 4
a. Compute the sample covariance.
(Round to three decimal places as needed.)
b. Compute the coefficient of
correlation.r=
(Round to three decimal places as needed.)
c. How strong is the relationship between X
and Y? Explain.
A. The...

Below you are given a partial computer output based on a sample
of 14 observations, relating an independent variable (x) and a
dependent variable (y). Predictor Coefficient Standard Error
Constant 6.428 1.202 X 0.470 0.035 Analysis of Variance SOURCE SS
Regression 958.584 Error (Residual) Total 1021.429 a. Develop the
estimated regression line. b. At = 0.05, test for the
significance of the slope. c. At = 0.05, perform an F test. d.
Determine the coefficient of determination. e....

A sociologist is interested in the relation between x = number
of job changes and y = annual salary (in thousands of dollars) for
people living in the Nashville area. A random sample of 10 people
employed in Nashville provided the following information. x (number
of job changes) 7 4 5 6 1 5 9 10 10 3 y (Salary in $1000) 38 32 34
32 32 38 43 37 40 33 Σx = 60; Σy = 359; Σx2 =...

The accompanying data represent the number of days absent, x,
and the final exam score, y, for a sample of college students in a
general education course at a large state university. Complete
parts (a) through (e) below.
Absences and Final Exam Scores
No. of absences, x
0
1
2
3
4
5
6
7
8
9
Final exam score, y
89.6
87.3
83.4
81.2
78.7
74.3
64.5
71.1
66.4
65.6
Critical Values for Correlation Coefficient
n
3
0.997
4...

A sociologist is interested in the relation between x =
number of job changes and y = annual salary (in thousands
of dollars) for people living in the Nashville area. A random
sample of 10 people employed in Nashville provided the following
information.
x (number of job changes)
3
5
4
6
1
5
9
10
10
3
y
(Salary in $1000)
37
32
34
32
32
38
43
37
40
33
Σx = 56; Σy = 358; Σx2 =...

The following data show the brand, price ($), and the overall
score for six stereo headphones that were tested by a certain
magazine. The overall score is based on sound quality and
effectiveness of ambient noise reduction. Scores range from 0
(lowest) to 100 (highest). The estimated regression equation for
these data is
ŷ = 24.331 + 0.307x,
where x = price ($) and y = overall score.
Brand
Price ($)
Score
A
180
74
B
150
71
C
95...

A baseball manager wishes to find out if there is a relationship
between the number of homeruns and the number of strikeouts in a
season by batters. The data for the sample are shown:
Homeruns, x: 23 62 10 51 38
Strikeouts, y: 61 175 40 129 124
a) Compute the value of the correlation coefficient.
b) Find the equation of the regression line.
c) Find y’ (the number of strikeouts) when x = 28. (someone hits
28 homeruns)

The following data represent a company's yearly sales volume and
its advertising expenditure over a period of 5 years.
(y) sales in millions of dollars (x) advertising in
($10,000)
15 32
16 33
18 35
17 34
16 36
Use the method of least squares to compute an estimated
regression line between sales and advertising by computing b0 and
b1.
If the company's advertising expenditure is $400,000, what are
the predicted sales? Give the answer in dollars.
What does the...

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