MATH 1130 Data & Tech Part 2 of 2 HW
xlsx
School
University of Nebraska, Omaha *
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Course
9950
Subject
Geography
Date
Dec 6, 2023
Type
xlsx
Pages
5
Uploaded by osbornkaden86
Problem A:
Coral
degrees Celcuis
Coral Length MM
y = -0.3255x + 12.317
5. What is the predicted Coral Growth at 30°C?
2.552
6. What is the correlation between the two variables?
(Use CORREL)
-0.882596829924096
7.
Is the Correlation positive or negative?
Negative
8.
Is the Correlation Strong, Moderate or Weak
Strong
9.
Should you use this data to make predictions?
Yes
Scientists are concerned that rising sea temperatures will have an adverse effect on coral growth. A small
study on this issue produced the data in the table to the left:
1. Which column is the measure
for the
Explanatory Variable
?
2. Which column is the measure
for the
Response Variable
?
3.
Create a
Scatter Plot
and the Quick Layout to add details.
4. What is the Equation of the
Regression line
?
29.6
29.8
30
30.2
30.4
30.6
30.8
31
2
2.1
2.2
2.3
2.4
2.5
2.6
2.7
f(x) = − 0.325454545454542 x + 12.3169870129869
R² = 0.778977164192064
Coral growth (mm)
Coral growth (mm)
Linear (Coral growth (mm))
degree celcuis
Coral Length (mm)
Problem B: Fish
Length
Mercury Concentration
y = 0.0032x - 0.7374
0.6066
6. What is the correlation between the two variables?
0.852426168230748
7.
Is the Correlation positive or negative?
Positive
8.
Is the Correlation Strong, Moderate or Weak
Strong
9.
Should you use this data to make predictions?
Yes
The presence of mercury in fish is a health hazard, particularly for women who may
become pregnant and children. The table contains data on mercury concentration in tissue
samples from 20 largemouth bass taken from Lake Natoma (California). Only fish of
legal/edible size were used in this study.
1. Which column is the measure
for the
Explanatory Variable
?
2. Which column is the measure
for the
Response Variable
?
3.
Create a
Scatter Plot
and the Quick Layout to add details.
4. What is the Equation of the
Regression line
?
5. What is the predicted Mercury Concentration for a fish 420 mm in
length?
300 320 340 360 380 400 420 440 460 480 500
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
f(x) = 0.003227361187131 x − 0.737435808550749
R² = 0.726630372284556
Fish
Mercury Concentration
(μg/gμg/g wet wt.)
Linear (Mercury Concen-
tration (μg/gμg/g wet
wt.))
Length
Concentration
Problem C: Rain
Temp
Radar Rain Rate
y = -9.5603x + 2009.1
5.
What is the predicted Radar Rain Rate at 200 K?
97.04
6. What is the correlation between the two variables?
-0.948575586983466
7.
Is the Correlation positive or negative?
Negative
8.
Is the Correlation Strong, Moderate or Weak
Strong
9.
Should you use this data to make predictions?
Yes
Satellites are one of the many tools used for predicting flash floods, heavy rainfall, and large amounts of
snow. Geostationary (GEOS) satellites collect data on cloud top brightness temperatures (measured in
degrees Kelvin). It turns out that colder cloud temperatures are associated with higher and thicker clouds,
which in turn are associated with heavier precipitation.
Because ground radar can be limited by location and
obstructions, having an alternative for predicting the rainfall rates can be useful.
1. Which column is the measure
for the
Explanatory Variable
?
2. Which column is the measure
for the
Response Variable
?
3.
Create a
Scatter Plot
and the Quick Layout to add details.
4. What is the Equation of the
Regression line
?
194 196 198 200 202 204 206 208 210 212
0
20
40
60
80
100
120
140
160
f(x) = − 9.56029411764706 x + 2009.14705882353
R² = 0.899795644221028
Rain
Radar Rain Rate (mm/h)
Linear (Radar Rain Rate
(mm/h))
Temp
Radar Rain Rate
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Problem E: Dates
y = 0.4237x + 41.079
5. What is the predicted date height for a women 66 inches tall?
69.0432
6. What is the correlation between the two variables?
0.360156774349722
7.
Is the Correlation positive or negative?
Positive
8.
Is the Correlation Strong, Moderate or Weak
Weak
9.
Should you use this data to make predictions?
No
A student wonders if tall women tend to date taller people than do short women. She
measures herself, her sister, and the women in the adjoining dorm rooms. Then she
measures the next person each woman dates and obtains the following data (in inches):
1. Which column is the measure
for the
Explanatory Variable
?
2. Which column is the measure
for the
Response Variable
?
3.
Create a
Scatter Plot
and the Quick Layout to add details.
4. What is the Equation of the
Regression line
?
62
63
64
65
66
67
68
69
70
71
60
62
64
66
68
70
72
74
f(x) = 0.423728813559323 x + 41.0790960451977
R² = 0.129712902109997
Heights of Dates (inches)
Heights of Dates (inches)
Linear (Heights of Dates
(inches))
Axis Title
Axis Title
Problem F: Icicles
Time
Length
y = 0.1509x - 1.95
6. What is the predicted the length if the time is 95 minutes
12.3855
7. What is the correlation between the two variables?
0.996295706050115
8.
Is the Correlation positive or negative?
Positive
9.
Is the Correlation Strong, Moderate or Weak
Strong
How fast do icicles grow? Here are data on two variables, Time measured in minutes and
Length measured in centimeters, for one set of conditions: no wind, temperature −11
C,
∘
and water flowing over the icicle at 12 milligrams per second.
1. Which column is the measure
for the
Explanatory Variable
?
2. Which column is the measure
for the
Response Variable
?
3.
Create a
Scatter Plot
and identify the outlier
4.
From the second copy of the icicle data, delete the outlier and re-create a Scatter Plot
in the space below questions 4.
Use the Quick Layout to add details.
5. What is the Equation of the
Regression line
?
0
20
40
60
80
100
120
140
160
0
5
10
15
20
25
30
35
40
45
f(x) = 0.176989453499521 x − 2.65848513902205
R² = 0.664325113295742
Icicles
Column B
Linear (Column B)
Time
Length
0
20
40
60
80
100
120
140
160
0
5
10
15
20
25
f(x) = 0.150934699103713 x − 1.94997865983782
R² = 0.992605133893896
Icicles
Column B
Linear (Column B)
Time
Length