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<p>Use Excel or another software to draw the scatter plot for the variables. You can either upload the file or copy the scatterplot into the text box for your answer.</p><p>The director of an alumni association for a small college wants to determine whether there is any type of relationship between the amount of an alumnus’s contribution (in dollars) and the years the alumnus has been out of school. The data follow. </p><table border=”0″><tbody><tr><td>Years <em>x</em></td><td>1</td><td>5</td><td>3</td><td>10</td><td>7</td><td>6</td></tr><tr><td>Contribution <em>y</em></td><td>500</td><td>100</td><td>300</td><td>50</td><td>75</td><td>80</td></tr></tbody></table>
Use Excel or another software to draw the scatter plot for the variables. You can either upload the file or copy the scatterplot into the text box for your answer.
The director of an alumni association for a small college wants to determine whether there is any type of relationship between the amount of an alumnus’s contribution (in dollars) and the years the alumnus has been out of school. The data follow.
Years x
1
5
3
10
7
6
Contribution y
500
100
300
50
75
80
Upload Choose a File
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<p style=”background-color: transparent; color: #2d3b45; font-family: sans-serif; font-size: 16px; font-style: normal; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal; margin: 12px 0px 12px 0px;”>Compute the correlation coefficient between hourly wage and years of service. Rounded to the nearest thousandths. Compare it to the answer of a previous question.</p><table style=”background-color: transparent; color: #2d3b45; font-family: sans-serif; font-size: 16px; font-style: normal; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal; border: 1px dashed #888888;”><tbody style=”background-color: transparent; color: #2d3b45; font-family: sans-serif; font-size: 16px; font-weight: 400; height: auto; line-height: 24px; min-height: 0px; margin: 0px;”><tr style=”height: 20px;”><td style=”min-width: 20px; padding: 2px; margin: 0px; border: 1px dashed #888888;”>years of service x</td><td style=”min-width: 20px; padding: 2px; margin: 0px; border: 1px dashed #888888;”>0.5</td><td style=”min-width: 20px; padding: 2px; margin: 0px; border: 1px dashed #888888;”>1</td><td style=”min-width: 20px; padding: 2px; margin: 0px; border: 1px dashed #888888;”>1.75</td><td style=”min-width: 20px; padding: 2px; margin: 0px; border: 1px dashed #888888;”>2.5</td><td style=”min-width: 20px; padding: 2px; margin: 0px; border: 1px dashed #888888;”>3.0</td></tr><tr style=”height: 20px;”><td style=”min-width: 20px; padding: 2px; margin: 0px; border: 1px dashed #888888;”>hourly wage y</td><td style=”min-width: 20px; padding: 2px; margin: 0px; border: 1px dashed #888888;”>9.51</td><td style=”min-width: 20px; padding: 2px; margin: 0px; border: 1px dashed #888888;”>8.23</td><td style=”min-width: 20px; padding: 2px; margin: 0px; border: 1px dashed #888888;”>10.95</td><td style=”min-width: 20px; padding: 2px; margin: 0px; border: 1px dashed #888888;”>12.70</td><td style=”min-width: 20px; padding: 2px; margin: 0px; border: 1px dashed #888888;”>12.75</td></tr></tbody></table><p> </p>
Compute the correlation coefficient between hourly wage and years of service. Rounded to the nearest thousandths. Compare it to the answer of a previous question.
years of service x
0.5
1
1.75
2.5
3.0
hourly wage y
9.51
8.23
10.95
12.70
12.75
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<img src=”https://upload.wikimedia.org/wikipedia/commons/thumb/a/af/Scatter_diagram_for_quality_characteristic_XXX.svg/1200px-Scatter_diagram_for_quality_characteristic_XXX.svg.png”><br>
Based on the scatterplot above, the correlation between process input and quality characteristic is [ Select ] [“negatie“, “positive“, “there is no correlation“]
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<img src=”http://www.conceptdraw.com/solution-park/resource/images/solutions/scatter-diagrams/Graphs-and-Charts-Scatter-Diagrams-Linear-Regression.png”><br>
Based on the scatterplot above, the correlation between in-lab crack reading and in-field crack reading is [ Select ] [“positive“, “negative“, “there is no correlation“]
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<img src=”http://science-fair-coach.com/wp-content/uploads/2011/12/Slide6.jpg”><br>
What is the value of variable 2 if variable 1 is equal 8?
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<p>Correlation coefficient between the left and right foot was computed and it was found to be 0.896.</p><p>If a patient’s left foot is cooler than the average, then the patient’s right foot is expected to be <select class=’question_input’ name=’question_40020995_53abc86406e2e287d275854673e2d89d’><option value=”>[ Select ]</option>[“<option value=’91822′>cooler</option>”, “<option value=’83759′>warmer</option>”]</select>than average.</p>
Correlation coefficient between the left and right foot was computed and it was found to be 0.896.
If a patient’s left foot is cooler than the average, then the patient’s right foot is expected to be [ Select ] [“cooler“, “warmer“] than average.
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<p>On Canvas, in session about Correlation and Regression you can find the file “How to test for correlation”. Use the data below to evaluate test statistic described there. Round your answer to the nearest thousandths.</p><p>cost of pizza 0.15 0.35 1.00 1.25 1.75 2.00</p><p>subway fare 0.15 0.35 1.00 1.35 1.50 2.00</p>
On Canvas, in session about Correlation and Regression you can find the file “How to test for correlation”. Use the data below to evaluate test statistic described there. Round your answer to the nearest thousandths.
cost of pizza 0.15 0.35 1.00 1.25 1.75 2.00
subway fare 0.15 0.35 1.00 1.35 1.50 2.00
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<p>Using the test describe in “How to test for correlation” (see question above), test the null hypothesis if n=12, t=3.1, <img class=”equation_image” title=”alpha=0.01″ src=”/equation_images/%255Calpha%253D0.01″ alt=”LaTeX: alpha=0.01″ data-equation-content=”alpha=0.01″> Choose the right conclusion.</p><p>a) T<span style=”display: inline !important; float: none; background-color: transparent; color: #000000; font-family: times new roman,serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal;”>here is not enough evidence at the α=0.01 level to conclude that there is a linear relationship in the population between the predictor </span><em style=”background-color: transparent; color: #000000; font-family: times new roman,serif; font-size: 15px; font-style: italic; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal; padding: 0px; margin: 0px;”>x</em><span style=”display: inline !important; float: none; background-color: transparent; color: #000000; font-family: times new roman,serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal;”> and response </span><em style=”background-color: transparent; color: #000000; font-family: times new roman,serif; font-size: 15px; font-style: italic; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal; padding: 0px; margin: 0px;”>y</em><span style=”display: inline !important; float: none; background-color: transparent; color: #000000; font-family: times new roman,serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal;”>.</span></p><p><span style=”display: inline !important; float: none; background-color: transparent; color: #000000; font-family: times new roman,serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal;”>b) there is sufficient evidence at the α=0.01 level to conclude that there is a linear relationship in the population between the predictor <em style=”background-color: transparent; color: #000000; font-family: times new roman,serif; font-size: 15px; font-style: italic; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal; padding: 0px; margin: 0px;”>x</em> and response <em style=”background-color: transparent; color: #000000; font-family: times new roman,serif; font-size: 15px; font-style: italic; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal; padding: 0px; margin: 0px;”>y</em></span></p><p>c) there is not enough data to draw any conclusion<span style=”display: inline !important; float: none; background-color: transparent; color: #000000; font-family: times new roman,serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal;”></span></p>
Using the test describe in “How to test for correlation” (see question above), test the null hypothesis if n=12, t=3.1,
α=0.01
Choose the right conclusion.
a) There is not enough evidence at the α=0.01 level to conclude that there is a linear relationship in the population between the predictor x and response y.
b) there is sufficient evidence at the α=0.01 level to conclude that there is a linear relationship in the population between the predictor x and response y
c) there is not enough data to draw any conclusion
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<p style=”background-color: transparent; color: #2d3b45; font-family: sans-serif; font-size: 16px; font-style: normal; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal; margin: 12px 0px 12px 0px;”>Using the test describe in “How to test for correlation” (see question above), test the null hypothesis if n=12, t=3.3, <img class=”equation_image” style=”height: 16px; max-width: 435.52px; vertical-align: middle; border: 0px none #2d3b45;” title=”alpha=0.01″ src=”/equation_images/%255Calpha%253D0.01″ alt=”LaTeX: alpha=0.01″ data-equation-content=”alpha=0.01″> Choose the right conclusion.</p><p style=”background-color: transparent; color: #2d3b45; font-family: sans-serif; font-size: 16px; font-style: normal; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal; margin: 12px 0px 12px 0px;”>a) T<span style=”display: inline !important; float: none; background-color: transparent; color: #000000; font-family: times new roman,serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal;”>here is not enough evidence at the α=0.01 level to conclude that there is a linear relationship in the population between the predictor </span><em style=”background-color: transparent; color: #000000; font-family: times new roman,serif; font-size: 15px; font-style: italic; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal; padding: 0px; margin: 0px;”>x</em><span style=”display: inline !important; float: none; background-color: transparent; color: #000000; font-family: times new roman,serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal;”> and response </span><em style=”background-color: transparent; color: #000000; font-family: times new roman,serif; font-size: 15px; font-style: italic; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal; padding: 0px; margin: 0px;”>y</em><span style=”display: inline !important; float: none; background-color: transparent; color: #000000; font-family: times new roman,serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal;”>.</span></p><p style=”background-color: transparent; color: #2d3b45; font-family: sans-serif; font-size: 16px; font-style: normal; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal; margin: 12px 0px 12px 0px;”><span style=”display: inline !important; float: none; background-color: transparent; color: #000000; font-family: times new roman,serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal;”>b) there is sufficient evidence at the α=0.01 level to conclude that there is a linear relationship in the population between the predictor <em style=”background-color: transparent; color: #000000; font-family: times new roman,serif; font-size: 15px; font-style: italic; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal; padding: 0px; margin: 0px;”>x</em> and response <em style=”background-color: transparent; color: #000000; font-family: times new roman,serif; font-size: 15px; font-style: italic; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal; padding: 0px; margin: 0px;”>y</em></span></p><p style=”background-color: transparent; color: #2d3b45; font-family: sans-serif; font-size: 16px; font-style: normal; font-variant: normal; font-weight: 400; text-align: left; text-decoration: none; text-indent: 0px; white-space: normal; margin: 12px 0px 12px 0px;”>c) there is not enough data to draw any conclusion</p>
Using the test describe in “How to test for correlation” (see question above), test the null hypothesis if n=12, t=3.3,
α=0.01
Choose the right conclusion.
a) There is not enough evidence at the α=0.01 level to conclude that there is a linear relationship in the population between the predictor x and response y.
b) there is sufficient evidence at the α=0.01 level to conclude that there is a linear relationship in the population between the predictor x and response y
c) there is not enough data to draw any conclusion
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If all data points on its scatter plot are on one line, then the correlation coefficient is equal <select class=’question_input’ name=’question_40020999_5a3641d237e60d3404067d9fcf811ff2′><option value=”>[ Select ]</option>[“<option value=’72553′>1 or -1</option>”, “<option value=’10454′>1</option>”, “<option value=’83615′>-1</option>”, “<option value=’40051′>0</option>”, “<option value=’50357′>not possible to tell</option>”, “<option value=’60008′>0.5</option>”, “<option value=’93076′>-0.5</option>”, “<option value=’55403′>4</option>”]</select>
If all data points on its scatter plot are on one line, then the correlation coefficient is equal [ Select ] [“1 or -1“, “1“, “-1“, “0“, “not possible to tell“, “0.5“, “-0.5“, “4“]
Question 11 1 pts
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