MATH 1130 Data & Tech Part 2 of 2 HW

xlsx

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University of Nebraska, Omaha *

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9950

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Geography

Date

Dec 6, 2023

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xlsx

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5

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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