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1. The following data are annual precipitation amounts (inches) from nine rain gauge stations at various elevations (ft) in the Willamette Valley climate zone. Station Beaverton Portland Estacada Hillsboro Oregon City Headworks Rex Willamette Dilley Elevation Precipitation (ft) 270 20 410 160 170 750 520 150 170 (in) 39.77 36.32 59.28 37.57 47.06 79.5 41.37 40.78 44.2 (a) Calculate the mean and standard deviation of elevation and precipitation. (b) Plot measured precipitation values (y-axis) against elevation (x-axis) in excel. (c) What is regression equation using precipitation (ppt) as a dependent variable (Y) and elevation as an explanatory variable (X). In other words, the form of the equation will look like Y = a + bX. State the physical meaning of a (Y intercept) and b (slope of the regression). (d) Is this a significant relationship? How do you tell? How well does precipitation amount track changes in elevation? How can you quantify this relationship? (hint: In Excel, go to data analysis under the tools menu. Highlight regression, click OK. You then need to assign input X and Y ranges. A new sheet will report the ANOVA table. Read significance F, and see whether the F value is greater than 0.05).

1. The following data are annual precipitation amounts (inches) from nine rain gauge stations at various elevations (ft) in the Willamette Valley climate zone. Station Beaverton Portland Estacada Hillsboro Oregon City Headworks Rex Willamette Dilley Elevation Precipitation (ft) 270 20 410 160 170 750 520 150 170 (in) 39.77 36.32 59.28 37.57 47.06 79.5 41.37 40.78 44.2 (a) Calculate the mean and standard deviation of elevation and precipitation. (b) Plot measured precipitation values (y-axis) against elevation (x-axis) in excel. (c) What is regression equation using precipitation (ppt) as a dependent variable (Y) and elevation as an explanatory variable (X). In other words, the form of the equation will look like Y = a + bX. State the physical meaning of a (Y intercept) and b (slope of the regression). (d) Is this a significant relationship? How do you tell? How well does precipitation amount track changes in elevation? How can you quantify this relationship? (hint: In Excel, go to data analysis under the tools menu. Highlight regression, click OK. You then need to assign input X and Y ranges. A new sheet will report the ANOVA table. Read significance F, and see whether the F value is greater than 0.05).

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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**Title: Analyzing Precipitation Data in the Willamette Valley Climate Zone** **Overview:** The following educational material presents data on annual precipitation (measured in inches) from nine rain gauge stations at different elevations (measured in feet) within the Willamette Valley climate zone. **Data Table:** | Station | Elevation (ft) | Precipitation (in) | |-------------|----------------|--------------------| | Beaverton | 270 | 39.77 | | Portland | 20 | 36.32 | | Estacada | 410 | 59.28 | | Hillsboro | 160 | 37.57 | | Oregon City | 170 | 47.06 | | Headworks | 750 | 79.5 | | Rex | 520 | 41.37 | | Willamette | 150 | 40.78 | | Dilley | 170 | 44.2 | **Tasks:** **(a) Statistical Analysis:** Calculate the mean and standard deviation for both elevation and precipitation data. These values will help understand the distribution and variability of the data. **(b) Data Visualization:** Plot the measured precipitation values against elevation. Use Excel to create a scatter plot with precipitation on the y-axis and elevation on the x-axis to visually assess the relationship. **(c) Regression Analysis:** Derive a regression equation with precipitation as the dependent variable (Y) and elevation as the explanatory variable (X). The equation will take the form Y = a + bX, where 'a' represents the Y-intercept and 'b' is the slope. Explain the physical meaning of these coefficients. **(d) Evaluating Relationship Significance:** Determine if there is a significant relationship between elevation and precipitation. Analyze how well changes in elevation correspond with changes in precipitation, and quantify this relationship using regression analysis. **Hint for Analysis:** To perform the regression analysis in Excel, navigate to "Data Analysis" under the "Tools" menu. Choose "Regression" and input the appropriate range for X and Y variables. The output will include an ANOVA table; review the significance F value to assess statistical significance (consider values greater than 0.05 as not significant).
Transcribed Image Text:**Title: Analyzing Precipitation Data in the Willamette Valley Climate Zone** **Overview:** The following educational material presents data on annual precipitation (measured in inches) from nine rain gauge stations at different elevations (measured in feet) within the Willamette Valley climate zone. **Data Table:** | Station | Elevation (ft) | Precipitation (in) | |-------------|----------------|--------------------| | Beaverton | 270 | 39.77 | | Portland | 20 | 36.32 | | Estacada | 410 | 59.28 | | Hillsboro | 160 | 37.57 | | Oregon City | 170 | 47.06 | | Headworks | 750 | 79.5 | | Rex | 520 | 41.37 | | Willamette | 150 | 40.78 | | Dilley | 170 | 44.2 | **Tasks:** **(a) Statistical Analysis:** Calculate the mean and standard deviation for both elevation and precipitation data. These values will help understand the distribution and variability of the data. **(b) Data Visualization:** Plot the measured precipitation values against elevation. Use Excel to create a scatter plot with precipitation on the y-axis and elevation on the x-axis to visually assess the relationship. **(c) Regression Analysis:** Derive a regression equation with precipitation as the dependent variable (Y) and elevation as the explanatory variable (X). The equation will take the form Y = a + bX, where 'a' represents the Y-intercept and 'b' is the slope. Explain the physical meaning of these coefficients. **(d) Evaluating Relationship Significance:** Determine if there is a significant relationship between elevation and precipitation. Analyze how well changes in elevation correspond with changes in precipitation, and quantify this relationship using regression analysis. **Hint for Analysis:** To perform the regression analysis in Excel, navigate to "Data Analysis" under the "Tools" menu. Choose "Regression" and input the appropriate range for X and Y variables. The output will include an ANOVA table; review the significance F value to assess statistical significance (consider values greater than 0.05 as not significant).
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