Instructions Go to the Mascon Visualization Tool from the Colorado Center for Astrodynamics Research – CU Boulder: https://ccar.colorado.edu/grace/gsfc.html Click on “Trend” from the top left menu and look for a mascon in the DMV region (DC, Maryland, Virginia). Pick one of your choices. Save the image (or take a screenshot, if it is easier) of the time series that is provided and insert it in your word file. Click on “Get Data” to download the time series. Data will be in .csv format. Plot your time series using your software of choice (Pyhton, Excel, Matlab, etc.). Make sure you label your axes, add a title, legend, etc. Analyze your time series. Find the mean, maximum value, minimum value, and standard deviation. You can do it in Excel using functions like "AVERAGE", "MAX", "MIN", and "STDEV", or using any other software of choice. What can you infer from this information? Do you notice any temporal pattern in the time series (e.g., daily, seasonal, climatological cycles)? Explain your findings. Add a linear trendline to your time series and show the equation and R2. Discuss the goodness of your fit. Add your figure to the report and compare it to the one you copied from the website. Discuss any physical or anthropogenic processes that may cause the trend (if any). Check the significance of the identified trend using the Mann-Kendall test. You may want to review this example that shows how to perform the test in Excel: https://www.real-statistics.com/time-series-analysis/time-series-miscellaneous/mann-kendall-test/ Check the significance of the trend only using the first 10 values of TWS in the time series, using alpha = 0.05; and alpha = 0.01. Repeat the test using the first 20 values and the two alpha values. Do you see any difference in the p-values you obtained? Is the result of the test different when you use a longer time series? And when you decrease alpha to 0.01? Why? Discuss your results and why it is important to test the significance of a time series trend. Please submit a word file containing: Detailed responses to every single point in the instructions; All figures and plots; Any references you used.

Instructions Go to the Mascon Visualization Tool from the Colorado Center for Astrodynamics Research – CU Boulder: https://ccar.colorado.edu/grace/gsfc.html Click on “Trend” from the top left menu and look for a mascon in the DMV region (DC, Maryland, Virginia). Pick one of your choices. Save the image (or take a screenshot, if it is easier) of the time series that is provided and insert it in your word file. Click on “Get Data” to download the time series. Data will be in .csv format. Plot your time series using your software of choice (Pyhton, Excel, Matlab, etc.). Make sure you label your axes, add a title, legend, etc. Analyze your time series. Find the mean, maximum value, minimum value, and standard deviation. You can do it in Excel using functions like "AVERAGE", "MAX", "MIN", and "STDEV", or using any other software of choice. What can you infer from this information? Do you notice any temporal pattern in the time series (e.g., daily, seasonal, climatological cycles)? Explain your findings. Add a linear trendline to your time series and show the equation and R2. Discuss the goodness of your fit. Add your figure to the report and compare it to the one you copied from the website. Discuss any physical or anthropogenic processes that may cause the trend (if any). Check the significance of the identified trend using the Mann-Kendall test. You may want to review this example that shows how to perform the test in Excel: https://www.real-statistics.com/time-series-analysis/time-series-miscellaneous/mann-kendall-test/ Check the significance of the trend only using the first 10 values of TWS in the time series, using alpha = 0.05; and alpha = 0.01. Repeat the test using the first 20 values and the two alpha values. Do you see any difference in the p-values you obtained? Is the result of the test different when you use a longer time series? And when you decrease alpha to 0.01? Why? Discuss your results and why it is important to test the significance of a time series trend. Please submit a word file containing: Detailed responses to every single point in the instructions; All figures and plots; Any references you used.

Residential Construction Academy: House Wiring (MindTap Course List)

4th Edition

ISBN:9781285852225

Author:Gregory W Fletcher

Publisher:Gregory W Fletcher

Chapter22: Solar Photovoltaic (pv) System Installation

Section: Chapter Questions

Problem 24RQ

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Instructions

Go to the Mascon Visualization Tool from the Colorado Center for Astrodynamics Research – CU Boulder: https://ccar.colorado.edu/grace/gsfc.html

Click on “Trend” from the top left menu and look for a mascon in the DMV region (DC, Maryland, Virginia). Pick one of your choices.

Save the image (or take a screenshot, if it is easier) of the time series that is provided and insert it in your word file.

Click on “Get Data” to download the time series. Data will be in .csv format.

Plot your time series using your software of choice (Pyhton, Excel, Matlab, etc.). Make sure you label your axes, add a title, legend, etc.

Analyze your time series.

Find the mean, maximum value, minimum value, and standard deviation. You can do it in Excel using functions like "AVERAGE", "MAX", "MIN", and "STDEV", or using any other software of choice. What can you infer from this information?
Do you notice any temporal pattern in the time series (e.g., daily, seasonal, climatological cycles)? Explain your findings.

Add a linear trendline to your time series and show the equation and R². Discuss the goodness of your fit.

Add your figure to the report and compare it to the one you copied from the website.
Discuss any physical or anthropogenic processes that may cause the trend (if any).

Check the significance of the identified trend using the Mann-Kendall test. You may want to review this example that shows how to perform the test in Excel: https://www.real-statistics.com/time-series-analysis/time-series-miscellaneous/mann-kendall-test/

Check the significance of the trend only using the first 10 values of TWS in the time series, using

alpha = 0.05;
and alpha = 0.01.

Repeat the test using the first 20 values and the two alpha values.

Do you see any difference in the p-values you obtained? Is the result of the test different when you use a longer time series? And when you decrease alpha to 0.01? Why? Discuss your results and why it is important to test the significance of a time series trend.

Please submit a word file containing:

Detailed responses to every single point in the instructions;
All figures and plots;
Any references you used.

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