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Application: Nuclear Plant Data Analysis | Learning Through Applications
Matlab From Beginner to Professional
course content

Contenido del Curso

Matlab From Beginner to Professional

Matlab From Beginner to Professional

1. Basic Syntax And Coding With A Text Editor
2. Coding Foundations
3. Learning Through Applications
4. Visualizations
5. Recursion + Matrix Multiplication

bookApplication: Nuclear Plant Data Analysis

Apply what you’ve learned to analyze power and wastewater generation data coming from three nuclear power plants, and pick up a bunch of important details along the way!

Alternatively, when we are dealing with a set of observations xi {x1, x 2, x 3, ..., xn} of a random variable with a presumed (but unknown) distribution, we can estimate the standard deviation with the formula.

Which is the formula coded in the video (note that mean(xi) was calculated on the line preceding the standard deviation calculation: so we reference this instead of recalculating for efficiency). A better, unbiased estimator would divide by n - 1 instead of n. We ignore this detail here for simplicity, however it could be easily fixed in the code by multiplying the result by

Task

  1. Understand the Goals
    Begin by watching the video to grasp the program's objectives. Use the video as a source of inspiration and guidance for your approach.
  2. Identify the Excel File Location
    Locate the file containing the data you'll be working with.
  3. Import the Excel Data
    Use appropriate libraries or methods to read the data from the Excel file.
  4. Analyze and Split the Data
    • Divide the data based on the plant location.
    • Compute descriptive statistics (minimum, maximum, mean, and standard deviation) for each location, focusing on both power and wastewater data across the entire year.
  5. Export the Results
    Save your results, including the calculated statistics, into an Excel file for further use.
  6. Iterate and Improve
    • Attempt to design your program in a modular and structured way.
    • If you encounter issues, rely more on hints or code shown in the video.
    • As a last resort, replicate the code in the video as closely as possible.
  7. Quality Control
    Validate your program's output by comparing it with the results shown in the video to ensure accuracy and reliability.

However, fair warning: it's better to practice coding your own versions now while there's a safety net, as we'll start getting lest explicit with the code we show beginning in the next chapter.

The video also highlights several convenient checkpoints where you can check your programming as you go along by either:

  • Unsilencing variables (by removing the semicolon);
  • Having your function temporarily output the variable in question.

¿Todo estuvo claro?

¿Cómo podemos mejorarlo?

¡Gracias por tus comentarios!

Sección 3. Capítulo 1
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