(1) Can explain basic issues and calculate probability using basic rules in relation to probability and probability theory
(2) Can calculate queues using parameters such as average arrival and average service in relation to queuing theory.
(3) Can calculate the failure rate, life expectancy, and reliability of parallel and series systems, in relation to reliability analysis.
Outline:
Handling cumbersome and large amounts of data requires statistical thinking. Statistical analysis of data leads to the fastest possible solution. This course will be held in lecture and exercise formats while introducing irregular data cases.
Style:
From weeks 1 to 15, classes will be held in lecture and exercise formats. Assignment exercises will be based on each item set in the Course Objectives and Aims.
Notice:
This course's content will amount to 90 hours of study in total. These hours include the learning time guaranteed in classes and the standard self-study time required for pre-study / review, and completing assignment reports.
Students who miss 1/3 or more of classes will not be eligible for a passing grade.
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Theme |
Goals |
| 2nd Semester |
| 3rd Quarter |
| 1st |
Explain the guidance, what is covered in this course, and evaluation method. |
Understand the guidance, what is covered in this course, and evaluation method.
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| 2nd |
Explain the statistical handling of events and probability, independence and dependency, and probability.
Explain binding events, independence, conditional probability, and Bayes' theorem. |
Understand the statistical handling of events and probability, independence and dependency, and probability.
Understand binding events, independence, conditional probability, and Bayes' theorem.
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| 3rd |
Understand variance and deviation, and Z-conversion as indicators of scattered data. |
Understand variance and deviation, and Z-conversion as indicators of scattered data.
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| 4th |
Explain how to organize 2D data and about orthogonality and correlation. |
Can understand how to organize 2D data and about orthogonality and correlation.
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| 5th |
Exercise 1
Submit within class time |
Exercise 1
Submit within class time
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| 6th |
Explain about calculating using moving average methods and noise reduction. |
Understand about calculating using moving average methods and noise reduction.
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| 7th |
Explain signals and noise, and S/N ratio decibel calculations. |
Understand signals and noise, and S/N ratio decibel calculations.
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| 8th |
Explain Type 1 and Type 2 errors, and testing. |
Understand Type 1 and Type 2 errors, and testing.
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| 4th Quarter |
| 9th |
Exercise 2
Submit within class time |
Exercise 2
Submit within class time
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| 10th |
Explain the bathtub curve, failure rate for a period of time, and life expectancy.
Explain the calculation of the average remaining count and reliability from the initial number and failure rate. |
Understand the bathtub curve, failure rate for a period of time, and life expectancy.
Understand the calculation of the average remaining count and reliability from the initial number and failure rate.
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| 11th |
Explain the calculation of the reliability of parallel and series systems and redundant configurations. |
Understand the calculation of the reliability of parallel and series systems and redundant configurations.
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| 12th |
Exercise 3
Submit within class time |
Exercise 3
Submit within class time
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| 13th |
Program development environment using Jupyter notebook
Explain data analysis using pandas and DataFrame creation and editing. |
Program development environment using Jupyter notebook
Understand program data analysis using pandas, and DataFrame creation and editing.
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| 14th |
Explain visualization with Matplotlib and various graph creation. |
Understand visualization with Matplotlib and various graph creation.
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| 15th |
Exercise 4
Submit within class time |
Exercise 4
Submit within class time
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| 16th |
No final exam |
No final exam
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