UAT 106 · 3(2-2-5) · Year/term 1/2

Statistics and Data Analytics for Technology

สถิติและการวิเคราะห์ข้อมูลสำหรับงานเทคโนโลยี

Progress
Notional hours: 135 h (online/self-study 75 · in class/lab 60)

Course description

descriptive statistics, probability, probability distributions, sampling, estimation, hypothesis testing, correlation, regression, data preparation, data visualization, and data analysis for technology-based decision making

Thai description

สถิติเชิงพรรณนา ความน่าจะเป็น การแจกแจงความน่าจะเป็น การสุ่มตัวอย่าง การประมาณค่า การทดสอบสมมติฐาน สหสัมพันธ์ การถดถอย การจัดเตรียมข้อมูล การแสดงผลข้อมูล และการวิเคราะห์ข้อมูลเพื่อการตัดสินใจทางเทคโนโลยี

Description source: Curriculum draft (revised 28 Sep 2026)Previous site code: DRT 116

Course learning outcomes (CLO)

CLOOutcomePLO
CLO1Summarise and present data with descriptive statisticsPLO1PLO4
CLO2Use statistical inference to evaluate test resultsPLO1PLO4
CLO3Analyse flight-log data with PythonPLO4

Learning modules

1Data and descriptive statistics
Weeks 1–3 · 27 h
Lesson 90 minquiz3 KU

Online (before class) · 15 h

Study the assigned knowledge units in advance, review media and take the module quiz

In class / field · 12 h

Lab or field practice from worksheets with a safety checklist

Learning evidence: Checked worksheets and quiz results

2Probability and distributions
Weeks 4–6 · 27 h
Lesson 90 minquiz1 KU

Online (before class) · 15 h

Study the assigned knowledge units in advance, review media and take the module quiz

In class / field · 12 h

Lab or field practice from worksheets with a safety checklist

Learning evidence: Checked worksheets and quiz results

3Confidence intervals and hypothesis tests
Weeks 7–9 · 27 h
Lesson 90 minquiz2 KU

Online (before class) · 15 h

Study the assigned knowledge units in advance, review media and take the module quiz

In class / field · 12 h

Lab or field practice from worksheets with a safety checklist

Learning evidence: Checked worksheets and quiz results

4Data analysis with pandas
Weeks 10–12 · 27 h
Lesson 90 minquiz2 KU

Online (before class) · 15 h

Study the assigned knowledge units in advance, review media and take the module quiz

In class / field · 12 h

Lab or field practice from worksheets with a safety checklist

Learning evidence: Checked worksheets and quiz results

5Experiments and interpreting test results
Weeks 13–15 · 27 h
Lesson 90 minquiz3 KU

Online (before class) · 15 h

Study the assigned knowledge units in advance, review media and take the module quiz

In class / field · 12 h

Lab or field practice from worksheets with a safety checklist

Learning evidence: Checked worksheets and quiz results

Assessment (draft)

Labs and worksheets35%
Module quizzes10%
Midterm examination20%
Mini-project or practical exam35%

Knowledge domain

Key references

  1. Montgomery, D. C., & Runger, G. C. (2018). Applied statistics and probability for engineers (7th ed.). Wiley. link
  2. McKinney, W. (2022). Python for data analysis (3rd ed.). O'Reilly. link