课程信息 | Environmetrics

UMTMOOC MICRO-CREDENTIAL MICRO-CREDENTIAL BOMBA AWARD

UMTMOOC Micro-Credential MOOC DALAMAN SEMESTER 2 2024/2025 SEMESTER 1 2025/2026 SEMESTER 2 2025/2026

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General information and other important information about this course

WELCOME MESSAGE TO NEW STUDENT

COURSE ANNOUNCEMENT

BACKGROUND PROFILE

COURSE LEARNING OUTCOME

MEET YOUR COURSE COORDINATOR (DR. KU)

UNIT 01

1.1 What is Environmetric (10 MINS)

1.2 Environmetric Data Process (10 MINS)

1.3 Flow Chart of Data Analysis (10 MINS)

1.4 Probability Distribution (10 MINS)

1.5 Type of Data &amp; Measurement Scales (10 MINS)

1.6 Descriptive Analysis (10 MINS)

1.7 Inferential Analysis vs. Descriptive Analysis (10 MINS)

Midterm Quiz

UNIT 2: DATA WRANGLING

2.1 What is R Software (10 MINS)

2.4 How to import data from MS Excel into R studio (10 MINS)

2.5 Library Package Installation (ADDTIONAL INFORMATION)

How to perform Barplot using ggplot2 (10 MINS)

ADDITIONAL LEARNING

2.3 Introduction to R studio interface (ADDITIONAL INFORMATION))

2.2 R software Installation procedure (ADDITIONAL INFROMATION)

UNIT 3: DATA VISUALIZATION

LECTURE NOTE

Data Visualization using ggplot2 in R Studio [1 hour &amp; 30 minutes]

UNIT 4: PARAMETRIC VS. NON PARAMETRIC

4.1 LECTURE NOTE

4.1.1 PARAMETRIC VS NON-PARAMETRIC (1 HOUR 30 MINUTES)

UNIT 5: HYPOTHESIS TESTING

5.1 LECTURE NOTE

HYPOTHESIS TESTING [1 Hour and 30 minutes]

5.2 LECTURE VIDEO

How hypothesis testing affecting our environmental result? [1 Hour]

UNIT 6: T-TEST (PARAMETRIC TYPE ANALYSIS)

LECTURE NOTE

6.1 ONE, INDEPENDENT AND DEPENDENT SAMPLE T -TEST (1 HOUR 30 MINUTES)

3.1: Statistical Table

UNIT 7: ANALYSIS OF VARIANCE (PARAMETRIC TYPE ANALYSIS)

LECTURE NOTE

ANALYSIS OF VARIANCE (1 HOUR 30 MINUTES)

UNIT 8: MANN - WHITNEY & WILCOXON (NON PARAMETRIC TYPE ANALYSIS)

LECTURE NOTE

MANN WHITNEY &amp; WILCOXON (1 HOUR 30 MINUTES)

UNIT 9: KRUSKAL - WALLIS (NON PARAMETRIC TYPE ANALYSIS)

LECTURE NOTE

KRUSKAL WALLIS (1 HOUR 30 MINUTES)

UNIT 10: CORRELATION ANALYSIS

LECTURE NOTE

10. 1 PEARSON AND SPEARMAN (1 HOUR 30 MINUTES)

UNIT 11: REGRESSION ANALYSIS

LECTURE NOTE

11. 1 REGRESSION ANALYSIS (1 HOUR 30 MINUTES)

UNIT 12: PRINCIPAL COMPONENT ANALYSIS

12. 1 LECTURE NOTE

12.1.1 LECTURE NOTE_PRINCIPAL COMPONENT ANALYSIS (1 HOUR 30 MINUTES)

UNIT 13: HIERARCHICHAL AGGLOMERATIVE CLUSTER ANALYSIS

LECTURE NOTE

CLUSTER ANALYSIS (1 HOUR 30 MINUTES)

UNIT 14: DISCRIMINANT ANALYSIS

LECTURE NOTE

DISCRIMINANT ANALYSIS (1 HOUR 30 MINUTES)

1.5 Type of Data & Measurement Scales (10 MINS)

Data Visualization using ggplot2 in R Studio [1 hour & 30 minutes]

MANN WHITNEY & WILCOXON (1 HOUR 30 MINUTES)