Brochure
Enquire
- Chapter 1: Introduction to Statistics and Geography
- Chapter 1: Examples of hypotheses
- Chapter 2: Geographic Data - Introduction
- Chapter 2: Data Types
- Chapter 2: Classification
- Chapter 2: Classification Map Examples
Statistical Problem Solving in Geography
Quick Facts
| particular | details | |||
|---|---|---|---|---|
|
Medium of instructions
English
|
Mode of learning
Self study
|
Mode of Delivery
Video and Text Based
|
Course overview
Statistical geography adds a geographical dimension to statistics. Statistical geography separates the region of interest where figures are collected into geographic categories called statistical areas, which allows the user to see not only how the information varies but also where it differs. Arthur Lembo - Instructor designed the Statistical Problem Solving in Geography online certification, which is delivered by Udemy.
Statistical Problem-Solving in Geography online training comprises more than 11.5 hours of video-based learning resources that focus on providing participants with a detailed understanding of statistical concepts and how they are used to overcome statistical problems in geography to develop their quantitative skills. Statistical Problem-Solving in Geography online classes cover topics such as statistical analysis, point pattern analysis, area pattern analysis, normal distribution, ANOVA, probability, dispersion, descriptive statistics, inferential statistics, and more.
The highlights
- Certificate of completion
- Self-paced course
- 11.5 hours of pre-recorded video content
- Learning resources
Program offerings
- Online course
- Learning resources
- 30-day money-back guarantee
- Unlimited access
- Accessible on mobile devices and tv
Course and certificate fees
Fees information
₹ 449 ₹2,299
certificate availability
Yes
certificate providing authority
Udemy
Who it is for
What you will learn
Problem solving ability
Knowledge of geography
After completing the Statistical Problem Solving in Geography certification course, participants will acquire a thorough understanding of the concepts of geography as well as will learn about the functionalities of geographical data for solving problems in geography and GIS. Participants will explore the strategies involved with statistical analysis, point pattern analysis, area pattern analysis, normal distribution, dispersion, probability, and ANOVA for solving statistical problems. Participants will learn about fundamentals associated with central tendency, data types, descriptive statistics, and inferential statistics.
The syllabus
Basic Statistical Concepts in Geography
Descriptive Problem Solving in Geography
- Chapter 3: Measures of Central Tendency
- Chapter 3 - Measures of Dispersion
- Chapter 3: Shape and Relative Position
- Chapter 3: Considerations for Spatial Data and Descriptive Statistics
- Chapter 4: Descriptive Spatial Statistics - Central Tendency
- Chapter 4: Spatial Dispersion
The Transition to Inferential Problem Solving
- Chapter 5: Probability - Terms and Definitions
- Chapter 5: Probability - Probability Rules
- Chapter 5: Probability - Binomial Distribution
- Chapter 5: Probability - Geometric Distribution
- Chapter 5: Probability - Poisson
- Chapter 5: Probability - Poisson Spatial
- Chapter 6: The Normal Distribution - Introduction
- Chapter 6: The Normal Distribution - Calculation
- Chapter 6: The Normal Distribution - Last Spring Frost Example
- Chapter 8: Estimation in Sampling - Introduction
- Chapter 8: Estimation in Sampling - Central Limit Theorem
- Chapter 8: Estimation in Sampling - Confidence Intervals
- Chapter 8: Estimation in Sampling - Examples
Inferential Problem Solving in Geography
- Chapter 9: Elements of Inferential Statistics - Terms and Concepts
- Chapter 9: Elements of Inferential Statistics - one sample difference of means
- Chapter 10: Two Sample Difference Tests - Introduction
- Chapter 10: Two sample difference of means - calculation
- Chapter 10: Difference of Proportions - calculation
- Chapter 10: Matched Pairs Test
- Chapter 11: ANOVA - Introduction
- Chapter 11: ANOVA - Calculation
- Chapter 11: ANOVA - Examples
Inferential Spatial Statistics
- Chapter 13: General Issues in Inferential Spatial Statistics
- Chapter 14: Point Pattern Analysis - Nearest Neighbor
- Chapter 14: Point Pattern Analysis - Quadrat Analysis
- Chapter 15: Area Pattern Analysis - Join Count
- Chapter 15: Area Pattern Analysis - Moran's I (Introduction)
- Chapter 15: Area Pattern Analysis - Moran's I (conclusion)
Statistical Relationships Between Variables
- Chapter 16: Correlation - Introduction
- Chapter 16: Correlation - Pearson
- Chapter 16: Correlation - Spearman
- Chapter 17: Simple Linear Regression - Introduction
- Chapter 17: Simple Linear Regression - Calculation
- Chapter 17: Simple Linear Regression - Interpretation
- Chapter 18: Multiple Regression - Introduction
Instructors
Dr Arthur Lembo
Professor
SU Salisbury
