Inferential Statistics
Learn fundamental concepts of inferential statistics, from hypothesis testing to regression analysis. Master statistical methods for data analysis.
Learn fundamental concepts of inferential statistics, from hypothesis testing to regression analysis. Master statistical methods for data analysis.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Methods and Statistics in Social Sciences Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.3
(592 ratings)
66,184 already enrolled
Instructors:
English
پښتو, বাংলা, اردو, 3 more
Powered by
What you'll learn
Apply and interpret various statistical tests for hypothesis testing
Conduct and analyze regression models for quantitative data
Perform analysis of variance (ANOVA) for group comparisons
Implement non-parametric tests for non-normal distributions
Use R software for statistical analysis and interpretation
Skills you'll gain
This course includes:
4.8 Hours PreRecorded video
8 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
Closed caption
Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
Created by
Provided by
Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 8 modules in this course
This comprehensive course covers essential concepts in inferential statistics, focusing on making data-driven decisions through statistical testing. Students learn various statistical methods including hypothesis testing, regression analysis, ANOVA, and non-parametric tests. The course emphasizes practical application using R software, enabling learners to perform and interpret statistical analyses for real-world research scenarios. Topics progress from basic significance testing to advanced techniques like multiple regression and factorial ANOVA.
Before we get started...
Module 1 · 1 Hours to complete
Comparing two groups
Module 2 · 5 Hours to complete
Categorical association
Module 3 · 2 Hours to complete
Simple regression
Module 4 · 3 Hours to complete
Multiple regression
Module 5 · 2 Hours to complete
Analysis of variance
Module 6 · 2 Hours to complete
Non-parametric tests
Module 7 · 3 Hours to complete
Exam time!
Module 8 · 1 Hours to complete
Fee Structure
Instructors
Expert in Quantitative Measurement and Learning Analytics Advancing Educational Research Methods
Annemarie Zand Scholten is an Assistant Professor specializing in quantitative measurement within psychology at the University of Amsterdam. Her research interests focus on integrating representational measurement theory with psychometric latent variable modeling to evaluate psychological properties and minimize inferential errors in parametric testing. Recently, she has developed a keen interest in Learning Analytics, exploring how automated feedback on learners' online activities can enhance academic performance and motivation. Annemarie has taught various courses, including Methods and Statistics in Educational Sciences, and has coordinated research project courses. Her work emphasizes the importance of effective measurement techniques and their application in educational settings, contributing significantly to the field of educational research.
Statistical Ecology Expert Pioneering Animal Movement Analysis and Research Reproducibility
Emiel van Loon serves as an Assistant Professor specializing in statistical ecology at the University of Amsterdam, where he balances teaching applied statistics to ecology and earth science students with innovative research in animal movement and distribution analysis. His work focuses on developing statistical and measurement theories while advocating for enhanced research reproducibility through standardized observation techniques and improved data management. Through his dedication to both teaching and research, he contributes significantly to the advancement of ecological studies by implementing better documentation practices and refined analytical methods for understanding animal behavior patterns.
Testimonials
Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.
4.3 course rating
592 ratings
Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.