Completion

CERTIFICATE

MathTrackX: Probability

Name: MathTrackX: Probability
Price: 8225 INR

This course is part of MathTrackX.

Course Cost

₹ 8,225

Beginner

Skill Level

4 Weeks

Self-paced lessons

This comprehensive course, part of the MathTrackX XSeries Program, provides a solid foundation in probability fundamentals. Students explore discrete and continuous random variables, their applications in modeling random processes, and the framework for statistical inference. Led by experts from the University of Adelaide's School of Mathematics and Maths Learning Centre, participants develop practical skills in calculating probabilities, expected values, and standard deviations. The course emphasizes real-world applications and problem-solving, making complex probability concepts accessible and applicable.

Dr David Butler

Dr Melissa Humphries

English

Dr David Butler

Dr Melissa Humphries

What you'll learn

Calculate and interpret probabilities in various real-world contexts

Differentiate between discrete and continuous random variables

Compute expected values variance and standard deviation of random variables

Analyze the effects of linear changes on statistical measures

Calculate quantiles of normal distribution

Apply probability concepts to solve everyday scenarios

Skills you'll gain

Probability

Random Variables

Statistical Inference

Mathematical Modeling

Data Analysis

Discrete Variables

Continuous Variables

Standard Deviation

Normal Distribution

This course includes:

PreRecorded video

Graded assignments, Exams

Access on Mobile, Tablet, Desktop

Limited Access access

Shareable certificate

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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 4 modules in this course

This comprehensive probability course covers fundamental concepts including discrete and continuous random variables, probability calculations, expected values, variance, and standard deviation. Students learn to interpret probabilities in various contexts, understand the differences between variable types, and apply mathematical concepts to real-world scenarios. The course emphasizes practical applications and problem-solving skills, featuring instruction from University of Adelaide experts.

Basic probability

Module 1

This module introduces fundamental concepts of probability and counting techniques. Students will learn to apply product and sum principles of counting, work with permutations and combinations, understand probabilities in random experiments, conceptualize events as sets of outcomes, use Venn diagrams for compound events, understand independent, mutually exclusive, and conditional events, apply the addition law of probability, and use tree diagrams for conditional probability problems. The module builds essential foundations for probabilistic reasoning.

Skills you'll gain

Counting Techniques

Event Probability

Conditional Analysis

Discrete random variables

Module 2

This module explores the concept of discrete random variables and their probability distributions. Students will learn to distinguish between discrete and continuous random variables, understand probability distributions and their properties, interpret various representations of discrete random variables, calculate statistical measures (mode, median, expected value, variance, standard deviation), understand relationships between random variables and their functions, recognize Bernoulli and Binomial experiments, and apply these concepts to solve practical problems.

Skills you'll gain

Distribution Analysis

Statistical Measurement

Probability Modeling

Continuous random variables

Module 3

This module focuses on continuous random variables and their probability density functions. Students will learn to understand and verify valid probability density functions, calculate statistical measures for continuous random variables, understand relationships between random variables and their functions, recognize properties of the normal distribution, apply the 68:95:99.7 rule, use standard normal transformation, find probabilities and quantiles with technology, and apply derivative rules and special functions to solve probability problems.

Skills you'll gain

Density Functions

Normal Distribution

Quantile Calculation

Assessment

Module 4

This module consists of a timed exam designed to evaluate students' understanding of probability concepts covered throughout the course. The assessment tests knowledge of basic probability, discrete random variables, and continuous random variables. This comprehensive evaluation helps students gauge their mastery of probabilistic reasoning and its applications to real-world problems.

Skills you'll gain

Probability Application

Time Management

Comprehensive Analysis

Fee Structure

Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: MathTrackX

Reviews

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Faculties

These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.

Courses

Dr David Butler

David Butler serves as Lecturer and Coordinator of the Maths Learning Centre and Writing Centre at the University of Adelaide, where he specializes in helping students develop effective mathematical learning strategies across all disciplines. His academic background combines pure mathematics, with a PhD in Finite Geometry, and educational expertise through a Graduate Diploma in Education. As a former high school mathematics teacher, he brings practical pedagogical experience to his university role. His innovative approach emphasizes the integration of play and artistic elements in mathematical education, making complex concepts more accessible to students. At the Maths Learning Centre, he focuses on developing students' mathematical thinking skills and confidence, working across diverse academic disciplines to support students in mastering course-specific mathematical concepts. His passion for mathematics education extends beyond the classroom through his active engagement in mathematical education communities and his development of creative learning resources.

Courses

Dr Melissa Humphries

Melissa Humphries serves as Senior Lecturer in Statistics at the University of Adelaide, where she combines her unique background as a former chef with expertise in statistical analysis and cognitive modeling. After completing her PhD in Statistics and Mathematical Psychology from the University of Tasmania in 2017, she has built an impressive career spanning teaching and research. Her work focuses on applied statistics across diverse fields including forensic science, defense, psychology, and wastewater analysis, with particular emphasis on developing tools that support expert decision-making. As a lecturer, she coordinates multiple courses including second-year undergraduate statistics and has helped develop innovative online learning units in Bayesian reasoning. Her teaching portfolio includes Data Literacy, Statistical Analysis and Modeling, and Research Methods and Statistics. Recently named a Superstar of STEM for 2023-24, she advocates for making academia more accessible while maintaining an active research program in Bayesian inference, stochastic processes, and large dataset management. Her expertise extends to analyzing spatially and temporally autocorrelated data, contributing to fields ranging from astrophysics to forensic anthropology, while her background in psychology enhances her ability to communicate complex technical concepts to diverse audiences.

Courses

Dr Danny Stevenson

Danny Stevenson serves as Senior Lecturer in Pure Mathematics at the University of Adelaide, where he has established himself as a leading researcher in category theory and homotopy theory. After completing his PhD at Adelaide in 2000, he gained international experience through academic positions in Scotland and the United States before returning to his alma mater. His research focuses on the intersection of higher category theory, abstract homotopy theory, and the emerging field of ∞-categories. As a member of the Pure Mathematics research group at Adelaide's School of Mathematical Sciences, he contributes to fundamental research in gerbes and non-abelian cohomology. His work has earned recognition in the mathematical community, particularly for his contributions to understanding inner anodyne maps and their properties in higher categorical structures. Through his position at Adelaide, he continues to advance the theoretical foundations of mathematics while contributing to the university's prestigious research tradition in pure mathematics.

Courses

Nicholas Crouch

Nicholas Crouch serves as Associate Lecturer at the University of Adelaide's Maths Learning Centre, where he has been helping students master mathematical concepts across diverse disciplines since 2009. After completing his master's degree in Pure Mathematics with a focus on algebraic and computational number theory, he has dedicated his career to mathematics education and student support. As a core member of the Maths Learning Centre team alongside David Butler, he provides essential guidance to students in subjects ranging from engineering mathematics to statistical analysis in psychology and economic derivatives. His role at the Drop-In Centre creates a safe learning environment where students can discuss mathematical challenges with friendly tutors either face-to-face or online. Beyond individual tutoring, he contributes to the broader mission of the Maths Learning Centre, which exists to help all University of Adelaide students succeed in learning and applying mathematics in their coursework. His work spans the Employability, Careers and Student Academic Skills unit, where he continues to make mathematics accessible and understandable to students across all disciplines.

Courses

Dr Brendan Harding

Brendan Harding currently serves as a Lecturer at Victoria University of Wellington, following his role as Research Associate at the University of Adelaide. His academic journey has focused on computational mathematics and fluid dynamics, with particular expertise in numerical methods for partial differential equations. His PhD research developed fault-tolerant algorithms for supercomputers, leading to significant publications in high-performance computing. His current research centers on microfluidic applications, specifically studying particle behavior in curved ducts with applications in cancer detection through circulating tumor cell identification. His work spans theoretical fluid mechanics, computational methods, and fractal geometry, with over 494 citations reflecting his significant impact in the field. His research portfolio includes groundbreaking work on inertial focusing of particles in curved microfluidic ducts, which has important applications in biomedical diagnostics. Beyond his primary research, he has contributed to diverse areas including fault-tolerant computation, sparse grid techniques, and fractal geometry, demonstrating his versatility as a computational mathematician. His expertise extends to creating mathematical visualizations, combining technical precision with artistic representation through programming.

Beginner

Skill Level

4 Weeks

Self-paced lessons

Course Cost

₹ 8,225

Completion

CERTIFICATE

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.

MathTrackX: Probability

What you'll learn

Skills you'll gain

This course includes:

Get a Completion Certificate

Get a Completion Certificate

Top companies offer this course to their employees

There are 4 modules in this course

Basic probability

Skills you'll gain

Discrete random variables

Skills you'll gain

Continuous random variables

Skills you'll gain

Assessment

Skills you'll gain

Fee Structure

Reviews

Faculties

Frequently asked Questions

What are the prerequisites for this course?

Who should take this course?

What will I learn in this course?