Python Statistics

TRAINING COURSE

Details Audience and Pre-Requisites Course Outline / Curriculum Schedule Dates and Booking Enquiry

Details

This is a one-day course for covering inferential and descriptive statistical concepts and their implementation using Python. This is useful for anyone needing to do hypothesis testing or who who deals with data on a regular basis and need to analyze it to derive insights and solve problems.

 

This course builds on existing Python knowledge to explore the tools Python has to conduct statistical analyses and operations.

Learners will conduct descriptive and inferential calculations on data sets using Python. Analyzing statistics using Python offers a rich ecosystem of libraries tailored for various statistical tasks, making it accessible to users with diverse backgrounds. Python's intuitive syntax and extensive community support contribute to its ease of use, while its flexibility enables seamless integration with other tools and platforms for comprehensive data analysis pipelines. With powerful visualization libraries, Python facilitates interactive exploration and effective communication of statistical findings, enhancing the efficiency and depth of statistical analysis workflows. 

 

Delivery Methods

Delivery Method Duration
Classroom
Instructor-led classroom-based training. Classes are scheduled at various conference centres in the Sandton area or your premises. Stationary and printed manuals or online resources are included. Refreshments, including 2 tea breaks and a cooked meal for lunch are provided. Training is between 9 am to 4 pm.
Classroom
1 days Get a Quote
Live Virtual Training
This course is delivered live via Microsoft Teams. You will be able to see and hear the instructor, view their whiteboard, and ask questions or communicate in the chat. Attend from the comfort of your own home or private office.
Live Virtual Training
1 days Get a Quote

Discounts Available

Brochure:

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Information may change without notice.

Audience

This course is for Data Scientists, Data Analysts, Business Analysts, Researchers and students, or anyone who deals with data regularly and needs to analyze it to derive insights and solve problems.

Pre-Requisites

Core mathematics to matric level

Python programming knowledge covered in our Python Programming 5-day course

Basic statistics knowledge covered in our Introduction to Statistics course

Data analysis concepts covered in our Python Pandas and Data Visualisation with Python

Course Outline / Curriculum

  • Introduction to Python statistics 

  • Probability 

    • Discrete probability 

    • Monte Carlo simulations for categorical data 

    • Independence 

    • Conditional probabilities 

    • Addition and multiplication rules 

    • Combinations and permutations 

    • Infinity in practice 

    • Continuous probability 

    • Theoretical continuous distributions 

    • Monte Carlo simulations for continuous variables 

    • Continuous distributions 

  • Random variables 

    • Random variables 

    • Sampling models 

    • The probability distribution of a random variable 

    • Distributions versus probability distributions 

    •  Notation for random variables 

    •  The expected value and standard error 

    •  Central Limit Theorem 

    •  Statistical properties of averages 

    •  Law of large numbers 

Schedule Dates and Booking

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