Python Statistics

Python Statistics

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	1 days	Get a Quote
Live Virtual Training	1 days	Get a Quote

Discounts Available

Brochure:

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

There are currently no scheduled dates.

Please note that this course needs a minimum of 6 delegates to schedule a course. You can choose to be added to the waiting list by clicking the button below, and we will contact you when we have enough delegates interested. Should we not get enough delegates, we will refund or credit your paid booking.

Add me to the waiting list

Should you need this course urgently, the following options are available:

Pay for 6 delegates (whether you have them or not) and we will schedule the course as soon as possible.
If you have fewer delegates and cannot pay for 6, we can negotiate a shortened course where some of the time will be spent in blended learning - watching videos and doing tutorials and exercises with some contact time with the trainer. We would want to discuss what your core needs are so that we cover those aspects. You need to have paid for 3 delegates at least.

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