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Statistics for Analytics and Data Science
Build or advance your career in Data Science and Analytics with this practical, comprehensive, self-paced course by Analytics Leap.
Data is everywhere, and with the demand for data professionals skyrocketing every year, many people are now learning statistics so they can learn how to collect, analyse, and interpret data.
If you’re reading this, you’re probably one of those people.
And whether you’re a seasoned professional or you’re someone just now realising the potential of a career path in data science and analytics, this course will help you learn and understand statistics in a way that makes you an indispensable part of any business and organisation.
This course comes with self-paced video modules, practical exercises and useful examples you can practice with and explore.
Everything is structured and provided to you in a comprehensive, student-friendly manner so anyone from beginners to professionals can use it to advance their skills and get real-world statistics experience.
This course is your complete guide to the fundamentals of statistics and probability
1. Data Exploration & Descriptive Statistics
We’ll start by discussing the various descriptive statistics, how data can be visually represented using frequency tables, and the measures of central tendency (and their interpretation.)
2. Correlation & Linear Regression
We’re going to introduce correlation and OLS regression, explore how they can be calculated in Excel through different formulas, and learn how to make interpretations and conclusions based on the data we’ve received.
3. Introduction to Probability Theory
This module will focus on Probability theory – sample space, events, randomness, and basic set theory. Later in the module, we’re going to discuss conditional probability and introduce mutually exclusive events.
4. Probability Distributions
Learn the difference between a continuous and a discrete distribution focusing on Normal and Binomial distributions.
5. Sampling Distributions
Learn the concept of Central Limit theorem, why sampling is such an important part of statistics, and how the Central Limit theorem is linked to normal distribution.
6. Confidence Intervals
Learn how to use intervals to determine the centre of a distribution as opposed to a point estimate (such as the mean.) Learn more about the relationship between significance level (alpha) and the confidence level.
7. Significance Tests
Learn what a significance test is, what it isn’t, and how to define the null and alternate hypotheses correctly - getting the direction and “tails” of your distribution correct. Finally, you’ll learn about Type I and Type II errors (with examples and interpretations.)
Who is this course for?
1. Aspiring Data Scientists, Machine Learning Engineers, Business Analysts and Data Analysts
2. Professionals looking to expand their analytical skill-set
3. Academics looking for a crash course in statistics for research
4. Those who seek a better analytical understanding of the world around us
5. Business Executives looking to fluently speak the language of data and insights
6. Students looking to ace fundamental statistics and probability courses
1. Microsoft Excel installed on the computer
2. Basic Mathematics and Algebra
Questions and answers
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Will you provide a certificate after completion?
Hi, yes course completion certificate will be issued at the end of the course. Thanks.This was helpful. Thank you for your feedback.
I'd like to know how long will the course be accessible for?
Hi, you will get life time access for the course.This was helpful. Thank you for your feedback.
Which institution will issue the certificate?
It will be issued by Analytics Leap.This was helpful. Thank you for your feedback.
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