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Statistics and Probability for Data analytics & Data science
Rating: 4.5 out of 5(4 ratings)
13 students

Statistics and Probability for Data analytics & Data science

Master your foundations in Statistics and probability for data insights in the field of Data analytics and Data science
Created bySubham Mishra
Last updated 4/2025
English

What you'll learn

  • The learners will get a comprehensive knowledge about fundamentals of statistics and probability.
  • In-depth knowledge of descriptive statistics including levels of measurement, measures of central tendency and variability, shape of distribution
  • Five point summary and Outlier detection using box plot method
  • Univariate and Bi variate data analysis such as coefficient of deviation, covariance, correlation, scatter plots, etc.
  • Permutation and combination
  • Probability and its various concepts such as its set operations, dependent events, total probability and Bayes theorem
  • Understanding the concepts of discrete and continuous variable probability distributions including cumulative probability distributions
  • Different probability distributions for both discrete and random variable such as Uniform, Bernouille, Binomial, Poissons, Normal, Students T, Chi square and F.
  • Sampling distributions, margin of error, confidence interval and its various cases for one sample and two sample
  • Inferential statistics including hypothesis testing, one tailed and two tailed test, different test of mean, chi square and ANOVA testing

Course content

9 sections • 45 lectures • 4h 53m total length

  • Welcome1:22
  • What is Statistics3:32
  • Sampling methods4:34
  • Quiz

Requirements

  • No prerequisite or maths background required for this course as every concepts has been explained in a very simplified manner to make your concepts crystal clear.

Description

Unlock the power of data with our comprehensive course: Statistics and Probability for Data Analytics & Data Science. In an era where data is the new oil and data drives decision-making, mastering these foundational concepts is of core importance for anyone looking to excel in the field of data analytics, business analytics or data science.

So, anyone who want to acquire these necessary skills for a bright career prospect in these fields, then, you’ve come to the right place my friend!

This 45 chapters course will help you to master your foundations in the field of statistics and probability which will help you to take data driven decisions appropriately. The course provides crisp yet comprehensive and detailed videos for every concept in the field of statistics and probability followed by quizzes with solutions to test the clarity of your concepts.

So, below is the overview of what we will be covering in this course:

  • Fundamentals of statistics

  • Deep dive into descriptive statistics including univariate data analysis with the help of levels of measurement, measures of central tendency, measures of variability and shape of distribution for proper data analysis

  • Five-point summary and Outlier detection using box plot method

  • Bi variate data analysis such as coefficient of deviation, covariance, correlation (including both Pearson correlation and spearman rank correlation), scatter plots, etc.

  • Permutation and combination along with their various cases and examples

  • Probability and its various concepts such as its set operations, dependent events, total probability and Bayes theorem

  • Understanding discrete and continuous variable probability distributions including cumulative probability distributions

  • Different probability distributions for both discrete and random variable such as Uniform, Bernoulli, Binomial, Poisson, Normal, Students T, Chi square and F.

  • Use cases and examples of each probability distributions

  • Sampling distributions of mean, margin of error, point estimate, confidence interval and its various cases for one sample and two sample

  • Inferential statistics including hypothesis testing, one tailed and two tailed test, different test of mean, chi square and ANOVA testing

  • Practical applications of one tailed and two tailed test

  • Real life scenarios of type 1 and type 2 error for better clarity

So, enroll today guys and master your concepts in statistics and probability.

Who this course is for:

  • 1. Aspiring Data Analysts, Business Analysts and Data Scientists who are beginning their career journey looking to build a strong foundation in statistical methods.
  • 2. Working Professionals in Data-Centric Roles where data analytics plays a pivotal role in decision-making.
  • 3. Professionals who wish to deepen their statistical knowledge to enhance their ability to solve business problems and communicate data insights effectively
  • 4. Learners who are keen to acquire practical skills to apply statistics and probability in analyzing and interpreting complex datasets
  • 5. Students with Academic Interests in Statistics and Data Science who wish to integrate statistical techniques into their research or projects.
  • 6. Intermediate Learners who wish to refine their expertise in statistics and probability

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