Statistics for Data Science - Module 3 | Random Variables & Probability Distributions | @SCALER

Join Sumit Shukla (DSML Educator, SCALER) as he unravels the mysteries behind these powerful statistical tools and show you how they can empower you to make data-driven decisions and predictions with confidence.

Whether you're just starting your data science journey or looking to brush up on these fundamental concepts, this module is your stepping stone towards mastering the art of extracting valuable insights from data. Don't forget to like, subscribe, and hit the notification bell to stay updated as we progress through this comprehensive playlist!

Topics Covered -
00:24 - What is Probability Distributions
07:56 - Continuous Random Variables
17:24 - Types of Discrete Random Variables
20:42 - Binomial Experiment
48:30 - Scaling
1:19:07 - Examples
1:40:30 - Inferential Statistics

What is Statistics?
Statistics is the science of collecting, organizing, interpreting, analyzing, and presenting data. It involves the study of data patterns, distributions, and relationships to draw meaningful conclusions and make informed decisions. In essence, statistics provides the tools and techniques to transform raw data into valuable insights.

How important is Statistics for Data Science?
Statistics is fundamental to data science as it underpins the entire data analysis process. It helps in understanding data distributions, making data-driven decisions, and evaluating the effectiveness of models. In data science, statistics is not just important; it's indispensable for extracting meaningful insights from data.

What is Data Science?
Data science is an interdisciplinary field that involves the use of various techniques, algorithms, processes, and systems to extract valuable insights, knowledge, and predictions from structured and unstructured data. It combines elements of statistics, mathematics, computer science, domain expertise, and data engineering to analyze, interpret, and solve complex problems, make data-driven decisions, and drive innovation across various industries.

What is Inferential Statistics?
Inferential statistics is a branch of statistics that involves drawing conclusions, making predictions, or generalizing from a sample of data to a larger population. It is a fundamental aspect of statistical analysis used in various fields, including science, business, social sciences, and data science. Inferential statistics allows us to make inferences or hypotheses about a population based on the data collected from a sample of that population.

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[shaktithapa]

The way you are teaching really Great.

[manjusingh-rvhj]

Very informative, i have watched many lectures but this is awesome .