Data Analysis

Statistics for Data Science

6 Seasons · 34 Episodes · 0/34 watched

A binge-worthy 6-season journey through Statistics for Data Science. Learn to turn raw numbers into decisions — one episode at a time.

About this course

A binge-worthy 6-season journey through Statistics for Data Science. Learn to turn raw numbers into decisions — one episode at a time.

Statistics for Data Science is a free, self-paced data analysis course from Crookshanks' Academy. It contains 34 video lessons organised into 6 seasons, each with study notes and a practice task. Track your progress as you go and earn a certificate of completion when you finish every episode.

What you'll learn

Season 1

Statistics For Data Analytics | Complete Syllabus | Data Science | Statistics Tutorial | Part 1
Types of Statistics | Descriptive | Inferential | Statistics for Data Science | Statistics Tutorial
Types of Data | Types of Variables | Statistics for Data Science | Part 3 | Statistics Tutorial
Population and Sample | Statistics for Data Science | Part 4 | Statistics Tutorial
Sampling Techniques | Statistics for Data Science | Statistics Tutorial Part 5
Statistical Data Analysis Complete Steps | Statistics for Data Science | Statistics Tutorial Part 6

Season 2

Measures of Central Tendency | Mean, Median, Mode | Statistics Tutorial Part 7
Measures of Dispersion | Variance, Standard Deviation, Range, IQR, Quartiles, Percentiles | Part 8
Frequency | Relative Frequency | Cumulative Frequency | Statistics Tutorial Part 9
Must know Visualization in Statistics | Descriptive Statistics | Ultimate Guide !! | Part 10
Outliers | Removing Outliers | Outliers detection | Impact on Data Analysis | Statistics Tutorial
Correlation | Covariance | Causation | Difference between them | Statistics

Season 3

Probability Concepts for Data Analysis and Data Science | Statistics for Data Science
Types of Events | Probability | Statistics Tutorial | Joint | Disjoint | Independent | Dependent
Conditional Probability | Statistics Tutorial
Bayes Theorem | Conditional Probability | Statistics Tutorial
PMF | PDF | Probability Distributions | Probability Mass Function | Probability Density Function
Bernoulli Distributions | Binomial Distributions | Discrete Probability Distributions

Season 4

Uniform Distribution | Continuous Distribution | Statistics Tutorial | Probability Distribution
Normal Distributions | Standard Normal Distributions | Z Distributions | Z Score
Standardisation | Normalisation | Probability Distributions | Feature Scaling
Empirical Rule | 68-95-99.7 Rule | Normal Distributions | Statistics Tutorial
Inferential Statistics | Point Estimation | Interval Estimation | Statistics Tutorial
Confidence Interval | Interval Estimation | Margin of Error | Statistics Tutorial

Season 5

Student's T Distribution | Z Distribution | T test | Statistics Tutorial
Hypothesis Testing| Null and Alternate Hypothesis | Level of Significance | P Value | Statistics
Type 1 and Type 2 Error | Hypothesis Error | Statistics Error
One tailed and Two tailed Tests | Hypothesis Testing | Detailed Explanation with Example
Z Test hypothesis Testing | Types of Z Test | Explanation with example | Statistics
Complete STATISTICS for Data Science | Data Analysis | Full Crash Course

Season 6

Statistics Project On Hypothesis Testing You NEED In Your Portfolio | Data Analytics Project
T Test Hypothesis Testing | Independent and Paired T Test | Statistics Tutorial
ANOVA Test | F Statistics | One Way ANOVA | Two Way ANOV | Statistics Tutorial
Chi Square Test | Test for Independence | Goodness of Fit Test | Statistics Tutorial