Statistics & Probability For Analytics Interviews

Statistics & Probability for Analytics Interviews is simply a system way of 13 lessons that build a complete, interview-ready knowing of the topic. Work done them successful order, past usage the quiz and flashcards successful each instruction to revise.

What this people covers

Descriptive Statistics: Centre, Spread & Shape - Mean, median, variance, modular deviation and skew, and what each hides.
When the Average Lies: Skew, Outliers & Median vs Mean - Why the mean misleads connected skewed business data, pinch Indian net and order-value examples.
Probability Essentials: Rules, Conditional Probability & Bayes' Theorem - The probability an expert is tested on, including a worked Bayes calculation.
The Distributions Analysts Actually Use - Normal, binomial, Poisson and power-law, each matched to the information it describes.
Sampling, Sampling Bias & the Central Limit Theorem - How samples spell wrong, and why sample intends behave predictably moreover erstwhile information does not.
Confidence Intervals & Margin of Error, Explained Plainly - What a assurance interval does and does not claim, and really to study one.
Hypothesis Testing: Null, Alternative, p-Values & Significance - The afloat testing logic, and the correct one-sentence mentation of a p-value.
Type I & Type II Errors, Statistical Power and Sample Size - Both correction types, the business costs of each, and really powerfulness drives sample size.
Choosing the Right Test: t-Test, Chi-Square & Analysis of Variance - A determination character from information type and group count to the correct test.
Non-Parametric Tests: What to Use When Assumptions Break - Rank-based alternatives for erstwhile normality aliases adjacent variance fails.
Correlation, Regression & the Limits of Both - Reading relationship and a fitted statement honestly, including wherever some break down.
Correlation vs Causation: Confounders & Study Design - Confounding, spurious correlation, and the designs that support a causal claim.
Statistical Traps: p-Hacking, Multiple Comparisons & Simpson's Paradox - How analyses spell incorrect invisibly, each shown pinch a reversal you tin reproduce.