Guides ยท Math
Linear Regression Basics
Fit a line to data
Linear regression estimates relationships between variables by fitting a line that minimizes squared errors, using coefficients, intercept, and evaluating fit.
- slope
- intercept
- least squares
- residuals
- r-squared
Model
Predict y from x with y = b0 + b1x; extend to multiple x.
Fit
Use least squares to minimize residuals; check assumptions.
Evaluate
Check residuals, R-squared, and avoid extrapolation.
Keep Exploring
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Interpreting Statistics
Statistics become more useful when you read averages, spread, sample size, and uncertainty together instead of in isolation.
Why it matters
Numeracy
Numeracy is the practical ability to read numbers, compare claims, and make better everyday decisions.
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Mental Math Techniques
Mental math gets easier when you break numbers apart, round strategically, and reuse familiar patterns.
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Understanding Probabilities
Probability becomes more intuitive once independence, uncertainty, and expected value are tied to real decisions.