Most Important Statistics Techniques

1. Linear Regression

[{"selector":"#anim-1815d86b-a625-47f0-975d-f5496782a318","keyframes":[{"offset":0,"transform":"translate3d(0, -950.42725%, 0)","easing":"cubic-bezier(.5, 0, 1, 1)"},{"offset":0.29,"transform":"translate3d(0, 0%, 0)","easing":"cubic-bezier(0, 0, .5, 1)"},{"offset":0.45,"transform":"translate3d(0, -267.2601427%, 0)","easing":"cubic-bezier(.5, 0, 1, 1)"},{"offset":0.61,"transform":"translate3d(0, 0%, 0)","easing":"cubic-bezier(0, 0, .5, 1)"},{"offset":0.71,"transform":"translate3d(0, -90.8608451%, 0)","easing":"cubic-bezier(.5, 0, 1, 1)"},{"offset":0.8,"transform":"translate3d(0, 0%, 0)","easing":"cubic-bezier(0, 0, .5, 1)"},{"offset":0.85,"transform":"translate3d(0, -34.120338275%, 0)","easing":"cubic-bezier(.5, 0, 1, 1)"},{"offset":0.92,"transform":"translate3d(0, 0%, 0)","easing":"cubic-bezier(0, 0, .5, 1)"},{"offset":0.96,"transform":"translate3d(0, -14.826665099999998%, 0)","easing":"cubic-bezier(.5, 0, 1, 1)"},{"offset":1,"transform":"translate3d(0, 0%, 0)","easing":"cubic-bezier(0, 0, .5, 1)"}],"delay":0,"duration":1600,"fill":"both"}]

2. Classification

[{"selector":"#anim-369063dc-32b8-400c-9873-d734ff04d4d0","keyframes":{"opacity":[0,1]},"delay":0,"duration":600,"easing":"cubic-bezier(0.2, 0.6, 0.0, 1)","fill":"both"}] [{"selector":"#anim-316fd897-02dc-456d-af12-6b3128f574e6","keyframes":{"transform":["translate3d(-115.87301%, 0px, 0)","translate3d(0px, 0px, 0)"]},"delay":0,"duration":600,"easing":"cubic-bezier(0.2, 0.6, 0.0, 1)","fill":"both"}]

3. Resampling

[{"selector":"#anim-0b30e1ed-8aea-4f2a-94f1-0dbab531ee67","keyframes":[{"transform":"scale(1)","offset":0},{"transform":"scale(1.5)","offset":0.33},{"transform":"scale(0.95)","offset":0.66},{"transform":"scale(1)","offset":1}],"delay":0,"duration":1450,"easing":"ease-in-out","fill":"both","iterations":1}]

4. Shrinkage

[{"selector":"#anim-e889d7a3-cc0f-4749-bb2e-64d7bba03f04","keyframes":{"opacity":[0,1]},"delay":0,"duration":600,"easing":"cubic-bezier(0.2, 0.6, 0.0, 1)","fill":"both"}] [{"selector":"#anim-9ec68ffb-fb9e-4ed4-837c-3bedd02c9cde","keyframes":{"transform":["translate3d(114.92064%, 0px, 0)","translate3d(0px, 0px, 0)"]},"delay":0,"duration":600,"easing":"cubic-bezier(0.2, 0.6, 0.0, 1)","fill":"both"}]

5. Dimension Reduction

[{"selector":"#anim-2bc2d638-6d66-4259-8d74-07992acf9694","keyframes":{"transform":["translate3d(-105.66038%, 0px, 0)","translate3d(0px, 0px, 0)"]},"delay":0,"duration":1000,"easing":"cubic-bezier(.2, 0, .8, 1)","fill":"both"}] [{"selector":"#anim-09436e61-827e-4b5c-a468-0d7a25cf1fb4","keyframes":{"transform":["rotateZ(-180deg)","rotateZ(0deg)"]},"delay":0,"duration":1000,"easing":"cubic-bezier(.2, 0, .5, 1)","fill":"forwards"}]

(a) Step function (b) Piecewise Function

[{"selector":"#anim-d23e7ea2-4483-4bfa-be17-b0338f6210a5","keyframes":{"opacity":[0,1]},"delay":0,"duration":600,"easing":"cubic-bezier(0.2, 0.6, 0.0, 1)","fill":"both"}] [{"selector":"#anim-209ef318-dc98-4882-b772-3fe3bb5259ec","keyframes":{"transform":["translate3d(115.28663%, 0px, 0)","translate3d(0px, 0px, 0)"]},"delay":0,"duration":600,"easing":"cubic-bezier(0.2, 0.6, 0.0, 1)","fill":"both"}]

7. Unsupervised Learning

[{"selector":"#anim-044736e0-1449-44ab-a301-f8c35e75433f","keyframes":{"transform":["translate3d(106.66666%, 0px, 0)","translate3d(0px, 0px, 0)"]},"delay":0,"duration":600,"easing":"cubic-bezier(0.4, 0.4, 0.0, 1)","fill":"both"}] [{"selector":"#anim-dda230df-ae46-4dd4-a705-c254550bf7f6","keyframes":{"opacity":[0,1]},"delay":0,"duration":600,"easing":"cubic-bezier(0.4, 0.4, 0.0, 1)","fill":"both"}] [{"selector":"#anim-63264c72-29cd-4b7e-b9ec-0d3ecaf56c0b","keyframes":{"transform":["scale(0.15)","scale(1)"]},"delay":0,"duration":600,"easing":"cubic-bezier(0.4, 0.4, 0.0, 1)","fill":"forwards"}]

8. Subset Selection

[{"selector":"#anim-60a0129a-9fd4-4f78-b1f5-55277a70bab0","keyframes":{"transform":["translate3d(106.94444%, 0px, 0)","translate3d(0px, 0px, 0)"]},"delay":0,"duration":1000,"easing":"cubic-bezier(.2, 0, .8, 1)","fill":"both"}] [{"selector":"#anim-f7343d85-7ec2-4e7b-abf8-be549e74e67f","keyframes":{"transform":["rotateZ(180deg)","rotateZ(0deg)"]},"delay":0,"duration":1000,"easing":"cubic-bezier(.2, 0, .5, 1)","fill":"forwards"}]

Basics statistics formulas you need to know

[{"selector":"#anim-2c95e505-f92a-4e32-8705-04dd083302b4","keyframes":[{"transform":"rotate(-540deg) scale(0.1)","opacity":0},{"transform":"none","opacity":1}],"delay":0,"duration":1000,"easing":"cubic-bezier(0.4, 0.4, 0.0, 1)","fill":"both","iterations":1}] Arrow Explore here

Most Important Statistics Techniques

1. Linear Regression

(a) Simple (b) Multiple

2. Classification

(a) Logic regressiom (b) Discriminant Analysis

3. Resampling

(a) Bootstrapping (b) Cross Valodation

4. Shrinkage

(a) Ridge Regression

5. Dimension Reduction

(a) Principal components (b) Regression

(a) Step function (b) Piecewise Function

6. Nonlinear Models

7. Unsupervised Learning

(a) Principal component Analysis (b) K-Means Clustering

8. Subset Selection

(a) Forward (b) Backward

Basics statistics formulas you need to know