Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Checklist Intro of Data Measures of Location Measures of Dispersion Module : Statistics 1 Topic Representation & Summary of Data Data = Observation = Variable Discrete & Continuous Data Quantitative & Qualitative Data Mean, Median, Mode (Quartiles) Including discrete, continuous, grouped and ungrouped data x x n Correlation Scatter Diagrams Linear Regression 769845008 The least square regression line: y = a + bx , where S xy b ,a y b x S xx Applications & Interpretations: or Outliers Histograms Stem & Leaf Box Plots Confidence with this topic fx f Understanding and use of coding Range & Percentile ranges Cumulative Frequency Polygons Variance & Standard Deviation σ2 Skewness or Board : Edexcel x 2 n fx 2 f x2 x2 Simple Interpolation Concept & Definition of Skewness Symetrical, Positive, Negative Distributions Concept of outliers Frequency = Area Frequency density = Frequency/Class Width Correlation & Regression Product-moment correlation coefficient: Its use, interpretation and limitations Variables: Explanatory (independent) variables and Response (dependent) variables Straight-line law: y = bx + a Linear regression model : yi α βx i εi Page 1 5/6/2017 Checklist Set Notations Probability Introduction Module : Statistics 1 Interpolation and extrapolation Probabilty Use of standard formulae Exclusive events Complementary events Board : Edexcel P(A' ) 1 P(A) P(A B) P(A) P(B) P(A B) Independent events P(A B) P(A) P(B) Probability Probability Discrete Random Variables Tree diagrams Conditional probability Solving Probability problems Discrete Random Variables Concept of random variables The probability function: Use of p(x) where p(x) = P(X = x) The cumulative distribution function: F ( x0 ) P( X x0 ) p ( x) x x0 Mean & Variance Calculating the mean – E(X) The use of E(X) and E(X2) to calculate the variance – Var(X) (Expectation Algebra) Knowledge and use of E(aX + b) = aE(X) + b Var(aX +b) = a2 Var(x) Each event is equally likely to occur. The mean and the variance of this distribution The Normal Distribution Properties of Normal Distribution: Shape of a Normal Distribution curve Symmetrical about mu Mode = Mean = Median Total area under the curve = 1 The Standard Normal Distribution The use of its table Discrete Uniform Distribution Normal Distribution 769845008 Page 2 5/6/2017