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
IT 403 -- Formulas for Final Exam Interquartile Range: IQR = Q3 - Q1 Inner fences for boxplot: Q1 - 1.5 × IQR; Q3 + 1.5 × IQR Outer fences for boxplot: Q1 - 3.0 × IQR; Q3 + 3.0 × IQR z-score for individual observations: z = (x - x) / SD+ Standard error of the average: SEave = SD+ / √n z-score for sample average: z = (x - μ) / SEave Ideal measurement model: xi = μ + ei Linear regression model: yi = axi + b + ei Estimated Linear regression model: yi - y = (r SDy / SDy) (xi - x) Root mean squared error for regression: RMSE = (SD+) √(1 - r2) Addition Rule: if A and B are disjoint events, P(A ∪ B) = P(A) + P(B). Multiplication Rule: if A and B are independent events, P(A ∩ B) = P(A)P(B) Probability of at Least One Success, of Bernoulli trials: 1 - (1 - p)n Expected Value of a random variable: E(x) = x1P(x1) + ... + xmP(xm) Ways to choose k items from n: nCk = n! / k! (n – k)! Binomial Formula: P(k successes out of n) = nCk pk (1 – p)n-k Theoretical Variance of a random variable: Var(x) = (x1 - E(x))2 P(x1) + ... + (xm - E(x))2 P(xm) Theoretical SD of a random variable: σx= sqrt(Var(x)) Expected Value of a Sum: E(S) = nE(x1) Theoretical SD of a sum: σS= sqrt(n) σx Expected Value Bernoulli Random Variable: E(x) = p Theoretical Standard Deviation of Bernoulli Random Variable: σx= sqrt(np(1 – p)) Standard Error of a Sum, where the random variables x1, ... , xn are independent: σS = sqrt(n) σx Test Statistic for a z-test: z = (x - μ) / SEave, SEave = SD+ / sqrt(n) Test Statistic for a t-test: t = (x - μ) / SEave, SEave = SD+ / sqrt(n) Test Statistic for a Chi-squared test: χ2 = (O1 - E1)2 / E1 + ... + (Ok - Ek)2 / Ek