math215 Lecture Notes - Lecture 5: Prediction Interval, Simple Linear Regression, Bias Of An Estimator
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These are followed by statistics questions 4, 5 and 6. / n n(0, 1) (either approximately or exactly): let x and s be the sample average and standard deviation obtained from a random sample of size n from a population with mean . Under appropriate conditions sample standard deviation, sp =q (n1 1)s 2. Spq 1 n1: let p be the sample proportion of successes" where the number of trials is n and the true probability of a success is . Under appropriate conditions p p (1 )/n n(0, 1) (approximately). 2: some formulae for simple linear regression: Consider the simple linear regression model: for i = 1, 2, . , n, yi = 0 + 1xi + i where the i are normally distributed n(0, 2) for constant . The least squares estimators b0 and b1 of 0 and 1 are b1 = Sxx b0 = y b1 x where.
