Quantitative Methods 1) Know how to calculate the different measures of central tendency (arithmetic mean, geometric mean, median, mode) – be on guard for a harmonic mean question, possibly –not often asked but maybe this’ll be the year. 2) Know the different measures of dispersion and how to calculate them- Variance, standard deviation, mean absolute deviation, range etc. 3) Know the difference for variance and std. deviation calculation for a population vs sample. 4) Make sure you know the coefficient of variation and Sharpe ratio from a qualitative and quantitative standpoint. 5) Know how to calculate expected return for a set of data and weights and know how to calculate HPR. 6) Know how to calculate correlation coefficient and covariance by the formula r = Covx,y / (std dev x) (std dev y) and make sure you understand both concepts from a qualitative standpoint too. 7) Know how to calculate a computed t and z value. That is: (sample mean – pop mean) / std dev. Know what a z-score or t-score means. 8) Know the rule of thumb (1 std dev = 68%, 2 std dev = 95%…) 9) Know the characteristics of a normal distribution. 10) Know how to calculate the standard error of a population or sample. 11) Know how to calculate a confidence interval : x +/- ts 12) Know the difference between null and alternate hypotheses. 13) Know how to do a one-tailed and two-tailed tests (but focus on two tailed tests) 14) Know Type I and Type II errors 15) Know the different variables of a simple regression equation, b0, b1, X1, Y and what they represent. 16) Focus on simple linear regression – know SST=SSR+SSE, also know SEE = square root of SSE / n-k-1 and of course that R squared = SSR/SST or 1 - SSE/SST. Don’t forget: relationship between R squared and correlation coefficient. 17) Know how to calculate the t-score (t calc = point estimate - hypoth value / standard error and how to calculate the standard error given the t calc, hypoth value and point estimate 18) Know how to calculate y, given x’s in a regression equation 19) Know the difference between F and t-tests, when to use each 20) Know how to compare t calc and t critical and whether to accept or reject H0. 21) Know Roy’s Safety First Criterion from a qualitative and quantitative standpoint.
- Know Type I and Type II errors Type I - the error of rejecting a true null hypothesis A court finding a person guilty of a crime that they did not actually commit. Type II - the error of failing to reject a false null hypothesis A court finding a person not guilty of a crime that they did actually commit