DQE+Potential+Questions+Analysis+-+Classical+Statistical+Inference

DQE Potential Questions Analysis - Classical Statistical Inference (DQE Prep) (GWU EMSE-271)
Index | Topics (Logical Lectures) | Lectures | Problems | Readings | Nomenclature | Concepts

Top Concepts | Fill in the blank calculations | Academic Correctness | Notes | Other Oohs and Aahs | Test Question Bank | Problem-Solving Oriented Checksheets | Q for VD | Definititions (TBD) | Symbols (TBD) | Potential Question Analysis (Mulitvariate Analysis) | Classical Statistical Inference | 2011 Study Plan | Problems Index ]


 * Classical Statistical Inference** (Not as important as [**Multivariate Analysis Methods]**

Upper and lower bounds roll into a confidence interval question. ||
 * Priorities: High, Medium, Low; MH, etc.; E - probably embedded in another question; W - Wild Card; Risk - take a risk and skip**
 * **Priority** || **Source** || **Problem** || **Category** || **Comments** ||
 * X || Session 1 Lecture || Mintab Plots ||  ||   ||
 * WMH ||  || Probability Calculus || calculations || Both VD and TM are fond of probability calcuations of the type on Slide 17. ||
 * WM ||  || Bayes Law || fill in the blank; concepts || Don't expect a Bayes table. Didn't see a Bayes problem on the midterm. Slides 22-26 to calculate. ||
 * W ||  || Batteries - Quality Control ||   ||   ||
 * W, but L - WM || Homework 1 || Quality Control ||  || Like TM's way to solve better. ||
 * WM || MidTerm || - Total Probability ||  ||   ||
 * || Session 2 Lecture || Distribution Theory ||  || Could be a PDF/CDF problem with a discrete distributon. Importance of Distribution Models (as shown on slides 46 and 47) ||
 * R ||  || - Kernals ||   ||   ||
 * MH ||  || Variance and Expected Value ||   || Univariate Point Estimation. Still need the table of common symbols (PAD 202) - TBD
 * WM || Homework 2 || Q!: Flight Overbooking || Calculations || PDF and CDF concepts. ||
 * WMH ||  || Q2: Refrigerator Expected Values || Calculations || Feels a little fill in the blanks to me (pws) ||
 * WMH w Bayes ||  || Q3: K-Out-Of-N || Calculations, concepts || Contains a little probability rule logic ||
 * X ||  || Q4:Steel Shafts || Calculations, concepts || Uses PDF and CDF but requires access to distribution tables. ||
 * WM ||  || Q5: Flexural Strength || Calculations || Simple E[X], etc calculations. (Low if ...) ||
 * L-E || Session 3 Lecture || Confidence Intervals || Calculations || Calcuations if distribution-value is given. Mean Confidence Intervals (usually t-test). Variance Confidence Intervals (Chi-Squared Test). Academic Correctness - TBD Complete - High Priority ||
 * E ||  || Hypothesis Testing ||   || Academic Correctness ||
 * E ||  || Type I and II Errors || concepts, could be calculations || But Type II (Beta) calculations were not trivial (see spreadsheet TBR) ||
 * E ||  || Goodness-of-Fit (Dielectric Breakdown) ||   || Question is how to check for normality - probablility plot. ||
 * Risk ||  || MLE/MOM ||   || Not on Van Dorp's Midterm (Although on Harris's) ||
 * H || Homework 3 || Confidence Intervals || concepts || Possible, more likely embedded; but do need to understand. Academic Correctness - TBD Complete - High Priority ||
 * E ||  || Insulating Paper || calcuate || CI ||
 * E ||  || Lightening Flashes || calculate || CI ||
 * E ||  || Lateral Expansion || calculate || CI (for sigma-square and sigma) ||
 * L-E ||  || Light Bulbs || calcuate || P-Value ||
 * X ||  || Melting Point ||   || need distribution tables to do ||
 * X || Session 4 Lecture || Equal Bin and Equal Width ||  || Chi-Squared Goodness-of-fit; would need distribution values to do ||
 * H ||  || Credibility Intervals ||   || TBD - High Priority. Find Spreadsheet with example, tec. ||
 * WH ||  || Two Sample CI / Hypothesis Testing ||   || Could be asked to compute degrees of freedom. If given X, Y, mu and S could be asked to compute test statistic (?? Priority word page needed) ||
 * E ||  || Lean Angle ||   || 2 Sample Variance Testing (F-test) where single variable uses Chi-squared (Check Priority) ||
 * R? || Homework 4-1 || Q1: MOM/MLE ||  ||   ||
 * R??? ||  || Q2: MOM/MLE using exponential distribution ||   || Also credibility interval, Chi-Squared Goodness-of-fit ||
 * R? || Session 5 Lecture || Vectors and Matrices ||  || Could ask us to show a Transposed Matrix? But why? What else? Compute length of a vector?  ||
 * W ||  || Women's Height/Weight example || Calculation || Height Weight Index? ||
 * E ||  || Singular Value Decomposition ||   ||   ||
 * E-W || Homework 4-2 || Q3: Low-Back Pain || Calculation (Hypothesis Test) || Another confidence interval problem. See Excel Spreadsheet for Solution. ||
 * E- WMH ||  || Q4: Copper Deficiency in Cattle || Calculation (Hypothesis Test) || Equality of Population Variances (multiple hypotheses. See Excel Spreadsheet for Solution. ||
 * || Session 6 Lecture || Joint Normal Distribution ||  ||   ||
 * ||  || Multivariate Point Estimation ||   ||   ||
 * WM ||  || Matrix Determinant || calculation ||   ||
 * WM ||  || Hotelling T-Squared Test and Two Sample Mean Test || calculation || F-Test; Weighted Degrees of Freedom calculation ||
 * ||  || Wisconsin Power || calculation of T-squared || Slide 176, comparison between T-squared (Hotelling) and Chi-Squared test. [Homework has an example of non-academically (complete) conclusion. ||
 * R || Homework 5 || Q1: Persipiration ||  || Matrix calculations; assume too complex. ||
 * X ||  || Q2-4: Gender Reasoning Differences || calcuation, but too distribution look-up intensive? || [Homework 5 Solution, Slide 4) This is an issue of contention in classical statistics. The prevailing view is that when multiple characteristics have been obtained for subject, you test for a difference between subjects using the multivariate test. To test for characteristic differences you use the univariate test. ||


 * Matrix and Vector Operations**
 * Calculate Determinate, 2x2 Inverse Matrix?


 * Sources:**
 * EMSE 271, Fall 2009