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STAT 600  University Of Michigan Study Resources

Stat 600 Midterm Review Questions 2013
School: University Of Michigan
1. A certain medical study utilizes standard hospital patient records at time of admittance, as shown below. Patient ID Blood Type (O, A, B, AB) Rh Factor (+, ) Body Temp (F) Pulse (beats/min) (systolic mm/Hg / diastolic mm/Hg) 00001 00002 00003 00004 000

Stat 600 Final 2012 Review Questions
School: University Of Michigan
1. According to astronomers, many of the stars that are visible with the naked eye are actually binary systems, i.e., two stars that orbit each other around a common center of mass. Generally, the variable X = Luminosity relative to the sun of a single st

Stat 600 Midterm 2 Review Questions 2011
School: University Of Michigan
1. A worker bee inspects a hexagonal honeycomb cell, starting at corner A. When done, she proceeds to an adjacent corner (always facing inward as shown), either by randomly moving along the lefthand edge with probability 0.35, or independently, along the

Stat 600 Law of Total Probability Quiz Solutions
School: University Of Michigan
1. (b) With events A = Al goes and B = Bob goes, we have P ( A B ) = 0.95 , P ( A) = 0.80 , and P ( B ) = 0.75 from the given. Via the addition rule P ( A B ) = P ( A) + P ( B ) P ( A B ) , we obtain 0.95 = 0.80 + 0.75 P ( A B ) , so that P ( A B ) = 0.60

Stat 600 Least Squares Homework Solutions
School: University Of Michigan
Statistics 600 Problem Set 1 Due in lab on Tuesday, September 23rd 1. Suppose that X1 , . . . , Xn are uniformly spaced from 0 to 1, and Yi = Xi2 . We use ordinary least squares to t the model Yi = + Xi . Derive approximate values for and by approximat

Stat 600 Midterm 2013 Solutions
School: University Of Michigan
Statistics 600 Exam 1 October 16, 2013 1. Prove that the horizontal residuals in a simple linear regression sum to zero. The horizontal residuals are the horizontal dierences obtained by following the line segments connecting each data point (Xi , Yi ) to

Stat 600 Independent Correlation Homework Solutions
School: University Of Michigan
Statistics 600 Problem Set 2 Due in lab on Tuesday, October 7th 1. Suppose we plan to collect data on two predictor variables X1 and X2 , and a response variable Y , then t a linear model of the form Y = 0 + 1 X1 + 2 X2 + X1 X2 using OLS. The sample corre

Stat 600 Midterm 2014 Solutions
School: University Of Michigan
Statistics 600 Exam 1 October 22, 2014 1. Suppose we have a 4n 4 design matrix X in which the rst n rows of X are (1, 0, 0, 0), the next n rows of X are (0, 1, 0, 0), the next n rows of X are (0, 0, 1, 0), and the nal n rows of X are (0, 0, 0, 1). We obse

Stat 600 Bonferroni Procedures
School: University Of Michigan
Statistics 600 Problem Set 3 Due in class on Monday, October 27th 1. (a) Suppose we are applying the Bonferroni procedure in a setting where the endpoints of each interval are independent of the endpoints of each other interval. Derive an expression for t

Stat 600 Central Limit Theorem Quiz Solutions
School: University Of Michigan
From the Central Limit Theorem, we know that if X ~ N(, ), then X ~ N , . Therefore, n 1. (b) 9.1 9.0 0.24 X ~ N 9, = 3.09, and , so the X score = 9.1 transforms to a Zscore = 0.24 55 55 likewise, the symmetric X score = 8.9 transforms to a Zsc

Stat 600 Midterm Solutions
School: University Of Michigan
Statistics 600 Midterm Exam October 25, 2011 1. Suppose we plan to t a linear model in which the design matrix satises X X/n = 1 0 0 0 0 0 1 r 0 0 0 r 1 0 0 0 0 0 1 r 0 0 0 r 1 . The usual linear model properties E[Yi Xi ] = Xi and cov(Y X) = 2 I ho

Stat 600 Numerical Solutions Quiz Solutions
School: University Of Michigan
1. (d) While Income ($) itself is a numerical variable, Income Level (for example, 1 = Low, 2 = Middle, 3 = High) is a classification into ordered categories, not measurements. 2. (c) The mode is simply

Stat 600 Expected Variance Quiz Solutions
School: University Of Michigan
1. (b) X = # Days is a discrete random variable; the average is given by the formula = x f ( x) = 2.5 days. (1)(.30) + (2)(.25) + (3)(.20) + (4)(.15) + (5)(.10) = Exercise: What would the variance 2 be? 2. (c) $0.70 4/9 x WIN LOSE f ( x) $0.65 5/9 There