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514 EPI - SPRING 2002- FINAL EXAM Your diskette contains THREE files: adr00_##.txt dth00_## pop00_## raw data file with discharge data from one hospital for one year SAS data set with 2000 death data for one county SAS data set with 2000 population data for one county 1 There are two questions to be answered using data in these files. There should be enough information for you to answer each part of the three questions. Make sure that you look at the descriptions of the data showing what data are INVALID or UNKNOWN. PROBLEMS, COMMENTS, SUGGESTIONS, WHATEVER...: E-MAIL msz03@health.state.ny.us mike.zdeb@verizon.net 473-2855 PHONE DO ALL THIS WORK YOURSELF (UNDER PENALTY OF PERMANENT GUILTY CONSCIENCE). IF YOU HAVE QUESTIONS, ASK ME. #1 DATA ID NUMBER ADMIT DATE DISCHARGE DATE AGE GENDER RACE ETHNICITY ADMIT SOURCE ADMIT TYPE DRG DISPOSITION LENGTH OF STAY PRINCIPAL DIAG OTHER DIAG 1-14 PRINCIPAL PROC OTHER PROC 1-14 PAYOR COST HOSPITAL NUMBER The HOSPITAL DISCHARGE RAW DATA FILE contains the following data.... LOCATION (COLUMNS) 1-4 5-12 13-20 21-23 24 25 26 27 28 29-31 32-33 34-37 38-40 41-82 83-84 85-112 113-114 115-124 125-128 MMDDYYYY MMDDYYYY M-MALE 1-WHITE 3,4,8-OTHER 1-HISPANIC (SEE BELOW) 1-EMERGENCY 4-NEWBORN (SEE BELOW) DAYS (EACH OTHER DIAGNOSIS IS 3-CHARACTERS) (EACH OTHER PROCEDURE IS 2-CHARACTERS) (SEE BELOW) DOLLARS F-FEMALE 2-BLACK 9-UNKNOWN 2-NOT HISPANIC 2-URGENT 9-NOT AVAILABLE U-UNKNOWN 3-UNKNOWN 3-ELECTIVE ADMIT SOURCE 1-MD REFERRAL 3-HMO REFERRAL 5-TRANSFER (SKILLED NURSING FACILITY) 7-EMERGENCY ROOM 9-NOT AVAILABLE 2-CLINICAL REFERRAL 4-TRANSFER (OTHER HOSPITAL) 6-TRANSFER (OTHER HEALTH FACILITY) 8-COURT/LAW ENFORCEMENT A-TRANSFER (RURAL PRIMARY CARE HOSPITAL EPI 514 - SPRING 2002- FINAL EXAM DISPOSITION 01-HOME 03-SKILLED NURSING FACILITY 05-OTHER INSTITUTION FOR INPATIENT CARE 07-LEFT AGAINST MEDICAL ADVICE 10-NEWBORN TRANSFERRED TO OTHER HOSPITAL 12-FACILITY FOR MENTALLY RETARDED 14-DOMICILIARY CARE FACILITY 50-HOSPICE (HOME) PAYOR 01-SELF PAY 03-MEDICARE 06-BLUE CROSS 08-COMMERCIAL INSURANCE 10-OTHER 12-CHAMPUS/VA 15-SELF INSURED 17-MEDICAID HMO 2 02-OTHER HOSPITAL 04-INTERMEDIATE CARE FACILITY 06-HOME HEALTH CARE 08-HOME UNDER CARE OF SPECIAL PROVIDER 11-SHORT-TERM PSYCHIATRIC HOSPITAL 13-OTHER HOSPITAL FOR TRAUMA CARE 20-DIED 51-HOSPICE (MEDICAL FACILITY) 02-WORKER'S COMPENSATIION 04-MEDICAID 07-OTHER GOVERNMENT 09-NO CHARGE 11-HMO 13-NO FAULT 16-MEDICARE HMO 18, 19, 20-CORRECTIONS #2 PROC CONTENTS run using the DEATH and POPULATION data sets shows the following... DTH00_## # Variable Type Len Label ------------------------------------------------------------------------------------3 age Num 8 AGE (0=<1, 1-99, 100=100+) 2 cause Char 1 CAUSE (A=ACCIDENT, C=CANCER, D=DIABETES, H=HEART ATTACK) 4 dth Num 8 2000 DEATHS 1 gender Char 1 GENDER (1=MALE, 2=FEMALE) POP00_## # Variable Len Type Label ---------------------------------------------------------2 age Num 8 AGE (0=<1, 1-99, 100=100+) 1 gender Char 1 GENDER (1=MALE, 2=FEMALE) 3 pop Num 8 2000 CENSUS POPULATION EPI 514 - SPRING 2002- FINAL EXAM NAME (DISK #) ___________________________________ #1 HOSPITAL DISCHARGES (RAW DATA) 3 ID (LAST 4-DIGITS)____________ HINT: ANSWERS REQUIRE CONVERTING RAW DATA TO A SAS DATA SET, PROCEDURES, WHERE STATEMENT(S), FORMAT(S), REARRANGING DATA, PLUS WHATEVER ELSE YOU MIGHT WANT TO TRY A/ How many discharges were there from your hospital... ____________ B/ Excluding newborns (any record with a principal diagnosis that starts with V3)... How many discharges were there in the following age groups: 0-4 5-14 15-24 25-64 65+ (1)____________ (2)____________ (3)____________ (4)____________ (5)____________ C/ Excluding newborns (any record with a principal diagnosis that starts with V3)... What is the most common principal diagnosis among males... What is the most common principal diagnosis among females... (1)____________ (2)____________ D/ What is the most common OTHER diagnosis... Excluding any non-invasive procedure (any procedure code greater than 86) What is the most common OTHER procedure... Excluding any non-invasive procedure (any procedure code greater than 86) How many patients (could be zero) had 5 or more other procedures (1)____________ (2)____________ (3)____________ E/ What is the mean length of stay for MEDICAID patients (includes Medicaid + Medicaid HMO)... ____________ F/ What payor (having at least 50 discharges) has the highest median cost... What is that cost... (1)____________ (2)____________ G/ Of those patients admitted from the emergency room.... How many patients were discharged to home (code 01)... How many patients were discharged dead... (1)____________ (2)____________ H/ What day of the week was the most frequent day of admission... ____________ EPI 514 - SPRING 2002- FINAL EXAM NAME (DISK #) ___________________________________ #2 DEATH AND POPULATION DATA (SAS DATA SETS) 4 ID (LAST 4-DIGITS)____________ HINT: ANSWER MAY REQUIRE REARRANGING DATA, A FUNCTION, COMBINING DATA SETS Round rates to one decimal place. What is the number (#) of deaths and CRUDE DEATH RATE (per 100,000 population) for the following.... A/ FOR ALL DEATHS (AND POPULATION)... ACCIDENTS MALES (1)#____________ RATE____________ FEMALES (2)#____________ RATE____________ DIABETES MALES (3)#____________ RATE____________ FEMALES (4)#____________ RATE____________ B/ FOR ONLY THOSE DEATHS (AND POPULATION) AGE 65+... CANCER MALES (5)#____________ RATE____________ FEMALES (6)#____________ RATE____________ C/ FOR ONLY THOSE DEATHS (AND POPULATION) AGE < 65... HEART ATTACK MALES (7)#____________ RATE____________ FEMALES (8)#____________ RATE____________
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ms2002.pdf
Path: SUNY Albany >> EPI >> 514 Fall, 2009
Description: MIDTERM EXAM - SPRING 2002 Last Name: ID #: 1 #1 After each data step, fill in the table with the variable names, types, and lengths. * list input; data test; input l_name $ f_name $ age ssn $ salary; datalines; GULIANI RUDOLPH 60 010360222 250000....
probability_3.pdf
Path: SUNY Albany >> STA >> 552 Fall, 2009
Description: PROBABILITY - CHAPTER 3 1 TERMINOLOGY SAMPLE SPACE: SET OF ALL POSSIBLE OUTCOMES EVENT: ANY SET OF OUTCOMES SIMPLE EVENT: (TRIOLA HANDOUT) AN OUTCOME THAT CANNOT BE FURTHER BROKEN DOWN INTO SIMPLER COMPONENTS PROBABILITY - CHAPTER 3 2 EXAMPL...
c2_descriptive_statistics.pdf
Path: SUNY Albany >> STA >> 552 Fall, 2009
Description: DESCRIPTIVE STATISTICS - CHAPTERS 1 & 2 1 OVERVIEW STATISTICS PANIK .THE THEORY AND METHODS OF COLLECTING, ORGANIZING, PRESENTING, ANALYZING, AND INTERPRETING DATA SETS SO AS TO DETERMINE THEIR ESSENTIAL CHARACTERISTICS. HYPERSTAT .IN THE BROADEST...
c5_probability.pdf
Path: SUNY Albany >> STA >> 552 Fall, 2009
Description: PROBABILITY - CHAPTER 5 1 UP TO NOW. Chapter 3: Probability (Classical, Relative Frequency, Subjective), Type of Events (Mutually Exclusive, Independent), Laws (Addition, Multiplication), Conditional Probability, Medical Tests (Sensitivity, Specif...
estimation_6.pdf
Path: SUNY Albany >> STA >> 552 Fall, 2009
Description: Estimation Overview Up until now, we have been dealing with describing data (Chapter 2), assuming that we already know how data are distributed and that we sometimes know population parameters such as the mean and variance (Chapter 3 through 5). Exam...
quiz04_f2008a.pdf
Path: SUNY Albany >> EPI >> 514 Fall, 2009
Description: QUIZ4 FALL 2008 * ANSWERS * ifyouwritedownthevaluesofFIRST.SSNand LAST.SSNforeachobservationyoushouldsee thevaluesshownbelow datanew; setstudy; byssn; iffirst.ssnorlast.ssn; run; datanew; setstudy; byssn; ifnotfirst.ssnandnotlast.ssn; run; datanew;...
assg_05.pdf
Path: SUNY Albany >> EPI >> 514 Fall, 2009
Description: ASSIGNMENT #5 (same data as used in ASSIGNMENT #3) #1 FORMATS - You are given a SAS data set named DEATH99 It contains observations for deaths that occurred in 1999 to residents of Albany, Schenectady, Rensselaer, and Saratoga counties. PROC CONTENTS...
hypothesis.pdf
Path: SUNY Albany >> STA >> 552 Fall, 2009
Description: Hypothesis Testing Overview While the previous chapter dealt with estimating the values for parameters of various distributions (point estimates and interval estimates), a more common situation is testing whether or not the value of a parameter is eq...
adjust_sas_code.pdf
Path: SUNY Albany >> EPI >> 697 Fall, 2009
Description: AGE ADJUSTING procformat; valueage 0=\'1\' 14=\'2\' 514=\'3\' 1524=\'4\' 2534=\'5\' 3544=\'6\' 4554=\'7\' 5564=\'8\' 6574=\'9\' 7584=\'10\' 85high=\'11\' ; run; *filenamevsdftp \'c:\\vs\\deaths\\data\\dthsta00.txt\' host=\'169.226.136.233\' prompt debug user=\'armando\' pass=\'sph12...
probability_f2007.pdf
Path: SUNY Albany >> STA >> 552 Fall, 2009
Description: Probability and Probability Distributions Classes 4 -10 (9/6 - 10/4) Overview The Descriptive Statistics module showed how to describe data by computing certain measures of location and certain measures of variation. You also learned how to construct...
fp019_025.pdf
Path: SUNY Albany >> EPI >> 514 Fall, 2009
Description: Introduction to SAS (a work in progress as of Spring, 2009) Mike Zdeb (send comments, corrections to: msz03@albany.edu) #19 (2) PROGRAMS, DATA SETS, RULES .SAS PROGRAMS For many of you, the only experience you have with working with data involves u...
assg_04a.pdf
Path: SUNY Albany >> EPI >> 514 Fall, 2009
Description: ASSIGNMENT #4 ( * ANSWERS *) * PROBLEM #1 (DATA STEP FROM ASSIGNMENT #2); libname x \'k:\\\'; data x.clinical; infile \'k:\\sasclass\\data\\clinical.dat\'; input id $ 1-2 visit mmddyy8. group $ 11 chol 12-14 sbp 15-17 dbp 18-20 hr 21-22 typevis $ 23 ; format...
p041_060.pdf
Path: SUNY Albany >> EPI >> 514 Fall, 2009
Description: Introduction to SAS Mike Zdeb (402-6479, msz03@albany.edu) #41 (6) SAS PROCEDURES Up to now, only three SAS procedures (PROC CONTENTS, PROC PRINT, PROC MEANS) have been used without much discussion as to how they work, options available, or why you...
chapter5_answers.pdf
Path: SUNY Albany >> STA >> 552 Fall, 2009
Description: Probability - Chapter 5 given that among 12-14 year old boys, carbohydrate intake is normally distributed, with a mean of 124 and a standard deviation of 20 . 5.6 What percentage of boys in this age range have carbohydrate intake above 140 g / 1000...
p083_120.pdf
Path: SUNY Albany >> EPI >> 514 Fall, 2009
Description: Introduction to SAS Mike Zdeb (402-6479, msz03@albany.edu) #83 (8) DATES SAS has numerous informats for reading dates and formats for displaying dates. Dates can be read with either numeric, character, or date informats. If you read a date as a cha...
nonparm_12.pdf
Path: SUNY Albany >> STA >> 552 Fall, 2009
Description: NONPARAMETRIC STATISTICS 1 PREVIOUSLY parametric statistics in estimation and hypothesis testing. construction of confidence intervals computing of p-values classical significance testing depend on assumptions about the underlying distribution of ...
appendix_B.pdf
Path: SUNY Albany >> EPI >> 514 Fall, 2009
Description: Introduction to SAS (a work in progress as of Spring, 2009) Mike Zdeb (send comments, corrections to: msz03@albany.edu) APPENDIX B - DEFAULT SORTING ORDER OF CHARACTERS There is a default sorting order for characters within SAS. It is know as ASCII (...
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Path: SUNY Albany >> PAD >> 705 Fall, 2008
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InstrumentalVariables.pdf
Path: SUNY Albany >> PAD >> 705 Fall, 2008
Description: Rockefeller College University at Albany PAD 705 Handout: Instrumental Variables In earlier handouts, we saw that when the independent variables are stochastic (i.e., measured as part of a sample rather than set by the researcher) we must show that ...
FactorAnalysisTheory.pdf
Path: SUNY Albany >> PAD >> 705 Fall, 2008
Description: Rockefeller College University at Albany PAD 705 Handout: Factor Analysis Throughout this course, I have emphasized that statistical analysis is part science, part art. Our final topic, factor analysis, strays the farthest into art of all the techni...
Lecture03.pdf
Path: SUNY Albany >> AJ >> 4575 Fall, 2009
Description: Class Notes August 29,2008 Mathematical methods: Graphing, nding slope of a line, and calculating area under a line. A graph matches amounts of two variables. It is drawn on axes - an x-axis (horizontal) and a y-axis (vertical) - that are perpendicul...
Lecture15.pdf
Path: SUNY Albany >> AJ >> 4575 Fall, 2009
Description: Welfare economics: Study of how allocation of resources aects well-being of buyers, sellers. First look at what benet to buyers and sellers of participating in a market is. Then see how these benets can be made as large as possible. A conclusion of w...
PROPHEWP11_Levy.pdf
Path: SUNY Albany >> PROPHEWP >> 11 Fall, 2009
Description: Access through Private Higher Education: Global Patterns and Indian Illustrations By Daniel C. Levy WP No. 11 April 2008 PROPHE Working Paper Series http:/www.albany.edu/dept/eaps/prophe PRIVATE HIGHER EDUCATION PROGRAM FOR RESEARCH ON Access t...
PROPHEWP12_PP.pdf
Path: SUNY Albany >> PROPHEWP >> 12 Fall, 2009
Description: Inside Thai Private Higher Education: Exploring Private Growth in International Context By Prachayani Praphamontripong PROPHE Doctoral Research Associate, University at Albany, SUNY WP No. 12 September 2008 PROPHE Working Paper Series http:/www.al...
WP9_Levy&Otieno_FINAL_.pdf
Path: SUNY Albany >> PROPHEWP >> 09 Fall, 2009
Description: Public Disorder, Private Boons? Inter-sectoral Dynamics Illustrated by the Kenyan Case By Wycliffe Otieno* and Daniel Levy* * Lecturer in Educational Planning and Economics of Education Kenyatta University * Distinguished Professor, University at A...
PROPHEWP03.pdf
Path: SUNY Albany >> PROPHEWP >> 03 Fall, 2009
Description: The New Institutionalism: Mismatches with Private Higher Educations Global Growth By Daniel C. Levy Distinguished Professor, State University of New York (SUNY) Department of Educational Administration & Policy Studies, University at Albany-SUNY WP...
PROPHEWP04.pdf
Path: SUNY Albany >> PROPHEWP >> 04 Fall, 2009
Description: EXTERNAL AFFILIATIONS AND DIVERSITY: Chiles Private Universities in International Perspective By Andrs Bernasconi Dean of the Law School, Universidad de Talca, Chile, and PROPHE Collaborating Scholar WP No. 4 November 2004 PROPHE Working Paper Serie...
PROPHEWP13_Levy.pdf
Path: SUNY Albany >> PROPHEWP >> 13 Fall, 2009
Description: Indian Private Higher Education in Comparative Perspective By Daniel C. Levy Distinguished Professor, University at Albany (SUNY) and PROPHE Director WP No. 13 October 2008 PROPHE Working Paper Series http:/www.albany.edu/~prophe PROGRAM FOR RESE...
PROPHEWP05.pdf
Path: SUNY Albany >> PROPHEWP >> 05 Fall, 2009
Description: THE FOR-PROFIT SECTOR: U.S. Patterns and International Echoes in Higher Education By Kevin Kinser and Daniel C. Levy WP No. 5 February 2005 PROPHE Working Paper Series http:/www.albany.edu/dept/eaps/prophe PROGRAM FOR RESEARCH ON PRIVATE HIGHER ...
PROPHEWP02.pdf
Path: SUNY Albany >> PROPHEWP >> 02 Fall, 2009
Description: PROFITS AND PRACTICALITY: How South Africa Epitomizes the Global Surge in Commercial Private Higher Education By Daniel C. Levy Distinguished Professor, State University of New York (SUNY) Department of Educational Administration & Policy Studies, U...
PROPHEWP06.pdf
Path: SUNY Albany >> PROPHEWP >> 06 Fall, 2009
Description: PRIVATE HIGHER EDUCATION PENETRATION INTO A MATURE EDUCATION MARKET: The New Zealand Experience By Malcolm Abbott School of International Studies AIS St Helens, New Zealand and PROPHE Associate Colleague WP No. 6 July 2005 PROPHE Working Paper Seri...
WP8_Scheker_DominicanRepublic_Final_10Jul07.pdf
Path: SUNY Albany >> PROPHEWP >> 08 Fall, 2009
Description: COMPARING SCHOOL-LEVEL TO PRIVATE HIGHER EDUCATION: Using the Dominican Republic as a Pioneer Study By Ancell Scheker Mendoza Doctoral Student, University at Albany-SUNY WP No. 8 July 2007 PROPHE Working Paper Series http:/www.albany.edu/dept/eap...
PROPHEWP07.pdf
Path: SUNY Albany >> PROPHEWP >> 07 Fall, 2009
Description: AN INTRODUCTORY GLOBAL OVERVIEW The Private Fit to Salient Higher Education Tendencies By Daniel C. Levy WP No. 7 September 2006 PROPHE Working Paper Series http:/www.albany.edu/dept/eaps/prophe PROGRAM FOR RESEARCH ON PRIVATE HIGHER EDUCATION ...
PROPHEWP01.pdf
Path: SUNY Albany >> PROPHEWP >> 01 Fall, 2009
Description: Unanticipated Development: Perspectives on Private Higher Educations Emerging Roles By Daniel C. Levy Distinguished Professor, State University of New York (SUNY) Department of Educational Administration & Policy Studies, University at Albany-SUNY ...
WP10_Georgia_24Sept07.pdf
Path: SUNY Albany >> PROPHEWP >> 10 Fall, 2009
Description: Changing Patterns of Private-Public Growth and Decline: The Case of Georgian Higher Education By Marie Pachuashvili Doctoral Student, Central European University WP No. 10 September 2007 PROPHE Working Paper Series http:/www.albany.edu/dept/eaps/...
regression_mean.pdf
Path: SUNY Albany >> PO >> 467 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Inference for the regression mean October 11, 2006 Least-Squares Estimator According to the regression model, the mean of variable y for a given value for x, say x = x* , is E( y | x =...
regression_mean.pdf
Path: SUNY Albany >> PO >> 553 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Inference for the regression mean October 11, 2006 Least-Squares Estimator According to the regression model, the mean of variable y for a given value for x, say x = x* , is E( y | x =...
correlation.pdf
Path: SUNY Albany >> PO >> 467 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Correlation October 26, 2006 Definition of covariance For a pair of random variables x and y, one can define the covariance of the variables as the average (expected value) product of dev...
correlation.pdf
Path: SUNY Albany >> PO >> 553 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Correlation October 26, 2006 Definition of covariance For a pair of random variables x and y, one can define the covariance of the variables as the average (expected value) product of dev...
assignment2.pdf
Path: SUNY Albany >> PO >> 467 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Computer Assignment 2 October 29, 2006 Problem 1 Consider the following dataset: obs 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 y 16.58 20.36 11.32 1...
assignment2.pdf
Path: SUNY Albany >> PO >> 553 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Computer Assignment 2 October 29, 2006 Problem 1 Consider the following dataset: obs 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 y 16.58 20.36 11.32 1...
dummy_variables.pdf
Path: SUNY Albany >> PO >> 467 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Regression Dummy variables October 26, 2006 Model 1: shift Consider the regression model yi = o + 1 xi + 0 Di + i where Di has the value 1 when the ith observation has a given attribut...
dummy_variables.pdf
Path: SUNY Albany >> PO >> 553 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Regression Dummy variables October 26, 2006 Model 1: shift Consider the regression model yi = o + 1 xi + 0 Di + i where Di has the value 1 when the ith observation has a given attribut...
regression_assumptions.pdf
Path: SUNY Albany >> PO >> 467 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Regression: Testing Assumptions December 4, 2006 Linearity The linearity of the regression mean can be examined visually by plots of the residuals against any of the independent variables,...
regression_assumptions.pdf
Path: SUNY Albany >> PO >> 553 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Regression: Testing Assumptions December 4, 2006 Linearity The linearity of the regression mean can be examined visually by plots of the residuals against any of the independent variables,...
twoway_anova.pdf
Path: SUNY Albany >> PO >> 467 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Two-way ANOVA November 11, 2006 Randomized complete replicate block design The population is blocked to reduce heterogeneous outcomes on a measure of choice, randomly sampled within blocks...
twoway_anova.pdf
Path: SUNY Albany >> PO >> 553 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Two-way ANOVA November 11, 2006 Randomized complete replicate block design The population is blocked to reduce heterogeneous outcomes on a measure of choice, randomly sampled within blocks...
logarithm.pdf
Path: SUNY Albany >> PO >> 467 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Logarithms October 26, 2006 Definition The logarithm of a number to a given, positive base is simply the exponent of the number written as a power of the base. For example, with a base of ...
logarithm.pdf
Path: SUNY Albany >> PO >> 553 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Logarithms October 26, 2006 Definition The logarithm of a number to a given, positive base is simply the exponent of the number written as a power of the base. For example, with a base of ...
regression_slope.pdf
Path: SUNY Albany >> PO >> 467 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Inference for the regression slope October 11, 2006 Hypotheses H 0 : 1 = 0 H A : (i ) 1 0 (ii) 1 > 0 (iii) 1 < 0 Least-Squares Estimators 1 = (xi x )( yi y ) , (xi x )2 2 = s2 ...
regression_slope.pdf
Path: SUNY Albany >> PO >> 553 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Inference for the regression slope October 11, 2006 Hypotheses H 0 : 1 = 0 H A : (i ) 1 0 (ii) 1 > 0 (iii) 1 < 0 Least-Squares Estimators 1 = (xi x )( yi y ) , (xi x )2 2 = s2 ...
SASguide.pdf
Path: SUNY Albany >> PO >> 467 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 SAS Analyst: menu-based data analysis November 28, 2006 1. Run Analyst: Menu: Solutions > Analysis > Analyst 2. Open a tab-delimited data file Menu: File > Open: Delimited file > Delimit...
SASguide.pdf
Path: SUNY Albany >> PO >> 553 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 SAS Analyst: menu-based data analysis November 28, 2006 1. Run Analyst: Menu: Solutions > Analysis > Analyst 2. Open a tab-delimited data file Menu: File > Open: Delimited file > Delimit...
syllabus.pdf
Path: SUNY Albany >> PO >> 467 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Syllabus September 8, 2006 Instructor: Email: Web: Assistant: Email: Hours: Textbook: Dr. P. Ochshorn p.ochshorn@albany.edu http:/www.albany.edu/~po467/ Diana Nadler mercedes_131@hotmail.c...
syllabus.pdf
Path: SUNY Albany >> PO >> 553 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Syllabus September 8, 2006 Instructor: Email: Web: Assistant: Email: Hours: Textbook: Dr. P. Ochshorn p.ochshorn@albany.edu http:/www.albany.edu/~po467/ Diana Nadler mercedes_131@hotmail.c...
Problems-chi-square.pdf
Path: SUNY Albany >> PO >> 467 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Chi-square Problems September 28, 2006 1. Goodness-of-fit test: US 61.9 Canada 8.8 Birth Place (1880 Census for Detroit) England Ireland Germany 4.8 6.3 13.6 Other 4.6 Population % An hi...
Problems-chi-square.pdf
Path: SUNY Albany >> PO >> 553 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Chi-square Problems September 28, 2006 1. Goodness-of-fit test: US 61.9 Canada 8.8 Birth Place (1880 Census for Detroit) England Ireland Germany 4.8 6.3 13.6 Other 4.6 Population % An hi...
assignment1.pdf
Path: SUNY Albany >> PO >> 467 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Computer Assignment 1 October 11, 2006 Problem Consider the following dataset: x 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 3.2 3.4 3.6 3.8 4.0 4.2 4.4 4.6 4.8 5.0 5.2 5....
assignment1.pdf
Path: SUNY Albany >> PO >> 553 Fall, 2009
Description: EPI/STA 553 Principles of Statistical Inference II Fall 2006 Computer Assignment 1 October 11, 2006 Problem Consider the following dataset: x 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 3.2 3.4 3.6 3.8 4.0 4.2 4.4 4.6 4.8 5.0 5.2 5....
quarter3.pdf
Path: SUNY Albany >> JUN >> 02 Fall, 2009
Description: New York Concensus Economic Forecast (NYCEF) Survey Date: July, 2002 CPIU-ALL for Urban CPIU-ALL for NY-NJCT-PA US Wages & Salaries Name of Respondent 2002 1 2 3 4 5 9 11 12 13 15 16 17 18 21 25 26 27 28 22 Mean Standard Deviation Middle 50% Lowest H...
epi.pdf
Path: SUNY Albany >> POSTER >> 2003 Fall, 2009
Description: # 43 EPI Steven Carlson Student Judging Dept. M.P.H./Dr.P.H >6 Ying Wang Mentor Dept or Program Years in program Residential Radon Exposure and Lung Cancer Incidence: A study of the NYS DOH Radon Registry Author (s) Steven Carlson Residential...
bs.pdf
Path: SUNY Albany >> POSTER >> 2003 Fall, 2009
Description: # 1 BS 2 Robert Pruzek Mentor Dept or Program Years in program A Propensity Score Analysis to Compare Two Kinds of Gallbladder Surgeries Author (s) Liyi Cen The objective of this study is to compare hospit...
feb_08_flyer_gp.pdf
Path: SUNY Albany >> T >> 2 Fall, 2008
Description: SCHOOL OF PUBLIC H EALTH UNIVERSITY AT ALBANY State University of New York Thursday - February 21, 2008, 9:00 - 10:00 am ET Diabetes: Whats depression got to do with it? Michelle Owens, PhD Behavioral Scientist Centers for Disease Control & Prevent...
Pagano.pdf
Path: SUNY Albany >> V >> 177 Fall, 2009
Description: pacific journal of mathematics Vol. 177, No. 1, 1997 BERGMAN ISOMETRIES BETWEEN CONVEX DOMAINS IN C2 WHICH ARE POLYHEDRAL Andrea Pagano This article deals with the problem of analyticity of Bergman isometries. One of the most important properties of...
Shlyakhtenko.pdf
Path: SUNY Albany >> V >> 177 Fall, 2009
Description: pacific journal of mathematics Vol. 177, No. 2, 1997 FREE QUASI-FREE STATES Dimitri Shlyakhtenko To a real Hilbert space and a one-parameter group of orthogonal transformations we associate a C -algebra which admits a free quasi-free state. This co...
vi-tutor.pdf
Path: SUNY Albany >> CSI >> 201 Fall, 2009
Description: The vi Editor A Brief Summary of Basic Commands A programmer spends a lot of time writing code. The essential tool for writing source code is a text editor, which means that an editor is one of the most important tools that a programmer uses. It is ...
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Path: SUNY Albany >> CSI >> 110 Fall, 2009
Description: 1. What is the URL (i.e, web address) for this course\'s web site? 2. How do you receive the messages from the course listserv? How do you send a message to the course listserv? Who gets the messages you send to the course listserv? 3. When a computer...
pr6spr07.pdf
Path: SUNY Albany >> CSI >> 310 Fall, 2009
Description: CSI 310 Data Structures Spring 2006 Project 6 Expressions and Trees Professor Chaiken Due: April 24-26(see project policy!) The major part of this project is to implement a program like that for Carranos postx calculator, but with more. Your progra...
pr6spr07.pdf
Path: SUNY Albany >> CSI >> 6 Fall, 2009
Description: CSI 310 Data Structures Spring 2006 Project 6 Expressions and Trees Professor Chaiken Due: April 24-26(see project policy!) The major part of this project is to implement a program like that for Carranos postx calculator, but with more. Your progra...
pr6spr07.pdf
Path: SUNY Albany >> PR >> 310 Fall, 2009
Description: CSI 310 Data Structures Spring 2006 Project 6 Expressions and Trees Professor Chaiken Due: April 24-26(see project policy!) The major part of this project is to implement a program like that for Carranos postx calculator, but with more. Your progra...
