Making Sense/ Making Numbers/ Making Significance

Making Sense Making Numbers Making Significance-ppt Download

  • Date:01 Aug 2020
  • Views:46
  • Downloads:0
  • Size:1.15 MB

Share Presentation : Making Sense Making Numbers Making Significance

Download and Preview : Making Sense Making Numbers Making Significance

Report CopyRight/DMCA Form For : Making Sense Making Numbers Making Significance


Transcription:

Gra6036 Multivartate Statistics withEconometrics Psychometrics DistributionsEstimatorsUlf H Olsson.
Professor of Statistics Two Courses in Multivariate Statistics Gra 6020 Multivariate Statistics Applied with focus on data analysis Non technical.
Gra 6036 Multivariate Statistics with Econometrics Technical focus on both application and understanding basics Mathematical notation and Matrix AlgebraUlf H Olsson Course outline Gra 6036.
Basic Theoretical Multivariate Statistics mixed with econometric psychometric theory Matrix Algebra Distribution theory Asymptotical Application with focus on regression type models.
Logit Regression Analyzing panel data Factor Models Simultaneous Equation Systems and SEM Using statistics as a good researcher should.
Research orientedUlf H Olsson Evaluation Term paper up to three students 75 1 2 weeks.
Multipple choice exam individual 25 2 3 hoursUlf H Olsson Teaching and communication Lecturer 2 3 weeks 3 hours per week UHO .
Theory and demonstrations Exercises 1 week 2 hours DK Assignments and Software applications SPSS EVIEWS LISREL Blackboard and Homepage Assistance David Kreiberg Dep of economics .
Ulf H Olsson Week hours Read2 Basic Multivariate Statistical 3 Lecture notesAnalysis Asymptotic Theory3 Logit and Probit Regression 3 Compendium Logistic.
Regression4 Logit and Probit Regression 3 Compendium LogisticRegression5 Exercises 26 Panel Models 3 Book chapter 14 Analyzing.
Panel Data Fixed andRandom Effects Models7 Panel Models 3 Book chapter 14 AnalyzingPanel Data Fixed andRandom Effects Models.
8 Exercises 2Ulf H Olsson 9 Factor Analysis Exploratory 3 Structural Equation Modeling Factor Analysis David Kaplan 200010 Confirmatory Factor Analysis 3 Structural Equation Modeling .
David Kaplan 200011 Confirmatory Factor Analysis 3 Structural Equation Modeling David Kaplan 200012 Exercises 213 Simultaneous Equations 3 Structural Equation Modeling .
David Kaplan 200015 Structural Equations Models 3 Structural Equation Modeling David Kaplan 200016 Structural Equations Models 3 Structural Equation Modeling David Kaplan 2000.
17 Exercises 2Ulf H Olsson Any Questions Ulf H Olsson Univariate Normal Distribution.
Ulf H Olsson Cumulative Normal DistributionUlf H Olsson Normal density functions2 1 1 2 x 2 2 .
x e1 x u e 2u N 0 1 Ulf H Olsson.
The Chi squared distributionsIf u N 0 1 then z u 1 If z1 z2 zn are n independent 2 1 var iablesthen zi 2 n E n n.
Var 2 n 2nUlf H Olsson The Chi squared distributionsIf u1 u2 un are n independent N 0 2 var iablesthen u 2i i 2 n .
If u1 u2 un are n independent N 2 var iablesthen u 2i i 2 n E n n Var 2 n 2n 4 Ulf H Olsson.
Bivariate normal distributionUlf H Olsson Standard Normal density functions u e 2 u 2 2 uv v 2 .
2 1 u v e2 1 1 u 1u u1 u2 un n 2 1 2.
2 u u1 u2 un Ulf H Olsson Estimator An estimator is a rule or strategy for using the data to estimate the.
parameter It is defined before the data are drawn The search for good estimators constitutes much of econometrics psychometrics Finite Small sample properties Large sample or asymptotic properties.
An estimator is a function of the observations an estimator is thusa sample statistic since the x s are random so is the estimatorUlf H Olsson Small sample propertiesUnbiased E .
Biased E 1 is more efficient Var 1 Var 2 Ulf H Olsson Large sample properties.
Consistency lim n P n 1for all Asymptotic unbiased lim n E n Var 1 1 is Asymptotic Efficent lim n .
Var for all Ulf H Olsson Introduction to the ML estimatorLet be the data matrix.
x1 x2 xk where xi are vectorsThe Likelihood function is as a function of the unknownparameter vector f x1 x2 xk f xi L X Ulf H Olsson.
Introduction to the ML estimator The value of the parameters that maximizes this function are the maximum likelihood Since the logarithm is a monotonic function the values that maximizes L are the same asthose that minimizes ln LThe necessary conditions for max imiz in g L is.
ln L We denote the ML estimator ML L L is the Likelihood function evaluated at Ulf H Olsson.
Introduction to the ML estimator In sampling from a normal univariate distribution withmean and variance 2 it is easy to verify that 1 n ML ML xi and.
2 1 n ML xi x 2 MLs are consistent but not necessarily unbiasedUlf H Olsson Two asymptotically Equivalent Tests.
Likelihood ration test The Likelihood Ratio TestLet be a vector of parameters to be estimated Two ML estimates U and RThe likelihood ratio is .
The l arg e sample distribution of 2 ln is 2 d Ulf H Olsson The Wald TestIf x N then x x is d .
H 0 c q then under H 0W c q U c q is d Ulf H Olsson.
Example of the Wald test Consider a simpel regression modely x H 0 0 0 .
we know z or t W 0 Var 0 0 zis 2 1 .
Ulf H Olsson Likelihood and Wald Example fromSimultaneous Equations Systems N 218 Vars 9 free parameters 21 Df 24 .
Likelihood based chi square 164 48 Wald Based chi square 157 96Ulf H Olsson Assessing Normality and MultivariateNormality Continuous variables .
Mardias test Bivariate normal distributionUlf H Olsson Positive vs Negative SkewnessThese graphs illustrate the notion of skewness Both.
PDFs have the same expectation and variance The oneon the left is positively skewed The one on the right isnegatively skewed Ulf H Olsson Low vs High Kurtosis.
These graphs illustrate the notion of kurtosis The PDF onthe right has higher kurtosis than the PDF on the left It ismore peaked at the center and it has fatter tails Ulf H Olsson J te order Moments.
Skewness KurtosisPopulation central moments j E X j j 1 E X X is continuous and random.
Skewness 1 2 3 2Kurtosis 2 2 3Ulf H Olsson Skewness and Kurtosis.
1 and 2 can be estimated from a sample We can test H 0 Skewnes 0 and H 0 Kurtosis 0by z and 2 testsWe can even estimate and test for multi var iate kurtosis Multi var iate kurtosis 2 p E X 1 X 2.
Ulf H Olsson To Next week Down load LISREL 8 8 Adr http www ssicentral com Read David Kaplan Ch 3 Factor Analysis Read Lecture Notes.
Ulf H OlssonAsymptotic Theory 3 Lecture notes 3 Logit and Probit Regression 3 Compendium: Logistic Regression 4 Logit and Probit Regression 3 Compendium: Logistic Regression 5 Exercises 2 6 Panel Models 3 Book chapter (14): Analyzing Panel Data: Fixed – and Random-Effects Models 7 Panel Models 3 Book chapter (14): Analyzing Panel Data: Fixed – and ...

Related Presentations

Arcavi 1994 Symbol sense informal sense making in

Symbol sense: informal sense-making in formal mathematics A. Arcavi (1994). For the Learning of Mathematics 14(3), 24-35 Il punto di partenza: la nozione di number sense Number sense A “non-algorithmic” feel for numbers, a sound understanding of their nature and the nature of the operations, a need to examine reasonableness of results, a sense of the relative effects of operating with ...

10 Views0 Downloads

Making Sense of the Numbers Understanding Risks and

Making Sense of Numbers:Understanding Risks and Benefits. Michelle Burda. NNLM MAR Education and Health Literacy Coordinator. October 11, 2017. Communicating Numerical Health Information. Hi I am Michelle Burda the education & health literacy coordinator for the Middle Atlantic Region & your instructor for this session.

8 Views0 Downloads

Numbers are never just numbers s3 amazonaws com

Hurricanes Katrina & Rita. South Asia Earthquake. Death Toll = 307,000. I want to take you back in time. 2005 opened in the wake of a the tsunami. It continued with the gulf coast hurricanes and the south Asian earthquake. The death toll from these disasters was approximately 307,000. That’s like losing everyone in Buffalo, NY or St. Paul, MN.

21 Views0 Downloads

Prime numbers Composite numbers Neither prime nor

Why? because, the number 1 only has one factor, not two different factors. 1 x 1 = 1 The special case of the number 0. Zero is another special number. Zero can not be a prime number because, every number is a factor of 0. 0 x 1 does equal 0, but 0 x anything at all = 0 Zero is not a composite number either.

18 Views0 Downloads

Big Data and Patient Reported Outcomes Making Sense of

Big Data and Patient-Reported Outcomes: Making Sense of the Noise. Mike Van Snellenberg, CTO and co-founder, Wellpepper. Kristin Helps, RN, Director of Clinical Operations, Wellpepper

9 Views0 Downloads

ACCESS STEM and ELL Making sense of the acronyms to

January 5, 2015 “allwithtests” file from BPS OIIT. *As of this data file, there are 77 LEP students with a “blank” ELD level; these students are included as ELD Level 1 in this table. In addition, there are 4 students coded as LEP with ELD 6 or P.

12 Views0 Downloads

Making Sense of Organizational Change

Dyckman (1981) suggests that there are three types of rationale: 1) contextual-rationale, 2) process rationale, and 3) calculation rationale (p. 35). Professor Thomas R. Dyckman Ann Whitney Professor Emeritus of Accounting at the Samuel Curtis Johnson Graduate School of Management at Cornell University

19 Views0 Downloads

Making Sense Out of Sensors

Ford Manual Lever Position (MLP) is an example. ... Karman-Vortex Ultrasonic Karman Vortex Used by Mitsubishi in many vehicles. Very reliable. ... Cable Tie ? Usually affects operation in drive; may run OK if driving in reverse. We started communicating by writing on the cave walls. As the years went by we progressed. We invented tools to make ...

7 Views0 Downloads

Making Sense of the Social World 4th Edition

Making Sense of the Social World 4th Edition. Chapter 3: Ethics in Research

9 Views0 Downloads

Making Sense of Qualitative Data

(Bogdan & Biklen, 1992, p. 166-172, as quoted in Creswell, p. 193) Creswell recommends analyzing data using codes readers would expect to learn more about, find surprising, and address larger theoretical issues in the literature.

10 Views0 Downloads

Making Sense of GAIA University of Oxford Department of

Galaxy modelling in the era of massive surveys of the Milky Way James Binney Oxford University Outline Surveys of the Galaxy Power of dynamical models Gross structure & fine structure Hierarchical modelling How to tune the potential Surveys Proper motion Radial velocity Microlensing Parallax Proper motion catalogues USNO B1 catalog (1 billion stars 0.2as and pm) Tycho 2 (2.5 million stars to m ...

5 Views0 Downloads

Business Valuations Making Sense of the Methods and

Business Valuation Tips “There are several commonly used methods of valuation. Each method may at times appear more theoretically justified in its use than others. The soundness of a particular method is entirely based on the relative circumstances involved in each individual case.

7 Views0 Downloads