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[咨询答疑] 求统计Master(Pre-Accounting PhD)选课

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发表于 2013-3-21 11:49:23 | 显示全部楼层 |阅读模式
目前都还没收到offer,这次的会计博士申请估计是全军覆没了。但是有申请到Templestatistics master,打算要曲线救国了。请问各位前辈要选哪些课程可以增加自己毕业后申请会计博士(主要作financial archival research)的竞争力,麻烦帮我评估一下,感谢!
Temple的统计选修课程list如下,可选6门或者超过一些也可:
8101.Stochastic Processes   (3 s.h.)
Prerequisite: Calculus.
This is a first course in stochasticprocesses, with an emphasis on continuous-time models that support applicationsin financial mathematics and derivative evaluation.  The course covers fundamentals ofprobability, limit theorems, conditional expectation, change of measures,Markov chains, random walks, martingales, Brownian motion, the Ito integral,stochastic differential equations, and the Black-Scholes model and its use inevaluating a variety of financial derivatives.

8103.Sampling Theory   (3 s.h.)
Prerequisite: STAT 8003 or permission ofinstructor.
In presenting theory and application ofsampling from finite populations, topics in this course include random,stratified, cluster, and systematic sampling; estimation of means andvariances; optimal allocation of resources; problems of nonsampling errors; andratio and regression estimation.

8104.Matrix Theory for Statistics   (3 s.h.)
Prerequisite: Undergraduate linear algebraor permission of instructor.
This course covers vector spaces, linear independenceof vectors and basis, matrices and algebraic operations on matrices,determinants, rank of a matrix, inverse of nonsingular matrices, linearequations and their solutions, generalized inverse of a matrix, eigen valuesand vectors of matrices, diagonalization theorems, quadratic forms and theirreduction to sum of squares, and Jacobians.

8105.Time Series Analysis I   (3 s.h.)
Prerequisite: STAT 8002 or permission ofinstructor.
This course covers theory and applicationof univariate time series analysis, including both time domain and frequencydomain methods.  It considers stationaryand nonstationary linear processes, time series model building, forecasting,unit root test, intervention models and outlier detection, spectral theory ofstationary processes, spectral windows, and estimation of spectrum.

8106.Linear Models I   (3 s.h.)
Prerequisite: STAT 8002, STAT 8004, andSTAT 8104 or permission of instructor.
This course covers the basic theory andpractice of generalized linear models (GLM), such as the logistic, Poisson andgamma regression, as well as models for multilevel or longitudinal Gaussianresponses, such as the hierarchical linear model and linear mixed model.Students work with R and SAS throughout the semester.  

8107.Design of Experiments I   (3 s.h.)
Prerequisite: STAT 8004 or permission ofinstructor.
The course covers principles ofexperimental designs, completely randomized designs, multiple comparisons,randomized block design, latin square design, missing value problems, analysisof covariance, and factorial experiments.

8108.Applied Multivariate Analysis I   (3s.h.)
Prerequisite: STAT 8004 and STAT 8104 orpermission of instructor.
The course discusses multivariate normaldistribution; marginal and conditional distributions; estimation of populationmean vector and dispersion matrix; correlation, partial correlation, andmultiple correlation coefficients; Hotelling's T2; MANOVA; discriminantfunction; repeated measurements analysis; principal components and canonical correlation;factor analysis; and multidimensional scaling.

8109.Regression, Time Series, and Forecasting for Business Applications   (3 s.h.)
Prerequisite: STAT 5001 or permission ofinstructor.
This intermediate-level course coversregression analysis, time series analysis, and forecasting. The course isapplication oriented, and standard statistical packages such as MINITAB areintroduced and extensively used.

8111.Survey Techniques for Business Applications  (3 s.h.)
Prerequisite: STAT 5001 or permission ofinstructor.
This application-oriented course deals withstatistical and nonstatistical aspects of organizing a sample survey. Includedare discussions of objectives, measurement, sample selection, pilot testing,data collection, data editing, summarization and interpretation of results, anddescriptions of various sampling schemes. Students may be required to plan andexecute a survey.

8112.Statistical Methods for Business Research I  (3 s.h.)
Prerequisite: One-year undergraduatestatistics courses.
Part I of a doctoral level, one-yearsequence of courses for Ph.D. students in the Business Administration program.The course covers a variety of statistical methods useful in business research,such as multiple regression analysis, ANOVA, linear models, analysis ofcovariance, logistic regression, principal component analysis, exploratoryfactor analysis, and canonical correlation analysis. Emphases are placed onrationales, assumptions, techniques, and interpretation of results fromcomputer packages.  Relevant mathematicalresults are presented, but proofs or abstract arguments are avoided. Thelectures cover computer usages, such as R and/or SAS, and the students areexpected to work with SAS (or equivalent packages) throughout thesemester.  

8113.Statistical Methods for Business Research II  (3 s.h.)
Prerequisite: STAT 8112 or equivalent.
Part II of a doctoral level, one-yearsequence of courses for Ph.D. students in the Business Administrationprogram.  Topics covered in this courseinclude discriminant analysis, confirmatory factor analysis and structuralequations modeling, time-series intervention analysis, survival (event history)analysis, MANOVA, multivariate profile analysis, hierarchical linear models(HLM), and linear mixed models (LMM)  formultilevel data.

8115.Nonparametric Methods   (3 s.h.)
Prerequisite: STAT 8002 or permission ofinstructor.
This thorough course in nonparametricstatistics covers estimation and testing of hypotheses when the function formof the population distribution function is not completely specified.

8116.Categorical Data Analysis   (3 s.h.)
Prerequisite: STAT 8002 or permission ofinstructor.
This course covers sampling models andanalyses for discrete data: Fisher's exact test, logistic regression, ROCanalysis, log-linear models and Poisson regression, conditional logisticregression, Cochran-Mantel-Haenszel test, measures of agreement betweenobservers, quasi-independence, multinomial logit models, proportional oddsmodel, association models, generalized estimating equations (GEE), generalizedlinear mixed model (GLIMMIX), GSK models, and composite link functions.  Students work with R and SAS throughout thesemester.

8117.Clinical Trials   (3 s.h.)
Prerequisite: STAT 8002 or STAT 8004 orpermission of instructor.
This course provides an introduction to thespecial problems associated with medical trials on humans. Topics includerandomization; sample-size determination; methods for early trial termination;and tests for superiority, equivalence, and non-inferiority. Also discussed arechoice of endpoints, control, side effects, use of historical data,meta-analysis, and the ethics of experimentation on humans.
8121. Statistical Computing   (3 s.h.)
Prerequisites: STAT 8004 or permission ofinstructor.
This course deals with the use of computersin solving statistical problems. Topics include floating point architecture,random number generation, design of statistical software, computational linearalgebra, numerical integration, and optimization methods.

8122.Advanced SAS Programming   (3 s.h.)

8123.Time Series Analysis and Forecasting   (3s.h.)
Prerequisite: ECON 8009, STAT 8002, STAT8101, or an advanced undergraduate statistics and probability course equivalentto MATH 3031 or MATH 3032.
This time series analysis course withfinancial and business applications covers important univariate and multivariatetime series methods, including ARIMA models, intervention analysis and outlierdetection, time series regression, volatility and GARCH models, vector timeseries, and cointegration.

9001.Advanced Statistical Inference I   (3s.h.)
Prerequisite: Advanced calculus, STAT 8001,and STAT 8002 or equivalents.
Background: Matrix Theory. Estimation:Sufficiency, Completeness, UMVU Estimation, Information Inequality, InvariancePrinciple, Bayes Estimation, Admissibility, Maximum Likelihood Estimation, LargeSample Properties of Estimators.

9002.Advanced Statistical Inference II   (3s.h.)
Prerequisite: STAT 9001.
Testing of Hypotheses: Neyman-PearsonFundamental Lemma; Uniformly Most Powerful Tests, Confidence Intervals, andLikelihood Ratio Tests; Asymptotic Tests; Multiple Hypotheses Testing.

9101.Time Series Analysis II   (3 s.h.)
Prerequisite: STAT 8105 or permission ofinstructor.
This course covers the theory andapplication of multiple time series analysis and special topics. It deals withtransfer function models, time series regression with autocorrelated errors,ARCH and GARCH models, vector time series models, cointegration, state spacemodels, long memory processes and nonlinear processes, and time seriesaggregation and disaggregation.

9106.Linear Models II   (3 s.h.)
Prerequisite: STAT 8106 or permission ofinstructor.
As a continuation of STAT 8106, this coursecovers the theory and practice of analyzing multivariate repeated/correlatednon-Gaussian responses, with or without missing observations.  It includes missing at random (MAR) models,informative missingness, EM algorithm, multiple imputations, quasi-likelihoodestimation, generalized estimating equations (GEE), transition models, Gibbssampling, and Markov Chain Monte-Carlo (MCMC) technique.  Students work with R, SAS, and WinBugsthroughout the semester.

9107.Design of Experiments II   (3 s.h.)
Prerequisite: STAT 8107 or permission ofinstructor.
This course covers symmetrical andasymmetrical factorial experiments, fractional replication, split plot design,balanced and partially balanced incomplete block designs with and withoutrecovery of interblock information, and lattice designs.

9108.Multivariate Analysis II   (3 s.h.)
Prerequisite: STAT 8002 and STAT 8108 orpermission of instructor.
This course is a study of specializedtopics in multivariate analysis.
发表于 2013-3-22 00:39:49 | 显示全部楼层
那得看楼主之前本硕什么专业,什么知识结构啊,这样别人怎么给你建议
 楼主| 发表于 2013-3-25 05:01:41 | 显示全部楼层
不好意思,沒有跟大家先講一下我的背景。
我本科是念財政系(Public Finance),大學有修過微積分、統計學、微觀&宏觀經濟學及租稅理論。
研究所讀會計,當時有修計量經濟學及多變量分析。
麻煩各位給個建議,感謝!
发表于 2013-3-25 06:03:33 | 显示全部楼层
建议修能handle的最高级的课程,比如9001,9002,9101,9106这些,以及必要的先修课程。
发表于 2013-3-28 00:31:38 | 显示全部楼层
zhanghj89 发表于 2013-3-22 00:39
那得看楼主之前本硕什么专业,什么知识结构啊,这样别人怎么给你建议

楼主应该木有修过中高级的econ课吧,为啥不读个经济ms,而选择读统计呢?
发表于 2013-3-28 00:32:50 | 显示全部楼层
godss1985 发表于 2013-3-25 05:01
不好意思,沒有跟大家先講一下我的背景。
我本科是念財政系(Public Finance),大學有修過微積分、統計學、 ...

楼主应该木有修过中高级的econ课吧,为啥不读个经济ms,而选择读统计呢?
 楼主| 发表于 2013-3-28 00:39:58 | 显示全部楼层
zhanghj89 发表于 2013-3-28 00:32
楼主应该木有修过中高级的econ课吧,为啥不读个经济ms,而选择读统计呢? ...

統計跟經濟比起來的話,我的統計背景相對薄弱。
大學微觀及宏觀經濟有修過中級課程了,而統計只有最初級的水準。
所以就選統計搂~~~
发表于 2013-3-28 00:45:15 | 显示全部楼层
godss1985 发表于 2013-3-28 00:39
統計跟經濟比起來的話,我的統計背景相對薄弱。
大學微觀及宏觀經濟有修過中級課程了,而統計只有最初級的 ...

貌似,econ 的ms 修的那些高级计量课就够用了吧
发表于 2016-10-19 09:09:48 | 显示全部楼层
请问楼主现在是在temple吗?
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