Wednesday, July 13, 2011

Frequently asked questions in Common multi variate techniques

Many a times, some of my friends asked about frequently asked questions in multivariate techniques at interviews, conferences etc. But, infact these questions do not have any limited scope but i tried a littel in this way here is my prefered questions.

Multi variate techniques:

Multiple regression analysis:

  • What is difference b/n  multiple regression and multivariate regression
  • How to select inde variables in to the system?
  • What are the measures of efficiency?
  • What is the specific proc in SAS
  • Assumptions underlying and the consequences of their violations.
  • Estimation techniques, adv and dis adv


Logistic regression analysis:

  • Difference b/n logistic and traditional regression
  • Assumptions if any?
  • Estimation method?
  • Efficiency measures?
  • Which domain having major applications
  • Odds ratio implementation
  • Tests of goodness of fit

Descriminant analysis:

  • What is the aim of descriminant analysis
  • Methods of constructing descriminant functions
  • Fisher discriminant function
  • Issue of multi collinearity here
  • What is cluster descriminant
  • Domain applications

MANOVA:

  • Tests of MANOVA
  • Structure of model in manova
  • Assumptions of MANOVA
  • How to use and read in SAS environment
  • Difference b/n manova and multiple regression
  • PROC MANOVA





Factor analysis:

  • What is the difference between PC and PAF (Principle factor analysis?)
  • What is a Simple or Clean Factor Structure?
  • Types of factor analysis
  • Applications in manufacturing
  • PROC PRINCOMP, how to improve the performance
  • Type of conclusions in FA

Multi dimensional scaling:

  • Types of multi dimensional scaling
  • How to decide on what dimensions respondents use when evaluating objects
  • how many dimensions they may use in a particular situation
  • test for the relative importance of each dimension
  • how the objects are related perceptually

Correspondence analysis:

  • How to use it in market research?
  • How to read the parameters?
  • Any significant tests
  • How to apply in SAS

Conjoint analysis:

  • Advantages in market research
  • Types of conjoint analysis
  • Relation with regression and logistic regression
  • Latest developments
  • Steps in the design of the studies

Cluster analysis:

  • Why it comes under multivariate techniques
  • How to choose the variables for the clustering
  • What are the types of clustering?
  • Measures for efficiency of clustering
  • Reports based on clustering


Canonical correlation:

  • Why it is important than usual correlation
  • What is the complexity involved here
  • Application area


Structural equation modeling:

  • Why it is so significant
  • Applications in SAS
  • How to interpret the results

Wednesday, June 22, 2011

Regulatory science-some concepts

Def of Regulatory science:

It is science  dealing with innovative methods and tools to asses the safety, quality and efficiency of FDA products.

Where is the role of regulatory professional lies in:

  • It begins with R&D Phase
  • Moves in to clinical trials analysis
  • It extends to pre market apporvals 

Thursday, March 3, 2011

Steps in data analysis:

The following are general steps in in data analysis:

1.      Requirement analysis
2.     Formulation of hypotheisis
3.     Designing the survey
4.     Data collection/data tabulation.
5.     Performance prescribed analysis and sample data.
6.     Evaluate results and carry analysis on full data.
7.     Tabulate results and conclusions.
8.     Limitations and Assumptions if any.
We will see explnation on them in the next post.

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