Basic Statistic Models in Decision Sciences

We explore the basic statistical models used in decision sciences here.

The basic models include:

• Central Limit Theorem
• Distributions
• Dispersions
• Population
• Sample
• T Test
• Z Test
• Chi Square test
• ANOVA and MANOVA
• Matrix Operations, Determinants, Vectors and Eigen values

Applications for prescreptive decisions - LiSP/LINGO.

Methods for Predective decision making:

• Time Series Analysis
  • Moving Average
  • Exponential
  • Holtz & Winter-Holts Model
• Auto Regressive Integrated Moving Average Models

Multi-criteria decision science:

• Interpretive Structural Modeling(ISM)
• Decision-Making Trial and Evaluation Laboratory(DEMATEL)
• Analytic Hierarchy Process(AHP)
• Interpretive Ranking Process(IRP)
• Analytic Network Process(ANP)
• Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)