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SAS Analytics and Predictive Modelling

SAS Analytics and Predictive Modelling

SAS Analytics and Predictive Modelling Online Training:

Who is Eligible:

Any Graduates/Post Graduates are eligible.
Any Functional/technical background consultants are eligible to learn SAS Analytics and Predictive Modelling Online Training.

  • 2

    Measure of Central Tendency

    00:00
  • 8

    Histograms, QQ Plots, and Probability Plots

    00:00
  • 4

    Continuous Probability Distributions [Uniform, Normal, Exponential]

    00:00
  • 5

    Discrete Probability Distributions[Binomial, Poisson, Negative Binomial,
    Hyper Geometric]

    00:00
  • 7

    Sampling Theory[Probability and Non Probability]

    00:00
  • 2

    Inferential Statistics – Hypothesis Testing [Parametric & Non-Parametric]

    00:00
  • 3

    Testing Single Means(T-test)

    00:00
  • 4

    Testing Differences between Two Means(T-test)

    00:00
  • 5

    Random Assignment of Subjects

    00:00
  • 6

    Two Independent Samples: Distribution Free Tests

    00:00
  • 7

    One-tailed versus Two-tailed Tests

    00:00
  • 8

    Paired T-tests (Related Samples)

    00:00
  • 2

    One-way Analysis of Variance

    00:00
  • 3

    Two-way Analysis of Variance

    00:00
  • 4

    Interpreting Significant Interactions

    00:00
  • 5

    Unbalanced Designs: PROC GLM

    00:00
  • 6

    Analysis of Covariance [ANCOVA]

    00:00
  • 2

    Questionnaire Design and Analysis

    00:00
  • 4

    A Short-cut Way to Request Multiple Tables

    00:00
  • 5

    Computing Chi-square from Frequency Counts

    00:00
  • 6

    McNamara’s Test for Paired Data

    00:00
  • 7

    Computing the Kappa Statistics (Coefficient of Agreement)

    00:00
  • 10

    Chi-square Test for Trend

    00:00
  • 11

    Mantel-Haenszel Chi-square for Stratified Tables and Meta-Analysis

    00:00
  • 2

    Significance of a Correlation Coefficient

    00:00
  • 5

    Partitioning the Total Sum of Squares

    00:00
  • 6

    Plotting the Points on the Regression Line

    00:00
  • 7

    Plotting Residuals and Confidence Limits

    00:00
  • 8

    Adding a Quadratic Term to the Regression Equation

    00:00
  • 3

    Multiple Regression [Model diagnostics]

    00:00
  • 4

    Logistic Regression [Model diagnostics]

    00:00
  • 7

    Pattern Discovery [Cluster Analysis, Market Basket Analysis]

    00:00
  • 8

    Forecasting [MA, AR, ARMA, ARIMA]

    00:00
  • 9

    Decision Tree Analysis [CHAID, CART]

    00:00
  • 3

    Finance Domain[Credit Card/ Insurance and Banking Domains]

    00:00
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