➣Understanding Data

➣Data Collection and Uni-variate Distributions

➣Exploring Bivariate Distributions


➣Discrete Probability Distributions

➣Continuous Probability Distributions

➣Multivariate Probability Distributions

➣Sampling Distributions, and Control Charts


➣Hypothesis Testing

➣Inference for Regression Parameters



➣The training curriculum is designed to prepare the participants to explore Univariate, Bivariate and Multivariate Probability distributions and tasks such as Hypothesis Testing.

➣Participants will be provided enough examples and illustrations to analyze and perform ANOVA

➣Usage of Real Time Example and Case study provide confidence to the participants

➣Data from one or more areas of interest will be taken as a case study and a detailed analysis is performed

➣All calculations and analysis are done using MS EXCEL 2010 or SPSS. The spread sheets/data files used for the training will be shared with the participants.

➣The course is participative


Participants are not expected to have any Statistical knowledge as this training starts from the basic.


TOPICS covered

Methods of Data Collection Planning and Conducting Surveys Planning and Conducting Experiments Planning and Conducting an Observational Study
Types of Data Frequency Distribution Tables Graphical Methods Tools for Describing Data: Numerical Measures
Summary Measures and Decisions Two-Way Table for Categorical Data Scatterplots Correlation
Regression: Modeling Linear Relationships Fitting the model: The least-squares approach Using the model for prediction Coefficient of Determination
Residual Analysis Transformations Definition of Probability Counting Rules Useful in Probability
Conditional Probability and Independence Rules of Probability Odds and Odds Ratios Random Variables and Their Probability Distributions
Expected Values of Random Variables Bernoulli Distribution Binomial Distribution Geometric and Negative Binomial Distributions
Poisson Distribution Hypergeometric Distribution Moment-Generating Function Simulating Probability Distributions
Continuous Random Variables and Their Probability Distributions Expected Values of Continuous Random Variables Uniform Distribution Exponential Distribution
Gamma Distribution Normal Distribution Lognormal Distribution Beta Distribution
Weibull Distribution Reliability Moment-Generating Functions for Continuous Random Variables Simulating Probability Distributions
Bivariate and Marginal Probability Distributions Conditional Probability Distributions Independent Random Variables Expected Values of Functions of Random Variables
Multinomial Distribution More on the Moment-Generating Function Conditional Expectations Sampling Distribution of X-bar
Sampling Distribution of Sample Proportion Y/N Sampling Distributions: The Multiple-Sample Case Control Charts Process Capability
Point Estimators and Their Properties Confidence Intervals: The Single-Sample Case Confidence Intervals: The Multiple Samples Case Prediction Intervals
Tolerance Intervals Method Of Maximum Likelihood Terminology Hypothesis Testing: The Single-Sample Case
Multiple-Sample Case Chi-Squared Tests on Frequency Data Goodness of Fit Tests Acceptance Sampling
Regression Models with One Predictor Variable Probability Distribution of the Random Error Component Making Inferences about Slope Linear Model for Estimation and Prediction
Multiple Regression Analysis Inference in Multiple Regression Model Building: A Test for a Portion of a Model Other Regression Models
Checking Conditions and Some Pitfalls Review of Designed Experiments Analysis of Variance (ANOVA) Technique Completely Randomized Design
Relation of ANOVA for CRD with a t-Test Relation of ANOVA for CRD with a Regression Analysis of Variance for the Randomized Block Design Factorial Experiment

Note - Course content and topics to be covered in the training can be customized as per requirement for Corporates.

Faculty profile

FEES for Corporates

Based on the syllabus, contents and other requirements for the corporate training, scope with detailed inclusions and exclusions along with the fee will be shared.