Statistics is always a difficult subject for business professionals. Our pursuit is make this subject simple and easy for you. Instead of focusing on the theory (like in academics), we have packaged the application of important statistical principles to real-life business situations.

### Is it right for you?

• Team members of improvement projects
• Executive Assistants

### What will you learn

• Need for Statistics in Business
• Statistics, Population, Population Parameter, Sample, & Sample Statistic
• Types of Statistics – Descriptive Statistics & Analytical Statistics
• Definition of Probability Distribution, Types, & Importance
• Measures of Central Tendency – Mean, Median, Mode
• Measures of Dispersion – Range, Span, Variance, Standard Deviation
• Types of Descriptive Statistics – Graphical, Numerical
• Definition, Application & Properties of a Normal Distribution & Outlier
• Confidence Limits, Confidence Level & Confidence Intervals
• Definition of Central Limit Theorem & its Application
• Hypothesis Testing
• Need for Statistical Significance & Statistical Inference
• Hypothesis Testing, Applications & Basics
• Hypothesis Statements – Null & Alternative Hypothesis
• Significance Levels, & Alpha Values
• Tests of Significance – Statistical & Practical Significance
• Test Statistic & P Value & Its Interpretation
• Errors in Hypothesis Testing & Types of Errors
• Hypothesis Tests for Means, Variance, Proportions
• Selection of Hypothesis Tests & Criteria for Selection
• Z-Test, Z-statistic, & Assumptions
• t-Test, t-Statistic, 1-t Test & 2-t Test, & Assumptions
• Paired Data – Paired t-Test, Preparation & Procedure
• ANOVA & F-test, Assumptions, Preparation & Procedure
• Chi-square Test & Statistic, Assumptions, Preparation & Procedure
• Proportions Test – 1-p Test & 2-p Test, Assumptions, Preparation & Procedure
• Correlation & Regression
• Correlation, Regression, Scatter Plots, & Correlation Coefficient
• Procedure of Simple Linear Correlation & Interpretation of Scatter Plots
• Application of Regression & its Types
• Regression Line of Fit, Regression Equation, & its Statistical Significance
• R-SQ Value & Procedure of Simple Regression
• Prioritization of Causes, & Pareto Principle

### Features of the Course

• 6 chapters with 210 mins of self-learning content
• Interactive audio-visual medium with ample manufacturing and service industry examples
• Interactive self-assessment quiz for every chapter