This course is about Statistics and Data Analysis. The course will teach you the advanced concepts related to Statistics and Data Analysis and help you in applying these concepts. Various examples and datasets will be used and then we will show you how to use Microsoft Excel to perform these calculations.

Course Objectives

At the end of course participants should be able to:

• Understand descriptive and Inferential Statistics.
• Understand statistical calculations.
• Understand statistics from basic to advance using excel.

Duration                 5 Days

Who Should Attend

The course targets Statistician, analyst, or a budding data scientist and beginners who want to learn how to analyse data with excel.

Course Content

• Statistics Introduction and Definitions
• Types of Data in Excel - Text, Numbers, Date/Time, Logical
• Qualitative vs Quantitative Data / Continuous vs Discrete
• Nominal, Ordinal, Interval & Ratio
• Population and Sample (Theory)
• Understanding Data Types
• Understanding Formulas and Functions
• Relative vs Absolute Reference
• Formulas, Functions and Named Ranges
• Descriptive Statistics
• Section Introduction - Descriptive Statistics
• Descriptive Statistics - Central Tendency
• Descriptive Statistics - Variation
• Installing Data Analysis Pack and Calculating Descriptive Statistics
• Descriptive Statistics - Central Tendency
• Descriptive Statistics - Variation (Excel)
• Descriptive Statistics - Shapes
• Descriptive Statistics
• Data Visualization
• Three commonly used Charts
• Create Histogram
• Histogram Shapes
• Create Box and Whisker Plot
• Scatter Diagram
• Create Scatter Plot
• Data Visualization
• Introduction to Basic Probability Concepts
• Basic Probability Concepts
• Calculate Factorial, Permutations and Combinations
• Basic Probability Concepts
• Probability Distributions
• Central Limit Theorem Demonstration
• Normal Probability Distribution
• Binomial Probability Distribution
• Other Distributions Related to Binomial Distribution
• Poisson Distribution
• Probability Distributions
• Introduction Hypothesis Testing
• Hypothesis Testing - Types of Errors
• Hypothesis Testing Explained
• Tests for Mean, Variance and Proportions
• One Sample z Test
• Two Tail Example
• Understanding the p Value
• Introduction to T Functions
• One Sample t Test - Example
• One Sample p Test
• Two Sample z Test
• Two Sample t Test - Equal Variance
• Two Sample t Test - Unequal Variance
• Two Sample t Test - Paired t Test
• Two Sample p Test
• Introduction Tests for Variance (F and Chi Square)
• F Test to Compare Variances
• Plotting F Distribution
• F Distribution Related Functions
• F.TEST Function
• F Test Using Data Analysis Pack
• Chi Square Test for Variance
• Plotting Chi Square Distribution
• Chi Square Distribution Related Functions
• Chi Square Test
• Introduction to ANOVA
• Understanding the concept of ANOVA
• Formulas and calculations in ANOVA
• Performing ANOVA
• Two Factor ANOVA without Replication
• Two Factor ANOVA with Replication
• Goodness of Fit and Contingency Table
• Introduction Goodness of Fit and Contingency Tables
• Goodness of Fit Test
• Contingency Table
• Correlation and Linear Regression
• Introduction to Correlation
• Plotting Scatter Plot and Calculating Correlation Coefficient
• Correlation Coefficient for Multiple Variables
• Correlation Related Functions
• Correlation vs Causation
• Coefficient of Determination
• Manual Calculation
• Slope, Intercept
• Forecast, Linear, Trend & Linest
• Regression using Data Analysis Pack

General Notes

• This course is delivered by our seasoned trainers who have vast experience as expert professionals in the respective fields of practice. The course is taught through a mix of practical activities, theory, group works and case studies.

• Training manuals and additional reference materials are provided to the participants.
• Upon successful completion of this course, participants will be issued with a certificate.