Institute for Forecasting Education - Statistics Modules

IFE Home >>> Workshops >>> Statistics Modules

Go To:

Statistical Analysis for Business
Workshop Modules

The Statistical Workshops offer an organization the opportunity to provide a group of its employees with an introduction or refresher on statistical concepts and methods which are essential for business analysis. Course materials can be adapted to embed the organization's own data and problem areas.

The series is presented in half-day modules of which 1-6 modules form a 3-day course. Nine modules is the equivalent of an introductory course in Statistics.

Workshop Objectives
1. Present the fundamental concepts of statistical reasoning and methodology.
2. Enhance capability to understand and undertake statistical studies
3. Acquire expertise in data handling and analysis through use of a professional statistical package

Module 1: Data, Distributions & Averages
Module 2: Variability & Normality
Module 3: Correlation & Regression
Module 4: Fundamentals of Probability
Module 5: Estimation & Confidence Intervals
Module 6: Statistical Significance Tests
Module 7: Comparing Groups/ANOVA
Module 8: Cross-Tab Analysis
Module 9: Survey Sampling
Module 10: Quality Control
Module 11: Time Series & Extrapolation
Module 12: Decisions & Risks

Module 1: Data, Distributions & Averages

Data Sets: Types of variables and measurements
Organizing data into arrays and frequency charts
Useful graphs
Describing variables by average values
Symmetric and asymmetric distributions
Identifying and treating outliers

Index | Top

Module 2: Variability & Normality

Describing variation about an average
Absolute Vs relative variation
Using bell-shaped curves
Understanding the Normal distribution
Dealing with non-Normal distributions

Module 3: Correlation & Regression

Relating two variables
Scatterplots
Correlation coefficients
Regression lines
Making predictions
Multiple predictors

Module 4: Fundamentals of Probability

Meaning of probability
Distinguishing types of probability
Probability trees
Using probability to assess the accuracy of a procedure
Developing a probability distribution
Random sampling

Module 5: Estimation & Confidence Intervals

Understanding chance variation
Sampling distributions
Monte Carlo simulations
Law of averages
Point estimates and confidence intervals
Confidence Vs Precision
How to determine optimal sample size

Module 6: Statistical Significance Tests

Intro to Test of Significance
Null and Working Hypotheses
Prob-values
Meaning of statistical significance
Statistical Vs practical significance
t tests for averages
Testing significance of regression coefficients

Module 7: Comparing Groups/ANOVA

Treatment Vs Control Groups
Experimental Vs observational studies
Comparing two independent groups
Matched pair comparisons
Three or more groups-ANOVA

Module 8: Cross-Tab Analysis

Cross tabulations
Pivot tables
Chi-Square tests
Logistic regression

Module 9: Survey Sampling

Questionnaire design
Sampling designs and methods
Determining required sample size
Analyzing interpreting and presenting results

Module 10: Quality Control

Statistical process control
Pareto diagrams
How to read control charts
Calculating control limits
Monitoring % defective

Module 11: Time Series & Extrapolation

Time series data
Trend and seasonality
Linear extrapolations
Smoothing the data
Exponential smoothing
Principles of forecasting

Module 12: Decisions & Risks

Decisions and tradeoffs
Rating systems
Dealing with uncertainty
Decision trees
Risk Analysis