Introduction and Overview

• The need for sound data in the decision-making process
• Defining key statistical terminology
• Types of data: qualitative, quantitative
• Selecting the right charts to support decisions

Assessing Probabilities

Fundamentals of probabilities

• Three ways of estimating probabilities
• Combining probabilities for a stronger outcome
• Weighing the probabilities of related and unrelated events

Making decisions with decision trees

• Blueprinting the decision tree architecture
• Applying expected values to determine the best decision

Harnessing probabilities for competitive analysis

• Leveraging backward conditional probabilities to model a competitor's decision process
• Refining probabilities based on public information

Extracting and Validating Data

Exploiting effective measuring techniques

• Interpreting data with statistical measures
• When to use the mean and other measures
• Exploring key measures of dispersion, such as standard deviation

Verifying distribution types

• Quantifying skewness and kurtosis
• Detecting outliers

Leveraging the power of distributions

• Applying the Binomial Distribution to calculate the probability of success
• Finding the probability of defects by using the Poisson Distribution

Applying Statistical Measures

Estimating population characteristics

• Selecting confidence intervals
• Estimating the mean and standard deviation

Testing hypotheses for future application

• Developing your hypothesis with tangible data
• Minimising Type I and Type II errors
• Choosing one- or two-tailed tests

Comparing statistical measures between groups

• Checking for equality of measures
• Performing measures of dispersion testing
• Discovering the sources of variability in your data

Obtaining substantive results through testing

• Matching your data with a distribution
• Selecting the best test to apply

Gathering Data Through Surveys

Applying probability-based sampling methods

• Random
• Stratified
• Systematic
• Cluster

Avoiding common mistakes in sampling

• Convenience
• Judgement

Selecting the right sample size

• Analysing the required level of confidence
• Choosing the appropriate level of accuracy

Creating your survey

• Focusing survey questions on key measures
• Selecting question types to pinpoint areas of concern
• Avoiding bias by ordering questions for accurate results

Strengthening Your Forecasting Techniques

Incorporating the appropriate trend type

• Linear
• Exponential
• Logarithmic
• Calculating the coefficient of determination
• Measuring the "goodness of fit"

Preparing your forecast

• Selecting the number of forecast periods
• Applying the trendline formula

Refining your forecast

• Analysing your data to determine seasonality
• Applying seasonal factors to improve your forecast

Identifying Misleading Statistical Techniques

Uncovering techniques used to mislead

• Data dredging
• Biased samples

Presenting data and conclusions accurately

• Communicating the main points
• Sidestepping common graphical mistakes