Decision Making: Interpreting Data

Course Overview

In today's fast-paced working environment, professionals at every level make important decisions daily. Dealing with large volumes of data and making informed decisions based on statistical evidence, not emotion, is crucial in gaining a competitive edge.

This introductory course provides you with the techniques to support your business decisions using well-established quantitative methods. You learn to gather data, identify trends and analyse patterns to solve business problems. By employing statistical tools, you learn to format and present information with clarity and precision.

Audience

This course is valuable for anyone involved in decision making. Those who manage quality, people, processes or any quantifiable resource will find this course valuable. No prior knowledge of statistics is required.

Skills Gained

• Apply and interpret data to support effective decision making
• Present results graphically and numerically to support negotiations
• Validate data quality using software applications
• Minimise risk while assessing uncertainty and probability
• Estimate outcomes and draw conclusions based on tested hypotheses
• Forecast results based on trends, patterns and sequences

Course Outline

Introduction to the Statistical Toolkit

The importance of statistics

• Alleviating preconceptions and fears about statistics
• Describing the parameters of real-world problems
• Presenting the results
• Exposing misleading graphs to avoid incorrect assumptions

Applying statistical terminology

• Deciphering the functions
• Measuring and collecting data
• Highlighting graphical presentations
• Avoiding mistakes based on insufficient information

Analysing and Presenting Data

Collecting data

• Reducing large volumes of data by sampling
• Comparing your collection against the population

Extracting information from data

• Determining central tendency using various methods
• Mean
• Median
• Mode
• Mid-range
• Calculating spread of data
• Range
• Variance
• Standard Deviation
• Ensuring confidence and accuracy

Designing graphs

• Summarising data visually
• Applying the appropriate graph type to simplify presentation

Validating Data Quality

Leveraging statistical tools

• Simplifying statistical tasks with Minitab and Excel
• Crafting graphs that accurately represent data

Distribution of the data

• Modelling data with bell curves
• Dividing data into percentiles
• Identifying outliers
• Applying analysis of variance (ANOVA) to decision making

Assessing Risks

Assigning probability

• Determining the odds of success or failure
• Building a frequency matrix to illustrate possibilities
• Identifying scenarios that affect outcomes
• Calculating probability based on a chain of events

Minimising risks

• Interpreting the level of risks within your project
• Justifying decisions based on calculation of probability

Evidence-Based Decision Making

Estimating outcomes

• Evaluating the quality of data to make a good prediction
• Visualising acceptable range of options

Drawing conclusions

• Formulating the right hypothesis
• Choosing the appropriate tests
• Performing hypothesis testing on real-world applications
• Accepting or rejecting results

Forecasting Business Trends

Comparing and contrasting trends

• Fitting a shape to a trend
• Identifying data relationships: linear, curved and others
• Estimating return on investment (ROI)

Predicting future results

• Refining predictions based on historical data
• Extrapolating trend lines to manage uncertainty

Applying Metrics to Real-World Scenarios

• Step-by-step statistics: the circular method
• Applying the circular method to a business case
• Resolving problems with statistical solutions