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Course Outline
What Statistics Can Offer to Decision Makers
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Descriptive Statistics
- Basic statistics - identifying which statistics (e.g., median, average, percentiles, etc.) are most relevant for different distributions
- Graphs - understanding the importance of accuracy (e.g., how the construction of a graph influences decision-making)
- Variable types - determining which variables are easier to manage
- Ceteris paribus - acknowledging that conditions are always in motion
- Third variable problem - how to identify the true influencing factor
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Inferential Statistics
- Probability value - understanding the meaning of the P-value
- Repeated experiment - how to interpret results from repeated experiments
- Data collection - recognizing that while you can minimize bias, you cannot eliminate it entirely
- Understanding confidence level
Statistical Thinking
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Decision making with limited information
- how to assess whether there is sufficient information
- prioritizing goals based on probability and potential return (benefit/cost ratio, decision trees)
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How errors accumulate
- Butterfly effect
- Black swans
- What is Schrödinger's cat and what is Newton's Apple in business
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Cassandra Problem - how to measure a forecast when the course of action has changed
- Google Flu trends - how it went wrong
- How decisions make forecasts outdated
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Forecasting - methods and practicality
- ARIMA
- Why naive forecasts are often more responsive
- How far back should a forecast look?
- Why more data can sometimes lead to worse forecasts?
Statistical Methods Useful for Decision Makers
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Describing Bivariate Data
- Univariate data and bivariate data
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Probability
- why measurements differ each time?
- Normal Distributions and normally distributed errors
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Estimation
- Independent sources of information and degrees of freedom
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Logic of Hypothesis Testing
- What can be proven, and why it is often the opposite of what we want (Falsification)
- Interpreting the results of Hypothesis Testing
- Testing Means
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Power
- How to determine a good (and cost-effective) sample size
- False positive and false negative and why it is always a trade-off
Requirements
Strong mathematical skills are required. Prior exposure to basic statistics (i.e., working with individuals who perform statistical analysis) is also required.
7 Hours
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 1300 € + VAT*
Contact us for an exact quote and to hear our latest promotions
Testimonials (3)
knowledge of the trainer, tailor based, all topics covered
eleni - EUAA
Course - Forecasting with R
The variation with exercise and showing.
Ida Sjoberg - Swedish National Debt Office
Course - Econometrics: Eviews and Risk Simulator
The real life applications using Statcan and CER as examples.
