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Who should attend
- CFOs looking to design-execute original finance-accounting econometric research studies
- CEOs looking to improve quantitative-based decision -making
- CROs looking to develop new forms and insights for marketing and competition research
- Board Members looking to fully monetize Big Data for the shareholders/stakeholders
- R+D/ Product Development Teams looking for direct connections
- Business Development Directors looking to proactively open up new opportunities
About the course
This comprehensive Oxford seminar will integrate the concepts, variable-analysis, interpretation, and applications to forecasting and managerial decision making of sophisticated multivariate econometrics modeling.
It will provide senior managers with high-level skills and techniques to both perform basic econometric analysis, as well as interpret and apply econometrics outputs to a wide range of quantitative and qualitative problem-solving – covering all facets of hypothesis testing, variables selection, data types, statistical analysis and error tolerances, along with inferences-insights, correlations, and trends.
The seminar will utilize inexpensive software applications linked within Excel to perform high-level econometric research-analysis-review on par with the “best practices” used in contemporary economics, corporate forecasting, and Wall Street investment banking – helping managers become fluent in the terminology and process-application of econometrics to everyday decision making contexts.
Specifically you will learn to:
- Design and produce all facets of an original business research study
- Collect and format various types of quantitative and qualitative data
- Perform different models of multivariate econometric analyses with applications in Excel
- Analyze detailed statistical output from econometric model-software
- Draw inferences to support high-level managerial decision making
- Write a detailed, yet succinct, executive summary of research findings
- Model Design, Hypotheses, Variables, Structure, Outcomes, Quantitative and Qualitative Inputs
- Software Options - Linking Models and Confirmation Metrics
- Cross Sectional Samples - Time Series Sequences - Longitudinal Tracking
- Primary Data vs. Secondary Data Costs and Acquisition .
- Descriptive Outcomes vs. Predictive Outcomes - Dummy Variables / Indicators / Surrogates
- Single-Variable vs. Multi-Variable Descriptors and Predictors - Correlation vs. Cause-And-Effect
- Punctuated Trending vs. Real-time Fluidity - Static Formations vs. Dynamic-Changing Models
- Micro-economic vs. Macro-economic Decisions - Indicators, Lagged Variables, Barometers/Bellwethers
- Problems of Multicollinearity and Autocorrelation - Caveats of Explaining Variance
- Drawing Inferences Rather than Conclusions and Confidence Intervals in Econometric Forecasts
- Packaging analysis-results for Optimum Explanation & Problems with Overreach of Statistical Outputs
- Personal-Managerial Bias Impacts Interpretation and Distilling Data Output into Actionable Intel
- Disseminating Data Output for Maximum Decision Making Impact
Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
We are happy to help you find a suitable online alternative.