SMCD Professional Training for Analysts and Managers

Aim: Uses Excel to introduce some simple aspects of statistical analysis. Shows how to derive meaning from figures.

Who is it for: This course is for non specialist staff who need to improve their data analysis skills. It is suited to people or teams who need to summarise or derive meaning from large quantities of information.

Requirements: The course uses guided Excel based practical exercises. A basic or intermediate level of Excel skill is needed.

Topics: Documenting, exploring and condensing data. Checking and ensuring data quality. Averages, variability, histograms, samples, scatter diagrams. Trends forecasting and seasonality, introduction to simple regression and correlation. Excel basics and statistical functions. Pivot tables and cross tabulations, the analysis toolpak.

Benefits: Data is not enough! Insights from data are needed to improve business outcomes.

Notes:

This course can be paired or combined with Data Presentation. The duration can be extended if Data Analysis is entirely new to the participants.

The course uses Excel and some new Excel skills may be acquired. However it is not a course in Excel.

Aim: Introduce standard and effective methods of data presentation, the difference between findings and messages, and the need to gain insight then demonstrate your messages simply and clearly using small tables and graphs.

The course is focussed on how to present data in reports to non specialist audiences who may have no taste for numbers or not enough time to absorb complex charts and tables. It does not teach Powerpoint or speaking skills. The course uses practical group exercises. The material is based firmly on research into what is effective and what is not.

Who is it for: This course is for staff who need to gain skills in data presentation and produce better, more influential reports aimed at non specialists. It can be run for non-specialists or for technical specialists.

Requirements: Participants need numeracy skills. Breakout groups will prepare charts and graphs for discussion – each group needs the skills to do this. The course works best when all participants are at roughly the same level of numeracy.

Topics: The audience, and how to consider them. Messages and Stories. Data and chart fundamentals, when to use tables and charts. Demonstration tables: essential standards, derived statistics, aggregates and order, guidelines for formatting and layout, how to read and analyse reference tables. Presentation charts: essential standards, accessibility, simplicity, types (pie, line, bar and column and variations). What to avoid. Narrative – an introduction. Optional discussion of powerpoint and formatting.

Benefits: Management spend less time trying to understand obscure reports. Reports are more effective and communicate your position more clearly.

Notes: Basic Data Analysis is a good preparation for this course. The two courses combine well.

Aim: To introduce the essential techniques of parametric statistical analysis using Excel: condensing data, sampling, some hypothesis tests, correlation, regression and time series analysis.

This course refreshes the topics of “Data Analysis” and introduces some more professional concepts such as statistical tests. These are explained in a simple and practical way, but because the concepts of statistics are not very intuitive the course needs at least two days.

Who it is for: This course would suit numerate analysts, including economists, researchers, scientists and engineers, who have previously had little or no background in statistical analysis. If you have completed our basic data analysis course, or are already at that level, “Introduction to Statistics” could be your next step, but it is a distinct step up in sophistication.

Requirements: The course uses Excel based practical exercises. A basic or intermediate level of Excel skill is needed.

Topics: Overview of the fundamentals: condensing data, histograms, averages, etc. Exploring the data before analysis. Excel data analysis and statistical functions and pivot tables. Sampling: introductory concepts. Inferences from sample to population; confidence intervals and introductory hypothesis testing. The Normal distribution and its uses. Further hypothesis tests of a mean and a proportion. Sample size determination. Charting your results. Tests of associations using proportions. Simple correlation of values & ranks. Cross plottings. Simple regression. Introduction to Multiple Regression and some simple testing procedures. Charts & trends. Smoothing and forecasting.

Benefits: Ability to provide a deeper level of data analysis, with a greater understanding of the value that formal statistical procedures can add.

Aim: Show why and how to make sound decisions based on evidence and good reasoning.

Who is it for. The course is aimed at Middle Management, and particularly those who are heading for Senior Roles where they will make significant contributions to important business or policy decisions.

Requirements: The course has no special requirements

Topics: Why use evidence? Types of evidence. The right question. Sourcing and finding evidence. Judging and grading individual items of evidence systematically or in a team context. Judging and grading evidence as a whole. Identifying gaps. Avoiding common logical errors. Technical evidence. Working with experts. Project appraisal. Statistical terms. Project and policy cycles. ROAMEF and other frameworks.

Benefits: Improved decisions for complex issues. Better team communication. More effective use of experts. Improved accountability.

Courses on research skills can often be customised to suit the need.

Dr McCormick regularly teaches an introduction to Operational Research and a course on modelling skills for research on behalf of the Operational Research Society. He has also delivered a full range of foundation courses for beginning Operational Researchers, on the topics of modelling, statistics, optimisation, and simulation. If you need a course of this nature, Dr McCormick will work jointly with the Operational Research Society. Specialist lecturers may be used depending on availability.

He has contributed to courses on Risk, Social Research and related topics, and can incorporate these into customised courses. If you need something strongly focused on such topics he would seek to either direct you to suitable experts or work with experts to provide training.