# Data Science for Managers (short course)

I am teaching part of a short-course on Data Science for Managers from 10-12 October in Melbourne.

### Course Overview

The impact of Data Science on modern business is second only to the introduction of computers. And yet, for many businesses the barrier of entry remains too high due to lack of knowhow, organisational inertia, difficulties in hiring the right manpower, an apparent need for upfront commitment, and more.

This course is designed to address these barriers, giving the necessary knowledge and skills to flesh out and manage Data Science functions within your organisation, taking the anxiety-factor out of the Big Data revolution and demonstrating how data-driven decision-making can be integrated into one’s organisation to harness existing advantages and to create new opportunities.

Assuming minimal prior knowledge, this course provides complete coverage of the key aspects, including data wrangling, modelling and analysis, predictive-, descriptive- and prescriptive-analytics, data management and curation, standards for data storage and analysis, the use of structured, semi-structured and unstructured data as well as of open public data, and the data-analytic value chain, all covered at a fundamental level.

More details available at it.monash.edu/data-science.

Early-bird bookings close in a few days.

# The bias-variance decomposition

This week, I am teaching my Business Analytics class about the bias-variance trade-off. For some reason, the proof is not contained in either ESL or ISL, even though it is quite simple. I also discovered that the proof currently provided on Wikipedia makes little sense in places.

So I wrote my own for the class. It is longer than necessary to ensure there are no jumps that might confuse students.

# Resources for the FPP book

The FPP resources page has recently been updated with several new additions including

• R code for all examples in the book. This was already available within each chapter, but the examples have been collected into one file per chapter to save copying and pasting the various code fragments.
• Slides from a course on Predictive Analytics from the University of Sydney.
• Slides from a course on Economic Forecasting from the University of Hawaii.

If any one using the book has other material that could be made available, please send them to me. For example, recorded lectures, slides, additional examples, assignments, exam questions, solutions, etc.

# Forecasting with R in WA

On 23-25 September, I will be running a 3-day workshop in Perth on “Forecasting: principles and practice” mostly based on my book of the same name.

Workshop participants will be assumed to be familiar with basic statistical tools such as multiple regression, but no knowledge of time series or forecasting will be assumed. Some prior experience in R is highly desirable.

Venue: The University Club, University of Western Australia, Nedlands WA.

Day 1:
Forecasting tools, seasonality and trends, exponential smoothing.
Day 2:
State space models, stationarity, transformations, differencing, ARIMA models.
Day 3:
Time series cross-validation, dynamic regression, hierarchical forecasting, nonlinear models.

The course will involve a mixture of lectures and practical sessions using R. Each participant must bring their own laptop with R installed, along with the fpp package and its dependencies.

For costs and enrolment details, go to
http://www.cas.maths.uwa.edu.au/courses/forecasting.

# Highlighting the web

Users of my new online forecasting book have asked about having a facility for personal highlighting of selected sections, as students often do with print books. We have plans to make this a built-in part of the platform, but for now it is possible to do it using a simple browser extension. This approach allows any website to be highlighted, so is even more useful than if we only had the facility on OTexts.org.

There are several possible tools available. One of the simplest tools that allows both highlighting and annotations is Diigo. Continue reading →