R for Statistical Analysis Training Course

This instructor-led, live training in New Zealand (online or on-site) is designed for intermediate-level advanced R users who wish to leverage R to build faster workflows, enhance code quality, and tackle more complex analytical tasks.

By the end of this training, participants will be able to: create reusable functions, improve data workflows, debug and optimise code, and produce reproducible reports.

This instructor-led, live training in New Zealand (online or onsite) is aimed at business analysts who wish to automate trading using algorithmic strategies, Python, and R.

By the end of this training, participants will be able to:

• Use algorithms to buy and sell securities rapidly in specialised increments.
• Reduce trading-related costs through the application of algorithmic trading.
• Automatically monitor stock prices and execute trades.

Big Data is a term referring to solutions designed for storing and processing large-scale datasets. Initially developed by Google, these Big Data solutions have evolved and inspired numerous similar projects, many of which are available as open-source. R is a widely used programming language within the financial industry.

This instructor-led, live training in New Zealand (delivered online or on-site) is designed for beginner-level data analysts who wish to use R to manipulate data, perform foundational data analysis, and create compelling visualisations to derive insights.

By the end of this training, participants will be able to:

• Understand the fundamentals of R programming.
• Apply core data science processes.
• Create visual representations of data.

R is an open-source, free programming language designed for statistical computing, data analysis, and graphics. It is increasingly adopted by managers and data analysts across corporations and academia. R has also gained traction among statisticians, engineers, and scientists who may lack formal programming skills but find the language intuitive to use. Its growing popularity stems from the expanding use of data mining for diverse objectives, such as setting advertising prices, accelerating drug discovery, or refining financial models. R offers a wide range of packages tailored for data mining tasks.

This instructor-led, live training in New Zealand (available online or on-site) is designed for data analysts who wish to programme with R in SAS for cluster analysis.

By the end of this training, participants will be able to:

• Apply cluster analysis for data mining purposes.
• Master R syntax for developing clustering solutions.
• Implement both hierarchical and non-hierarchical clustering techniques.
• Make data-driven decisions to help improve business operations.

Data analytics is a vital tool in today's business landscape. Throughout this course, we focus on building practical, hands-on skills for data analysis. The goal is to empower participants to provide evidence-based answers to key questions: 

What has happened?

• processing and analysing data
• creating insightful data visualisations

What will happen?

• forecasting future performance
• evaluating forecasts

What should happen?

• turning data into evidence-based business decisions
• optimising processes

This instructor-led, live training in New Zealand (online or on-site) is designed for beginner-level professionals who wish to clean and analyse data, make statistical projections, and create insightful visualisations using these tools.

By the end of this training, participants will be able to:

• Understand the basics of Python, R, Power Query, and Power BI for data analysis.
• Clean and organise datasets using Python and Power Query.
• Perform statistical analysis and projections with R.
• Create professional dashboards and reports with Power BI.
• Integrate and analyse data from multiple sources effectively.

R is a widely used, open-source environment for statistical computing, data analytics, and graphics. This course introduces students to the R programming language, covering language fundamentals, libraries, and advanced concepts. Participants will explore advanced data analytics and visualisation using real-world datasets.

Audience

Developers and data analytics professionals

Duration

3 days

Format

Lectures and hands-on sessions

This instructor-led, live training in New Zealand (online or on-site) is designed for anyone wishing to learn and master the fundamentals of econometric analysis and modelling.

By the end of this training, participants will be able to:

• Learn and understand the fundamentals of econometrics.
• Use Eviews and Risk Simulator.

This instructor-led, live training in New Zealand (online or onsite) is aimed at intermediate-level data analysts and business professionals who wish to perform time series forecasting and automate data analysis workflows using R.

By the end of this training, participants will be able to:

• Understand the fundamentals of forecasting techniques in R.
• Apply exponential smoothing and ARIMA models for time series analysis.
• Utilise the 'forecast' package to generate accurate forecasting models.
• Automate forecasting workflows for business and research applications.

This instructor-led, live training (available online or on-site) is designed for HR professionals who wish to leverage analytical methods to enhance organisational performance. The course explores both qualitative and quantitative approaches, including empirical and statistical techniques.

Course Format

• Interactive lectures and group discussions.
• Abundant exercises and hands-on practice.

Course Customisation Options

• To request a customised training session for this course, please contact us to arrange.

Audience

This course has been developed for analysts and forecasters seeking to introduce or enhance forecasting capabilities in areas such as sales forecasting, economic forecasting, technology forecasting, supply chain management, and demand or supply planning.

Description

This course guides participants through a range of methodologies, frameworks, and algorithms that are valuable when selecting approaches to predict future outcomes based on historical data.

It utilises standard tools such as Microsoft Excel or certain open-source programs (notably the R Project).

The principles covered in this course can be implemented using any software (for example, SAS, SPSS, Statistica, MINITAB, etc.).

This instructor-led, live training in New Zealand (online or on-site) is aimed at beginner-level to intermediate-level professionals who wish to perform statistical analysis using SPSS to interpret data accurately, run complex statistical tests, and generate meaningful insights.

By the end of this training, participants will be able to:

• Navigate the SPSS interface and manage datasets efficiently.
• Perform descriptive and inferential statistical analyses.
• Conduct t-tests, ANOVA, MANOVA, regression, and correlation analyses.
• Apply non-parametric tests, principal component analysis, and factor analysis for advanced data interpretation.

Audience

Course Format

By the end of this training, participants will be able to:

In this instructor-led, live training, participants will learn how to manipulate and visualise data using the tools included in the Tidyverse.

The Tidyverse is a collection of versatile R packages for cleaning, processing, modelling, and visualising data. Some of the packages included are: ggplot2, dplyr, tidyr, readr, purrr, and tibble.

• Beginners to the R language
• Beginners to data analysis and data visualisation

• Part lecture, part discussion, exercises and heavy hands-on practice

• Perform data analysis and create appealing visualisations
• Draw useful conclusions from various datasets of sample data
• Filter, sort and summarise data to answer exploratory questions
• Turn processed data into informative line plots, bar plots, histograms
• Import and filter data from diverse data sources, including Excel, CSV, and SPSS files