This two-day course is designed for those who analyse data or who are creating machine learning models, but who wish to firm their understanding in core concepts as well as expanding into types of data distributions, inferential statistics (hypothesis tests), statistical significance, and a deeper understanding of how linear regression works. It is expected that you will have experience with a programming language used for data analysis such as R or Python – if this is not currently the case we suggest completing one of our R or Pythonfor Data Handling courses.

As well as providing a business context to using core concepts such as averages, spread, and interpreting analyst visualisations, you will take this knowledge further and learn how distributions, sampling, and hypothesis testing can be used to analyse data in an organisation and in automatically highlighting significant results or anomalies.

If you are on a learning journey with Machine Learning and AI this course will give you a strong starting point in the statistical methods that underpin a large number of algorithms without overloading, you with too many mathematical formulae or notations that are otherwise commonly used to communicate advanced mathematics. Your focus will be on business problems and applying tools such as R that you will need as part of this journey.

Throughout the course you will engage with practical labs, activities, and discussions with one of our technical specialists. All modules involve the use of R to practice the techniques taught – setting you up to succeed in analysing, interpreting, and getting value from your data.

Prerequisites

Minimum of GCSE Maths or equivalent
Experience with Python or R for Data Handling

Target Audience

Anyone wishing to expand their understanding of Maths and Statistics related to Data Science. This course will provide all the required pre-requisite statistical knowledge needed for our more in-depth programmes.

For corporate groups, we can organize this training as an on-site private group.

Training Outline

Central Tendency, Variation, and Outliers - Using an appropriate software tool, calculate:

Mean, Mode, Median, Mid-range
Population and Sample Standard Deviation & Variance
Inter-Quartile Range
Apply methods for automating identification of outliers
Discuss appropriate handling of outliers
Practical Lab Activities with R

Visualisations and Skew - Using an appropriate software tool, create:

Histograms
Scatter Plots
Use these to:
- Identify skew and the effect this may have on modelling
- Identify the location of the averages
- Compare twsamples (e.g. taken at different times or from different locations)
- Determine the appropriate shape of a model and whether there are opportunities t linearise
Practical Lab Activities with R

Introduction to Probability

Interpret P() notation and calculate simple and conditional probabilities
Use Venn diagrams with set notation tcalculate probabilities
Use Tree diagrams and simple combinatorics tcalculate probabilities
Practical Lab Activities with R

Introduction to Distributions

Recognise what a probability or data distribution is
Identify when a distribution is considered tbe Binomial, Poisson, or Normal
Identify when a distribution can be treated as Normal and what this means for analytical methods
Practical Lab Activities with R Sampling
Critique different sampling techniques
Explain the impact a sampling or data gathering method may have on analytical model results
Recognise methods for estimating summary statistics for a population from a sample
Practical Lab Activities with R

Introduction to Hypothesis Testing

Recognise the steps required for a Hypothesis test from the set- up, assumptions, testing, and interpretation of p-values
Identify a variety of tests and when they are used
Evaluate the output of tests from an appropriate software tool
Practical Lab Activities with R

Linear Regression

Recognise when a linear regression is an appropriate method tuse
Interpreting y = mx + c
Evaluate linear models
Practical Lab Activities with R

Why Choose Us

Leading UK-based global training provider since 1995.

Experience Statistics for Data Analysis in R in Germany through Bilginç IT Academy's live and interactive virtual classroom environment. Join a Public course as an individual delegate or arrange a dedicated Private / In-house online training program exclusively for your organization.

Delivery Method: Online Instructor-Led
Participation Model: Public / Private (In-house)
Live and Interactive Training: Connect with your instructor in real time and actively participate through discussions, Q&A sessions, practical exercises, and group activities.
Flexible Participation: Join the training from your home, office, or any location with a suitable internet connection.
Expert Trainer Network: Learn from experienced trainers with strong industry backgrounds and practical field expertise.
Over 30 Years of Training Expertise: Benefit from Bilginç IT Academy's professional training experience since 1995.
Worldwide Access: Join our live virtual classrooms from Germany or anywhere else in the world, or arrange a dedicated online training program for your organization.

Experience Statistics for Data Analysis in R through face-to-face Classroom Based training in Germany. Training can be delivered as a Public course open to individual delegates or as a dedicated Private / In-house class for your organization.

Delivery Method: Classroom Based
Participation Model: Public / Private (In-house)
Face-to-Face Learning: Interact directly with your instructor and fellow delegates in an engaging classroom environment.
Experienced Trainers: Learn from specialists with extensive industry experience and practical real-world knowledge.
Professional Training Environment: Attend training in comfortable, well-equipped classrooms designed to support effective learning.
Practical Learning: Depending on the course, reinforce your knowledge through hands-on exercises, scenarios, case studies, and instructor-led activities.

Arrange Statistics for Data Analysis in R in Germany as a dedicated Onsite training program for your organization. Bilginç IT Academy trainers can deliver the training at your office or another location of your choice, with the program planned around your team's requirements and business objectives.

Delivery Method: Onsite
Participation Model: Private (In-house)
Training at Your Preferred Location: Organize the training at your company's office or another location selected by your organization.
Tailored Course Content: Adapt the training program to your projects, team structure, existing skill levels, and specific business requirements.
Team-Focused Learning: Develop your team around a shared knowledge base while strengthening internal collaboration and knowledge transfer.
Flexible Scheduling: Plan the training dates, location, and program according to your organization's operational requirements.
Worldwide Onsite Delivery: Arrange the training in Germany or at another preferred location worldwide. Bilginç IT Academy trainers can travel to your selected location to deliver the dedicated training program.

Statistics for Data Analysis in R Training in Germany

Prerequisites

Target Audience

Training Outline

Why Choose Us

Statistics for Data Analysis in R Training Course in Germany Schedule

Statistics for Data Analysis in R Training in Germany

Prerequisites

Target Audience

Training Outline

Why Choose Us

Online Instructor-Led Training

Classroom Based Training

Onsite Training

Statistics for Data Analysis in R Training Course in Germany Schedule