Statistics for Data Analysis in Python Training in Sweden

  • Learn via: Classroom
  • Duration: 2 Days
  • Level: Fundamentals
  • Price: From €2,078+VAT
We can host this training at your preferred location. Contact us!

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 Python or R – if this is not currently the case we suggest completing one of our Python or R for 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 Python or R that you will need as part of this journey.

If you wish to expand your understanding of Maths and Statistics related to Data Science then this course will give you all the required pre-requisite statistical knowledge needed for our more in depth programmes.

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

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

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
  • Discuss when the above measures are appropriate
  • Apply methods for automating identification of outliers
  • Discuss appropriate handling of outliers
  • Practical Lab Activities with Python

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 two samples (e.g.taken at different times or fromdifferent locations)
    • Determine the appropriate shape of a model and whetherthere are opportunities to linearise
  • Practical Lab Activities with Python

Introduction to Probability

  • Interpret P() notation and calculate simple and conditionalprobabilities
  • Use Venn diagrams with set notation to calculate probabilities
  • Use Tree diagrams and simple combinatorics to calculateprobabilities
  • Practical Lab Activities with Python

Introduction to Distributions

  • Recognise what a probability or data distribution is
  • Identify when a distributionis considered to beBinomial, Poisson,or Normal
  • Identify when a distribution can be treated as Normal and whatthis means for analytical methods
  • Practical Lab Activities with Python

Sampling

  • Critique different sampling techniques
  • Explain the impact a sampling or data gathering method mayhave on analytical model results
  • Recognise methods for estimating summary statistics for apopulation from a sample
  • Practical Lab Activities with Python

Introduction to Hypothesis Testing

  • Recognise the steps required for a Hypothesis test from thesetup, 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 Python

Linear Regression

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


Contact us for more detail about our trainings and for all other enquiries!

Upcoming Trainings

Join our public courses in our Sweden facilities. Private class trainings will be organized at the location of your preference, according to your schedule.

Classroom / Virtual Classroom
23 suoidnemánnu 2024
Stockholm, Malmö, Göteborg
2 Days
Classroom / Virtual Classroom
01 borgemánnu 2024
Stockholm, Malmö, Göteborg
2 Days
Classroom / Virtual Classroom
08 borgemánnu 2024
Stockholm, Malmö, Göteborg
2 Days
Classroom / Virtual Classroom
10 borgemánnu 2024
Stockholm, Malmö, Göteborg
2 Days
Classroom / Virtual Classroom
11 čakčamánnu 2024
Stockholm, Malmö, Göteborg
€2,078 +VAT Book Now
Classroom / Virtual Classroom
20 čakčamánnu 2024
Stockholm, Malmö, Göteborg
2 Days
Classroom / Virtual Classroom
24 čakčamánnu 2024
Stockholm, Malmö, Göteborg
2 Days
Classroom / Virtual Classroom
25 čakčamánnu 2024
Stockholm, Malmö, Göteborg
2 Days
Statistics for Data Analysis in Python Training Course in Sweden

Sweden is a Nordic country that borders Norway, Finland and Denmark. The name "Sweden" originated from the "Svear", a people mentioned by the Roman author Tacitus. While being the largest Nordic country, Sweden is the fifth-largest country in Europe. Sweden has a total population of 10.4 million. The capital and largest city is Stockholm. About 15 percent of the country lies within the Arctic Circle, so that's why from May until mid-July, sunlight lasts all day in the north of the Arctic Circle. On the other hand, during December, the capital citt experiences only about 5.5 hours of daylight.

When in Sweden, visiting Stockholm's Old Town Gamla Stan, Sweden's most popular museum Vasa Museum and a UNESCO World Heritage Site; Drottningholm Palace is highly recommended.

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