Fundamentals of Statistics For Data Analysis

Whether you work with Excel, R, Python or any other data solution, you will need to understand statistics to get your data analysis off the ground. The course is taught using R for programming illustration with a focus on statistic that applies across domains.

Aimed at fledging data practitioners who wish to have a practical understanding of statistical methods.

GCSE mathematics or above An interest in mathematical and logical thinking No prior experience of R is assumed, although prior experience will be an advantage

Introduction to R RStudio Data Structures Flow and Functional Programming Introduction to Data Exploring Data Summarizing Data Probability Bayes Rule and Conditional Probability Random Variables Statistical Distributions Bernoulli Normal Binomial Poisson Inferential Statistics Point Estimates Hypothesis Testing Confidence Levels Inference for Numerical Data T-tests ANOVA Inference for Categorical Data Proportions Chi-Square Machine Learning as Statistical Inference Regression Classification

At the end of this course attendees will be able to: create visualizations such as histograms and scatter plots to visually show data; apply basic descriptive statistics to past data to gain greater insights; combine descriptive and inferential statistics to analyze and forecast data; utilize a regression analysis to spot trends in data and build a robust forecasting model.

Participation requirements

Koolitushind sisaldab: koolitust; õppematerjale. Lisaks pakume: sooje jooke koos küpsistega; lõunasööki igal koolituspäeval.