# Basic Statistics

This course will introduce to the main concepts and tools of Statistics, providing a full overview of data driven mindset and overall the ability to practically work on data with the principal instruments offered by Statistics. It is the starting point you cannot miss to develop your expertise with analytics. Statistics is the basis of machine learning and Data Science as well, so this training course is definitely a must have in this data driven era we live in.

### Topics include

DAY 1:

• Introduction to Statistics
• Why you need Statistics
• Statistics and Data Science
• The main chapters of applied Statistics
• Collecting data
• Preparing data for analysis
• Main errors and problems in data preparation
• Descriptive Statistics
• Location and variation
• Mean, median, IQR, percentiles, standard deviation, range
• Main data visualisations: box plots, histograms, scatterplots, bar charts
• Choosing the proper graph
• Inferential Statistics
• 1 sample and 2 sample t-test
• Normal distribution and its importance
• Normality test
• Confidence interval
• P-value and significance level
• Guidelines and best practices

DAY 2:

• Introduction to statistical modelling
• Why you need a data model
• Representing a process
• How to rationalise complex processes
• The data scientist mindset
• Analysis of Variance
• General linear models
• Introduction to interaction between variables
• The fundamental importance of interactions
• How to model and study interactions
• Correlation and statistical relation between variables
• Simple regression
• Multiple regression
• How to validate a model
• Interpreting a model
• Using a model for prediction
• The concept of optimisation
• Using a model for optimisation

### What you will be able to do

• Prepare data for analysis
• Explore data with descriptive Statistics
• Find relevant variables with ANOVA
• Make predictions and simple optimisations

1 or 2 days.

None.

### Audience

This course is a fundamental for every business area. Different example data can be used according to industry type, for a better understanding and faster use of the concepts.