Data Analytics Foundation

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Durationn: 2 Days
Provider: Trigraph
Course Fees: Full Course Fee: €1395

Network Members Fee: €840

Course Objectives/ Learning Outcomes

At the end of the course participants will know what the data analytics methodology is.
At the end of the course participants will have a fundamental understanding of how to use the various tools listed below. Even though we will practice as much as possible, it is advised that the participants keep practicing. The knowledge acquired will provide an understanding of how Data Analysis can be integrated into the company’s reporting and decision structure.

Who Should Attend

This course is recommended for all those in an organisation who want to get a good understanding of Data Analysis, the methodology, the main tools and tests and when to use them and when not. In addition we will spend some time looking at various common errors you must be aware to avoid wrong results.

Course Content

Day 1

Data Analysis Methodology – CRISP-DM (Cross-Industry Standard
Process for Data Mining)
Page 8 of 47
Business Understanding
Data understanding
Data Preparation
Modeling
Evaluation
Deployment
Introduction to Minitab and Excel (History in Minitab & Change settings
in Excel)

Distributions
Types of data: Continuous, Attribute (Ordinal, Discrete and categorical)
Normal Distribution
Binomial distribution
Poisson distribution

Day 2

Hypothesis testing – Part I

When you want to compare averages or medians of some sample of
data to decide if they are statistically different.

When you want to compare the standard deviation of some sample of
data to decide if their variation is statistically different.

When you want to compare proportions or percentages that came
from different samples of data to decide if they are statistically
different.

Principles of Hypothesis testing: What is it and why and when do we
use hypothesis testing
1 Sample T-Test: for comparing the averages of one sample against a
specific target or historical average
2 Sample T-Test: for comparing the averages of two samples against
each other.
One way ANOVA: for comparing the averages of 3 or more samples
against each other
Pared T-Test: for comparing the averages of two samples that contain
data that is linked in pairs.
Exploratory data analysis via graphical tools

Time series
Scatter
Pareto
Box and Whiskers
Advanced Section – Continued for another 2 days

Trainer Profile

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