# Statistics & Multivariate analysis with XLSTAT, Virtual class: Online, March 8-12 2021

Subscribe to this online statistics training course illustrated with XLSTAT Basic+. Attend this course directly over the internet and on any device without having to travel. You will learn the basics of descriptive statistics, multivariate data analysis (PCA, CA, AHC), statistical modeling (ANOVA, regression), statistical tests (parametric and nonparametric) as well as machine learning techniques. All of those essential features will be illustrated using the XLSTAT Basic+ solution.

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#### Statistics & Multivariate Analysis with XLSTAT Basic+, training over 5 half days

This training goes through most commonly used data analysis methods in a wide variety of fields including research, biostatistics, marketing, sensometrics, finance and industry. The course proposes conceptual and intuitive approaches to descriptive statistics, multivariate data analysis, tests, modeling as well as machine learning. Methods are illustrated with many examples and implementations in XLSTAT Basic+, including a thorough interpretation of results. Participants are also given time to practice on real data provided by the trainer. At the end of the training, participants are able to quickly find and implement appropriate statistical methods to answer their own data-related questions, using XLSTAT Basic+.

## Dates (training over 5 half days):

• Monday 6/21/21 - 2:00PM - 6:00PM EST
• Tuesday 6/22/21 - 2:00PM - 6:00PM EST
• Wednesday 6/23/21 - 2:00PM - 6:00PM EST
• Thursday 6/24/21 - 2:00PM - 6:00PM EST
• Friday 6/25/21 - 2:00PM - 6:00PM EST

## Pre-requisites

Basic experience in using Microsoft Excel

## Program

### Introduction

• A couple of definitions: individuals, variables, sample, population

### Describing data:

• Quantitative variables: mean, standard deviation, variance, median, quartiles, Histograms, box plots, scatter plots
• Qualitative variables: frequencies, mode, bar chart, cross tab

### Exploring large data sets:

• Reducing dimensionality: principal component analysis, correspondence analysis
• Segmenting data: agglomerative hierarchical clustering, k-means

### Hypothesis testing

• Defining the null hypothesis, the p-value and error risks
• Parametric tests assumptions
• Parametric tests vs nonparametric tests
• One-tailed tests vs two-tailed tests

### Modeling data

• Linear regression
• One-way ANOVA and multiple comparisons
• Multi-way ANOVA and interaction effects
• ANCOVA

### Machine learning

• Supervised vs unsupervised learning
• Introduction to some supervised machine learning techniques

### Deploying R procedures in Excel

• Overviewing the XLSTAT-R code infrastructure

Entreprise/Privé

1 300,00 €
Par personne

Début :

Fin :

Anglais

#### Jean-Paul Maalouf

Jean-Paul Maalouf est un consultant sénior en statistique ayant rejoint l’équipe d’Addinsoft en 2014. Il détient un doctorat en biologie et une expérience importante de l’enseignement des statistiques, activité qu’il a pratiquée de manière intensive depuis 2012. Il a dispensé des formations auprès des plus grandes institutions de recherche françaises (INRA, CNRS, INSERM, CIRAD, plusieurs universités), ainsi qu’auprès de sociétés privées à travers le monde. Ses méthodes d’enseignement reposent sur une approche conceptuelle et très centrée sur l’exemple plutôt que sur l’explication de formules mathématiques complexes. Les notions sont ainsi saisies aisément par les personnes n’ayant pas nécessairement d’expérience en mathématique mais souhaitant devenir rapidement opérationnels dans le domaine de l’analyse de données.

Logiciel de statistique complet pour Microsoft Excel