Statcon. Statistik: Consulting · Training · Software

This course is focussed on the basic statistical concepts and measures. First we Introduce the idea of statistical thinking before we procede to descriptive statistics. Dazu gehören Lagemaße, Streuungsmaße, Formmaße, Verteilungen und typische grafische Darstellungsformen der explorativen Datenanalyse, wie z.B. Histogramme und Box-Plots. Anschließend beginnen wir mit Themen der schließenden Statistik. Ausgehend vom fundamentalen Konzept des Hypothesentests behandeln wir Mittelwertvergleiche, Korrelationsanalysen und lineare Regressionsmodelle. Wir passen diesen Kurs in Länge und Schwerpunkt Ihren Vorkenntnissen und Bedürfnissen an.

Objectives:

• control the key data mean, standard deviation, median, ....
• understand bar charts and boxplots
• you are able to adopt t-tests, interpret them and check the prerequisites
• understand and adopt analysises of correlation
• adopt simple linear regression

Prerequisites:

Basic knowledge of statistics helps, but is not required. If necessary they will be covered in the course.

Interested in this course ? Please contact us !		phone: +49 (0)5542 - 93300 email: vertrieb@statcon.de			contact form

COURSE SET-UP
The set-up is similar to the regular Applied Statistics course but reduced to two days. This is accomplished mainly by de-emphasizing the theory. Only continuous variables will be treated, some more advanced topics of ANOVA and regression are skipped.

DISCUSSING OWN APPLICATIONS
Each participant is offered free individual follow-up coaching; an individual session of two hours with one of the trainers, in CQ’s offices. So each participant can appeal to the trainer’s expertise, after having applied the methods treated in the course to his / her own cases. Appointments for the individual sessions can be made during the course.

COURSE OBJECTIVE
As a result of this course, participants will develop a certain feel for statistics and will be able to choose an appropriate technique and interpret the results correctly for the most common types of problems.

INTENDED AUDIENCE AND PRIOR KNOWLEDGE
This course is intended for anyone who wants to retrieve the information from statistical numbers and graphs so easily produced by software. Although the mathematical level and amount of detail are considerably lower as compared to the regular course, the same topics are covered in a shorter time span. So although labeled “light”, it may still be “spicy”. After all, it’s still statistics!
No prior knowledge is required.

COURSE CONTENTS

Module 1

• Descriptive statistics
  • Graphical techniques: scatter plot, histogram, dotplot, boxplot, normal probability plot
  • Descriptive statistics: means, median, variance, IQR, ...
  • Describing the similarity between variables: covariance & correlation
  • Autocorrelation
• Good data collection practice
  • Representative sampling
  • Paired comparisons

Module 2

• Dealing with random variables (probability distributions)
  • Properties of distributions of random variables
  • The normal distribution and its derivatives ( the z, ?2, t and F-distribution). Transformations.

Modul 3

• Confidence intervals
• Hypothesis testing
  • Hypothesis testing with confidence intervals
  • Classical hypothesis testing
  • Statistical significant versus practical relevant
  • Type I and Type II errors
  • Power and sample size calculations

Module 4

• One-way ANOVA
• Simple Linear Regression

ome cases &applications:

• detecting and proving a change in a process
• quantifying and judging the difference between two products or systems
• calculating the number of data needed to detect a certain improvement
• investigating the effect of different types of a constituent on the product properties
• investigating the effect of a process parameter on a characteristic

PRACTICAL

Each course day will be held from 9 am to about 5.30 pm. The course fee includes handouts, lunches and the individual follow-up coaching.

 

Type of training	date	location	price	duration	languages
Open		Zurich	800,- net	2 days	english
Interested in this course ? Please contact us !		phone: +49 (0)5542 - 93300 Email: vertrieb@statcon.de			contact form

WHY MULTIVARIATE DATA ANALYSIS
The massive amounts of (non-designed) collected data, often stored without further analysis, might contain valuable information about wanted and unwanted variation in process factors and product properties. A multivariate approach might reveal the cause of the unwanted variation or phenomena, without any additional experiments or measurements. Taking into account all available information will lead to insights in the often complex interplay of many factors.

COURSE SET-UP
During day 1 qualitative aspects of multivariate data analysis will be treated: exploring the data, searching for correlations, clusters, outliers, ...
In day 2 we come to the model building part: searching for relations between groups of variables. Emphasis will be put on correctly applying and interpreting the different techniques, and not on underlying theory. The course matter can immediately be applied with real-life exercises on PC.

DISCUSSING OWN APPLICATIONS
Each participant is offered free individual follow-up coaching; an individual session of two hours with one of the trainers, in CQ’s offices. So each participant can appeal to the trainer’s expertise, after having applied the methods treated in the course to his / her own cases. Appointments for the individual sessions can be made during the course.

COURSE OBJECTIVE
Multivariate analysis comprises a broad gamma of techniques, but at the same time contains an equally broad gamma of pitfalls. Breaking down the barriers towards multivariate analysis and smoothing the path towards expertise building while at the same time making the participants aware of the problems that arise, are considered to be the main objectives of this course.
At the end of the course participants will be able to select the proper technique to solve a number of problems, analyse the data and correctly interpret the results.

INTENDED AUDIENCE AND PRIOR KNOWLEDGE
This course will be of great help to anyone who is frequently faced with large data tables and who is not familiar with multivariate techniques, who can not make the appropriate choice, or who does not feel confident when trying to interpret the results of these methods.
Prior knowledge is not required.

COURSE CONTENTS

Day 1: Exploratory multivariate analysis

• Visualisation of big datasets
• Principal Component Analysis (PCA)
• Cluster analysis: searching for groups of similar samples

Day 2: Quantitative analysis: in search of cause-effect relations

• Multiple Linear Regression (MLR) with uncorrelated variables
• Multiple Linear Regression (MLR) with correlated variables
  • Stepwise regression
  • The collinearity problem
  • An overview of the pitfalls
• Principal Component Regression (PCR)
• Partial Least Squares (PLS)
  • Interpretation of PCR and PLS models
  • Validation of regression models
  • Detection of outliers and non-linearities
  • Prediction with regression models
• Some alternatives

Day 3: Quantitative analysis: the sequel + specific applications

• Feasibility study: does a quantitative analysis make sense?
• Classification (supervised pattern recognition): predicting class membership
  • Classification rules
  • Linear Discriminant Analysis (LDA)
  • Soft Independent Modeling of Class Analogy (SIMCA)
  • PLS-DA
• Specific applications:
  • QSAR / QSPR (Quantitative Structure Activity / Property Relations)
  • Multivariate SPC (M-SPC)
  • Principal Properties Design
• ......

PRACTICAL

Each course day will be held from 9 am to about 5 pm. The course fee includes handouts, lunches and the individual follow-up coaching.

 

Type of training	date	location	price	duration	languages
Open		Zurich	1200,- net	3 days	english
Interested in this course ? Please contact us !		phone: +49 (0)5542 - 93300 Email: vertrieb@statcon.de			contact form