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TSM_BusAn

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How to save (and load) datasets in R: An overview
The Trouble with Tibbles

Tibble Data Format in R: Best and Modern Way to Work with Your Data

The Workspace

R for Data Science

Wikipedia

Statistik
Stochastik
Mathematische/induktive Statistik (beurteilende Statistik)
Deskriptive Statistik (beschreibende Statistik)
Grundgesamtheit (Population! Gesamterhebungsumfang)
Schätztheorie
Schätzfunktion
Schätzmethode (Schätzverfahren)

R

PH525x series – Biomedical Data Science
Procedural Languages > R
R – Tilde Operator
DataCamp – Formulas in R Tutorial
R for Dummies – How to Use the Formula Interface in R
The R Formula Method: The Good Parts

Verteilungen

Wahrscheinlichkeitsverteilung
Diskrete Wahrscheinlichkeitsverteilung
Stetige Wahrscheinlichkeitsverteilung
Absolutstetige Wahrscheinlichkeitsverteilung

Liste univariater Wahrscheinlichkeitsverteilungen
Kategorie:Absolutstetige Wahrscheinlichkeitsverteilung
Kategorie:Univariate Wahrscheinlichkeitsverteilung

Diskrete

Poisson-Verteilung
Bernoulli-Verteilung (Null-Eins-Verteilung)
Binomialverteilung

Stetige

Stetige Gleichverteilung
Dreiecksverteilung
Exponentialverteilung
Gammaverteilung

YouTube

StatQuest with Josh Starmer

Video Index
Statistics Fundamentals
Linear Models

StatQuest: Logistic Regression in R

DataCamp

R tutorial – Learn R Programming

Week 2

  • Samplr Size totally obscured
  • Variability not visible
  • Statistical evidence
  • Statistical significance
  • Statistical relevance
  • Statistical inference
  • Confidence Intervals
  • Statistical hypothesis testing, Null-Hypothesis
  • p-Values

Mittelwert
Median
p-Wert

Mean
Median
p-value

Statistischer Test / Statistical hypothesis testing / Hypothesis Testing
Statistische Signifikanz / Statistical significance
Mathematische Statistik / Statistical inference

Wilcoxon-Mann-Whitney-Test (Rank Sum Test)
Kruskal-Wallis-Test, H-Test, (Rank Sum Test)
Hypothese (Statistik)
Null hypothesis
Informal inferential reasoning
MathsNZ Students – 3.10 – Formal Inference

YouTube

p-Wert und p-Wert-Grenzen – was leistet ein p-Wert (nicht)?
p-Wert in der Statistik einfach erklärt | Hypothesen-Test | Beispiel | wirtconomy
p-Wert, Nullhypothese, Signifikanzniveau – die Idee erklärt
Hypothesentest, p-Wert und weshalb man damit vorsichtig sein muss
p-Wert: einseitiger und beidseitiger Hypothesentest / Signifikanztest – erklärt
p-Werte sind Zufallsgrößen; Signifikanzniveau
Statistische Tests und der p-Wert
Hypothesentest, Signifikanztest, Ablehnungsbereich mit TR bestimmen | Mathe by Daniel Jungn, M
Students t-Test, Hypothesentest der t-Verteilung, t-Test, Mathe by Daniel Jung
Writing a formal inference – the conclusion

Mann-Whitney-U-Test – Voraussetzungen, Funktionsweise und Interpretation – Daten analysieren in SPSS
Kruskal-Wallis-Test in SPSS – Funktionsweise und Interpretation – Daten analysieren in SPSS (21)

How To… Perform the Mann-Whitney U Test (By Hand)

Boxplot

Khan Academy – Boxplot – Wiederholung
Wikipedia – Box-Plot
Box plot
Konfidenzintervall, Vertrauensintervall, Vertrauensbereich und Erwartungsbereich
Confidence interval
Boxplot erstellen, Median, unteres/oberes Quartil, Minimum, Maximum | Mathe by Daniel Jung

Week 3

  • categorical perdictor
  • distribution
  • deviation
  • Gauss / not Gauss
  • Residual plots

Regression analysis
Regressionsanalyse
What is Regression Analysis and Why Should I Use It?
Der Klassiker lineare Regression einfach erklärt – Herleitung und Anwendungsbeispiele
Varianzanalyse (ANOVA)

Logarithmische Skalierung
logarithmieren in diagramm

Week 6

Survival Analysis
12. Summarising Time to Event Data
8. Log-Rank Test for Analysing ‘Time to Event’ Data
What is Survival Analysis | Kaplan-Meier Estimation | Time to Event Model
Survival Models: Introduction to Survival Analysis | Data Science
Survival Analysis in R
Kaplan Meier Survival Analysis
Überlebenszeitanalyse mit R, Kaplan-Meier-Kurve, Lograng-Test, Cox-Regression
tranSMART – Schulungsvideo 03 – Überlebenszeitanalyse
Relatives Risiko und Odds Ratio in Beobachtungsstudien – Statistik Teil 7 – AMBOSS Auditor

Week 7

Wikipedia

Customer Lifetime Value (CLV)
Kundenwert
Deckungsbeitrag
Variable Kosten

KUNDENWERT – Was ist eigentlich…?
So berechnest du deinen KUNDENWERT! (CLV)
Fixe Kosten vs. Variable Kosten – einfach erklärt!
Was ist Abzinsen? Erklärt an einem Beispiel Zinsrechnung

Week 8

Youtube search: time series forecasting
Time Series Analysis – 1 | Time Series in Excel | Time Series Forecasting | Data Science|Simplilearn

Beyoncé macht dumm | Korrelation vs. Kausalität
Statistik: Kovarianz und Korrelation: Grundlagen – FernUni Hagen – Wiwi
Streudiagramm und Korrelation
Kausalität
Regression
Bedeutung Korrelationskoeffizient, linearer Zusammenhang | Mathe by Daniel Jung
Korrelation Was ist das?
Korrelation nach Pearson – Voraussetzungen
Bivariate Korrelation in SPSS (Skalenniveau+korrekte Korrelationsmaße) -Daten analysieren in SPSS(8)

Week 9

Forecasting: Moving Averages, MAD, MSE, MAPE
Demand Forecasting (Exponential Smoothing)
Forecasting – Measurement of error (MAD and MAPE) – Example 2
Forecast Accuracy Mean Average Percentage Error (MAPE)

Week 10

Week 11

K – Means Clustering – Fun and Easy Machine Learning
Hierarchical Clustering – Fun and Easy Machine Learning

MESOSworld – Methodological Education for the Social Sciences (Universität Zürich)

Lerninhalte

Grundlagen

Population und Stichprobe
Population und Stichprobe (PDF)

Univariate Verteilungen

Beschreibung univariater Verteilungen
Grafische Darstellung der Ausprägungen eines Merkmals

Bivariate Verteilungen

Regressionsanalyse

Statistik-Nachhilfe

REGRESSIONSANALYSEN (Prädiktor)
EINFAKTORIELLE & MEHRFAKTORIELLE VARIANZANALYSE (ANOVA)
P-WERT, KRITISCHER WERT
NULLHYPOTHESE, ALTERNATIVHYPOTHESE (GEGENHYPOTHESE), GERICHTETE HYPOTHESE, UNGERICHTETE HYPOTHESE
HYPOTHESENTESTS / SIGNIFIKANZTESTS
TESTTHEORIE
ALPHAFEHLER (FEHLER 1. ART), SIGNIFIKANZNIVEAU
ZENTRALER GRENZWERTSATZ
STOCHASTISCHE MASSZAHLEN

Crashkurs Statistik

Grundgesamtheit, Stichprobe, Merkmale
Parameterschätzung

Steve Brunton – Intro to Data Science

Intro to Data Science

  • Intro to Data Science: Overview
  • Intro to Data Science: Historical Context
  • Intro to Data Science: What is Data Science?
  • Intro to Data Science: Answering Questions with Data
  • Intro to Data Science: The Nature of Data
  • Machine Learning Overview
  • Machine Learning Goals
  • Machine Learning and Cross-Validation
  • Types of Machine Learning 1
  • Types of Machine Learning 2
  • Artificial Intelligence
  • Neural Network Overview
  • Neural Network Architectures
  • Neural Networks and Deep Learning
  • Neural Networks: Caveats
  • Digital Twins
  • Data Visualization: Overview
  • Data Visualization: Types of Data
  • Data Visualization: Storytelling with Data
  • Data Visualization: Buyer Beware

Nominal, Ordinal, Cardinal

M101 Numerals and digits; Cardinal, ordinal and nominal numbers
Scales of Measurement – Nominal, Ordinal, Interval, Ratio (Part 1) – Introductory Statistics
Types of Data: Nominal, Ordinal, Interval/Ratio – Statistics Help

TSM_DataMgmt

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An Animated Guide: Knowing SQL Internal Processes makes SQL Easy, makes SQL easy
WHERE-Klausel im Detail

Lecture

Week 3

Postgres Handles More Than You Think
Don’t Do This
B-Baum
AVL-Baum

CTE in SQL

What is the difference between tree depth and height?
Height, Depth and Level of a Tree

Nested set model
Nested Sets
Jede Menge Bäume

Storing hierarchical data: Materialized Path
Trees in SQL: Nested Sets and Materialized Path
Nested Sets and Materialized Path SQL Trees
Trees in SQL : an approach based on materialized paths and normalization for MySQLTrees in SQL : an approach based on materialized paths and normalization for MySQL
Materialized Path in PostgreSQL

Week 4

Install MongoDB Community Edition on Ubuntu

Week 5

“Schema Later” Considered Harmful
Visualization software
Tableau Software
Superset: enterprise-ready web application for data exploration, data visualization and dashboarding
What does Tableau offer that Apache Superset doesn’t?

Week 6

What is the difference between scale-out versus scale-up (architecture, applications, etc.)?

Week 8

Assoziationsanalyse | Video Based Learning
Apriori-Algorithmus | Business Intelligence | Unsupervised Learning
Frequent Pattern (FP) growth Algorithm for Association Rule Mining
Apriori algorithm with complete solved example to find association rules
data mining fp growth | data mining fp growth algorithm | data mining fp tree example | fp growth

Week 9

ID3
C4.5
Decision tree learning
Decision Tree Classification in R

Week 11

K – Means Clustering – Fun and Easy Machine Learning
Hierarchical Clustering – Fun and Easy Machine Learning

Week 13

Minimal Viable Search using Postgres
Unscharfe Suche, Levenshtein-Distanz, N-Grammen, Soundex
PostgreSQL Full Text Search and Trigram Confusion
Victor Lavrenko – Search Engine

MapReduce – Computerphile
PostgreSQL Full Text Search and Trigram Confusion
13.68 MapReduce, Verarbeitung eines MapReduce Jobs auf einem Cluster Victor Lavrenko – Search Engine
Apache Hadoop
MapReduce

Heaps’ law
Zipf’s law

Rest

Step by Step Guide to Dimensional Data Modeling
Introduction to Dimesional Modelling
Business Intelligence: Building Your First Cube
Create First OLAP Cube in SQL Server Analysis Services
Building Your First Data Cube
Dimensional modeling
OLAP-Würfel
OLAP cube

SQL | DDL, DQL, DML, DCL and TCL Commands

Grundbegriffe der Prädikatenlogik
Prolog – Begriffe, (Literal, Klausel, Prädikat)

Wikipedia

Prädikatenlogik
Literale in der mathematischen Logik
Disjunktionsterm
Prädikat (Logik)

Wikipedia

(de)
Relational algebra (en)
Join (SQL) (de)
Join (SQL) (en)
Data Manipulation Language (DML)
Transaction Control Language (TCL)
CRUD
ACID
NoSQL
Dokumentenorientierte Datenbank
Codd’s 12 rules

NULL

NULL in SQL: Platzhalter für fehlende Daten

SQL Functions

Substring function overview

Sakila Databas

MySQL Sakila Sample Database
The Sakila Database
github.com/jOOQ/jOOQ/tree/master/jOOQ-examples/Sakila

JOOQ

A Beginner’s Guide to the True Order of SQL Operations

Datenbankenlernen.de – Prof. Dr. Jens Dittrich

Datenbankenlernen.de
13.XX SQL (Playlist)
13.20 Übersicht über Datenbanksysteme: Welches DBMS für was?
13.21a SQL Standards
13.21b SQL Teilsprachen
13.24 SELECT FROM WHERE
13.44 NULL != NULL
13.46 Unteranfragen mit IN, EXISTS, ALL, ANY
13.48 SQL Datentypen

postgresql

postgresql – can’t create database – OperationalError: source database “template1” is being accessed by other users

PostgreSQL Data Types
PostgreSQL Show Tables
Show tables in PostgreSQL
PostgreSQL Show Databases

Documentation

9.20. Aggregate Functions

SELECT DISTINCT, GROUP BY

SQL – select DISTINCT
Is there any difference between GROUP BY and DISTINCT

NoSQL – Graph Databases

OrientDB

Demo Database

Wikipedia

Multi-model database

YouTube

OrientDB – the 2nd generation of (MultiModel) NoSQL by Luigi Dell’Aquila
Michael Hackstein: Multi-Model NoSQL Databases
Building on Multi-Model Databases

WEKA

Weka 3: Machine Learning Software in Java
Weka Wiki
WEKA API Tutorial: How to use WEKA in JAVA

Windows 10 Boot-Manager (Safe Mode / Abgesicherter Modus)

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HP PCs – Abgesicherter Modus von Windows (Windows 10, 8)

bootrec /fixmbr
bootrec /fixboot
bootrec /scanos
bootrec /rebuildbcd

msconfig
diskpart

bcdedit /set {default} safeboot minimal
bcdedit /set {default} safeboot network
bcdedit /set {default} safeboot minimal.
bcdedit /set {default} safebootalternateshell yes

bcdedit /deletevalue {default} safeboot

Fix: Boorec /Fixboot Element Not Found on Windows
How to Rebuild the BCD in Windows
Anleitung zum Reparieren des EFI-Bootloaders auf einer GPT-Festplattenlaufwerk für Windows 7, 8, 8.1 und 10 auf Ihrem Dell PC
Gelöst: Das angeforderte Systemgerät kann nicht gefunden werden
Windows 10 – Boot-Manager anpassen, entfernen und reparieren

JavaSE 4, …, 9 Features

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javaTpoint Java Tutorial

JavaSE 4, …, 9 Features

Java 9 Features

Interface Private Methods
Try-With Resources
Anonymous Classes
SafeVarargs Annotation
Collection Factory Methods
Process API Improvement
Version-String Scheme
JShell (REPL)
Module System
Control Panel
Stream API Improvement
Underscore Keyword

Java 8 Features

Lambda Expressions
Method References
Functional Interfaces
Stream API
Stream Filter
Base64 Encode Decode
Default Methods
forEach() method
Collectors class
StringJoiner class
Optional class
JavaScript Nashorn
Parallel Array Sort
Type Inference
Parameter Reflection
Type Annotations
JDBC Improvements

Java 7 Features

Binary Literals
Switch with String
Multi Catch
Try with Resources
Type Inference
Numeric Literals
JDBC

Java 4/5 Features

Assertion
For-each Loop
Varargs
Static Import
Autoboxing
Enums
Annotations
Generics

JavaSE 4, …, 8 Features

JavaSE 8 Features

Java 8 Date/Time API (Java 8)
Lambda Expressions (Java 8)
Method References (Java 8)
Functional Interfaces (Java 8)
Stream (Java 8)
Base64 Encode Decode (Java 8)
Default Methods (Java 8)
forEach method(Java 8)
Collectors(Java 8)
StringJoiner(Java 8)
Optional class (Java 8)
Nashorn JavaScript (Java 8)
Parallel Array Sorting (Java 8)
Type Inference (Java 8)
Method Parameter Reflection (Java 8)
Type annotations and repeating annotations (Java 8)
Java JDBC Improvements (Java 8)
Java IO Improvement (Java 8)
Java Concurrency Improvement (Java 8)

JavaSE 7 Features

String in switch statement (Java 7)
Binary Literals (Java 7)
The try-with-resources (Java 7)
Caching Multiple Exceptions by single catch (Java 7)
Underscores in Numeric Literals (Java 7)

JavaSE 6 Features

Instrumentation (premain method) (Java 6)

J2SE 5 Features

For-each loop (Java 5)
Varargs (Java 5)
Static Import (Java 5)
Autoboxing and Unboxing (Java 5)
Enum (Java 5)
Covariant Return Type (Java 5)
Annotation (Java 5)
Generics (Java 5)

J2SE 4 Features

Assertion (Java 4)