04:15:27

Statistics - A Full Lecture to learn Data Science

12:42

Levels of Measurement - Nominal, Ordinal, Interval and Ratio

14:13

Repeated Measures ANOVA (Analysis of Variance) - Simply explained

14:08

z-Score, z-Standardization, Standard Normal Distribution, z-Distribution Table - Simply explained

07:22

What is the difference between parametric and nonparametric hypothesis testing?

09:58

What is Descriptive Statistics? A Beginner's Guide to Descriptive Statistics!

08:07

What is a hypothesis test? A beginner's guide to hypothesis testing!

20:21

What is Statistics? A Beginner's Guide to Statistics (Data Analytics)!

12:54

Fractional Factorial Design (DoE) Simply explained

08:27

Between-Subject Design vs. Within-Subject Design

11:32

Mixed Model ANOVA (Analysis of Variance) Simply explained

14:23

Full Factorial Design (DoE - Design of Experiments) Simply explained

25:53

Design of Experiments (DoE) simply explained

08:14

Simple linear Regression, Multiple linear Regression and Logistic Regression - Regression Analysis

07:45

What is inferential statistics? Explained in 6 simple Steps.

08:06

Two-Way ANOVA - all Equations - calculated by Hand

03:10

Standard Deviation, Variance, Range and Interquartile Range - Measures of dispersion

03:25

Mean, Median and Mode - Measures of Central Tendency

11:10

Descriptive Statistics [Simply explained]

08:01

How to calculate a Chi-Square Test?

03:19

What is a Raincloud Plot? [Simply explained]

03:45

Violin Plot [Simply explained]

05:35

Bland-Altman Plot [Simply explained]

01:07

What are the assumptions of a Two-Way ANOVA?

01:20

What are the hypotheses of the t-test (Null & alternative hypothesis)?

16:21

Two-Way ANOVA - Full Course

05:37

How to report an Paired Samples t-Test?

05:18

How to report an Independent Samples t-Test?

04:49

How to report a Wilcoxon signed rank test?

03:29

How to report a Mann-Whitney U Test?

27:00

Correlation Analysis - Full Course

07:17

One sample t-test vs Independent t-test vs Paired t-test

16:14

t-Test - Full Course - Everything you need to know

04:08

Levene's test [Test for variance equality]

04:01

Causality (and the difference to correlation) simply explained

06:32

Kendall's Tau [Easily explained]

05:50

Standard Deviation and Variance

06:30

Point-biserial Correlation [Simply explained]

05:41

Spearman Rank Correlation [Simply explained]

07:17

ROC Curve and AUC Value

07:50

Pearson correlation [Simply explained]

08:20

Mann-Whitney U Test [Simply explained]

08:22

Hierarchical Cluster Analysis [Simply explained]

14:22

Logistic Regression [Simply explained]

10:11

Chi2 test - easily explained with an example

08:11

p-value - easily explained with an example

06:36

Hypothesis [Research Hypothesis simply explained]

09:29

Literature research [Systematic Literature Research - State of Research - Research Hypotheses]

09:24

Research Topic, Research Problem & Central Research Question [How to find and formulate]

07:49

Quantitative Research

09:46

Empirical Research - Qualitative vs. Quantitative

02:52

Online Statistics Calculator - Get Started - DATAtab

11:56

Weighted Cohen's Kappa (Inter-Rater-Reliability)

03:48

One Factor vs. Two Factor ANOVA [One Way vs Two Way]

09:57

Two factor ANOVA with repeated measures

24:53

Two Factor ANOVA [without repeated measures]

06:01

Cox Regression [Cox Proportional Hazards Survival Regression]

12:11

Log-Rank Test [Simply Explained]

10:05

Kaplan-Meier-Curve [Simply Explained]

12:58

Survival Analysis [Simply Explained]