Uploaded March 2022 | Updated September 2026, 8 hours ago
Analysis of variance with repeated measurement tests whether there are statistically significant differences in three or more dependent samples. The one-factor analysis of variance with repeated measures is the extension of the t-test for dependent samples for more than two groups.
In the t-test for dependent samples, we examined whether there is a difference between two dependent groups. If we want to test whether there is a difference between more than two dependent groups, we use the analysis of variance with repeated measures.
Analysis of variance with repeated measurement:
numiqo.com/tutorial/anova-with-repeated-measures
ANOVA Calculator:
numiqo.com/statistics-calculator/hypothesis-test/anova
Analysis of variance with repeated measurement tests whether there are statistically significant differences in three or more dependent samples. The one-factor analysis of variance with repeated measures is the extension of the t-test for dependent samples for more than two groups.
In the t-test for dependent samples, we examined whether there is a difference between two dependent groups. If we want to test whether there is a difference between more than two dependent groups, we use the analysis of variance with repeated measures.
Analysis of variance with repeated measurement:
numiqo.com/tutorial/anova-with-repeated-measures
ANOVA Calculator:
numiqo.com/statistics-calculator/hypothesis-test/anova
![Linear Regression vs. Logistic Regression [in 60 sec.] #shorts
What is the difference between linear and logistic regression? Both methods are very important in the field of machine learning. In a linear regression, the dependent variable is a metric variable, e.g. salary or electricity consumption. In a logistic regression, the dependent variable is a dichotomous variable.
#statistics #regression #research Linear Regression vs. Logistic Regression [in 60 sec.] #shorts](https://i.ytimg.com/vi/FLmfPbP0Bac/mqdefault.jpg)

![Log-Rank Test [Simply Explained]
In this video I explain the Log Rank Test. We will go through what the Log Rank Test is and how it is calculated. What is the Log Rank Test? The log rank test is used in survival time analysis and compares the distribution of time to occurrence of an event of two or more independent samples.
Log-Rank Test Calculator
https://numiqo.com/statistics-calculator/survival-analysis/cox-regression
All Videos:
Survival Analysis Basics: https://youtu.be/Wo9RNcHM_bs
Kaplan-Meier-Curve: https://youtu.be/L_ziqYhksG8
Log-Rank Test: https://youtu.be/FhUkDRzHdHE
Cox Regression: https://youtu.be/DpZoRqqDgXA Log-Rank Test [Simply Explained]](https://i.ytimg.com/vi/FhUkDRzHdHE/mqdefault.jpg)
![Descriptive Statistics [Simply explained]
In this video we are gone talk about descriptive statistics and I will explain the four key components in a simple way. Descriptive statistics aims to describe and summarize a dataset in a meaningful way. It provides a simple overview of the main characteristics of data. But it is important to note, that descriptive statistics only describe the collected data without drawing conclusions about a larger population. To describe data descriptively, we look at the four key components:
Measures of Central Tendency, Measures of Dispersion, Frequency Tables and Charts
► Descriptive Statistics Calculator
https://numiqo.com/statistics-calculator/descriptive-statistics/create-frequency-table-and-crosstab?example=descriptive
► Load Data Set
https://numiqo.com/statistics-calculator/descriptive-statistics/create-frequency-table-and-crosstab?example=descriptive
► EBOOK
https://numiqo.com/statistics-book
0:00 What is Descriptive Statistics?
0:40 What is Descriptive Statistics vs. Inferential Statistics
1:13 Measures of Central Tendency, Measures of Dispersion, Frequency Tables and Charts
1:27 What are Measures of Central Tendency?
3:58 What are Measures of Dispersion?
6:19 Measures of Central Tendency vs. Measures of Dispersion?
7:13 What are frequency table and contingency table?
9:22 Charts in Descriptive Statistics Descriptive Statistics [Simply explained]](https://i.ytimg.com/vi/FzujIYo9GYo/mqdefault.jpg)

![Hypothesis [Research Hypothesis simply explained]
What is a hypothesis? How are hypotheses formulated? And what types of And what types of hypotheses are there?
A hypothesis is an assumption or conjecture about a relationship.
For example, your hypothesis might be:
Men earn more than women in Germany.
Our goal now is to test this hypothesis.
So we want to know whether to reject or retain the hypothesis.
But what is it about null and alternative hypotheses?
Two hypotheses are always formulated, that assert the opposite.
These are called the null and alternative hypotheses.
Tutorial:
https://numiqo.com/tutorial/hypothesis
Linke to the Statistics Calculator:
https://numiqo.com/statistics-calculator/descriptive-statistics
Link to the Survey App
https://numiqo.com/survey/
00:12 What is a hypothesis?
00:58 How to formulate a hypothesis?
01:34 What is a variable?
02:25 Null and alternative hypotheses?
03:21 Different types of hypotheses
06:09 What are hypothesis tests? Hypothesis [Research Hypothesis simply explained]](https://i.ytimg.com/vi/G4LPPS-8Co0/mqdefault.jpg)




