Uploaded June 2026 | Updated September 2026, 1 day ago
Design of Experiments helps you test smarter, not just more. In this video, we explain how DoE works, why it can reduce the number of experiments, and how it helps you learn more about your process with fewer runs.
► Design of Experiments Software numiqo
/statistics-calculator/design-of-experiments/design-of-experiments-software
Design of Experiments helps you test smarter, not just more. In this video, we explain how DoE works, why it can reduce the number of experiments, and how it helps you learn more about your process with fewer runs.
► Design of Experiments Software numiqo
/statistics-calculator/design-of-experiments/design-of-experiments-software
![Normality test [Simply Explained]](https://i.ytimg.com/vi/AVketBmpUTE/mqdefault.jpg "Normality test [Simply Explained]
One of the most common requirements for statistical test procedures is that the data used must be normally distributed. For example, if a t-test or an ANOVA is to be calculated, it must first be tested whether the data or variables are normally distributed. This is done with a test of normality.
If the normal distribution of the data is not given, the above procedures cannot be used and the non-parametric tests, which do not require normal distribution of the data, must be used.
How do I test normal distribution?
Normal distribution can be tested either analytically or graphically. The most common analytical tests to check data for normal distribution are the:
1) Kolmogorov-Smirnov Test
2) Shapiro-Wilk Test
3) Anderson-Darling Test
For the graphical test either a histogram or the Q-Q plot is used. Q-Q stands for Quantile Quantile Plot, it compares the actual observed distribution and the expected theoretical distribution.
Normality test
https://numiqo.com/tutorial/test-of-normality
Statistics Calculator:
https://numiqo.com/statistics-calculator/descriptive-statistics")
![t-test for dependent samples [in 60 sec.] #shorts](https://i.ytimg.com/vi/ByST3w5PebI/mqdefault.jpg "t-test for dependent samples [in 60 sec.] #shorts
t-test for dependent samples (paired samples t test) #datascience #dataanalysis #stats #research #machinelearning #datatab #statistics #dataanalytics")
![Logistic Regression [Simply explained]](https://i.ytimg.com/vi/C5268D9t9Ak/mqdefault.jpg "Logistic Regression [Simply explained]
What is a Logistic Regression? How is it calculated? And most importantly, how are the logistic regression results interpreted? In a logistic regression, the dependent variable is a dichotomous variable. Dichotomous variables are variables with only two values. For example: Whether a person buys or does not buy a particular product. Logistic regression is very often used in machine learning.
► Load Example Dataset
https://numiqo.com/statistics-calculator/regression?example=Medical_example_logistic_regression
► Online Logistic Regression Calculator
https://numiqo.com/statistics-calculator/regression
►Tutorial Logistic Regression
https://numiqo.com/tutorial/logistic-regression
► E-BOOK
https://numiqo.com/statistics-book
00:00 What is a Regression
00:45 Difference between Linear Regression and Logistic Regression
01:24 Example Logistic Regression
02:23 Why do we need Logistic Regression?
03:31 Logistic Function and the Logistic Regression equation
05:01 How to interpret the results of a Logistic Regression?
07:58 Logistic Regression: Results Table
08:21 Logistic Regression: Classification Table
09:19 Logistic Regression: and Chi Square Test
10:22 Logistic Regression: Model Summary
11:24 Logistic Regression: Coefficient B, Standard error, p-Value and odds Ratio
13:56 ROC Curve (receiver operating characteristic curve)
#statistics")
