Statistics Lecture 3.3: Finding the Standard Deviation of a Data Set
https://www.patreon.com/ProfessorLeonard Statistics Lecture 3.3: Finding the Standard Deviation of a Data Set
From playlist Statistics (Full Length Videos)
t Test Write Up of a Hypothesis Test of an Unknown Population Mean
How to perform and write up a hypothesis test [t test] of an unknown population mean [In accordance with AP Statistics requirements]
From playlist Unit 9: t Inference and 2-Sample Inference
Excel for Statistics 8a--t-tests, introduction and one-sample
This video explains how t-tests work, and shows how to perform a one-sample t-test in Excel
From playlist RStats Videos
Data that are collected for statistical analysis can be classified according to their type. It is important to know what data type we are dealing with as this determines the type of statistical test to use.
From playlist Learning medical statistics with python and Jupyter notebooks
Learning the One Sample t Test by Hand with Excel (10-3)
To really understand the fundamentals of statistics, it is helpful to calculate a one-sample t test by hand using formulas. To make the calculations easier, we use Excel for the math. We will use the five steps of hypothesis testing and Student's t table, to learn the test. This example us
From playlist WK10 One Sample t Tests - Online Statistics for the Flipped Classroom
How to Do a One Sample t Test in SPSS (10-4)
The one sample t-test compares the mean of a sample that you select to a population mean. We will do the one sample t-test in SPSS. Along the way, we refer to the five steps of hypothesis testing and Student's t table to learn how to interpret the findings. This example uses fictitious dat
From playlist Introduction to SPSS Statistics 27
Parametric and nonparametric tests
Parametric tests are most commonly used in healthcare research. They include tests such as Student's t-test and ANOVA. There is, however a rich set of non-parametric tests that are much more appropriate to use in certain circumstances.
From playlist Learning medical statistics with python and Jupyter notebooks
Statistics Lecture 8.2: An Introduction to Hypothesis Testing
https://www.patreon.com/ProfessorLeonard Statistics Lecture 8.2: An Introduction to Hypothesis Testing
From playlist Statistics (Full Length Videos)
This video is part of a full course on statistics and machine-learning. The full course includes 35 hours of video instruction, tons of Python and MATLAB code, and access to the Q&A forum. More information available here: https://www.udemy.com/course/statsml_x/?couponCode=202006 For a co
From playlist Statistics and machine learning
Lecture 0603 Model selection and training/validation/test sets
Machine Learning by Andrew Ng [Coursera] 06-01 Advice for applying machine learning
From playlist Machine Learning by Professor Andrew Ng
Stanford EE104: Introduction to Machine Learning | 2020 | Lecture 4 - validation
Professor Sanjay Lall Electrical Engineering To follow along with the course schedule and syllabus, visit: http://ee104.stanford.edu To view all online courses and programs offered by Stanford, visit: https://online.stanford.edu/
From playlist Stanford EE104: Introduction to Machine Learning Full Course
Lecture 06-01 Advice for applying machine learning
Machine Learning by Andrew Ng [Coursera] 0601 Deciding what to try next 0602 Evaluating a hypothesis 0603 Model selection and training/validation/test sets 0604 Diagnosing bias vs variance 0605 Regularization and bias/variance 0606 Learning curves 0607 Deciding what to try next (revisited
From playlist Machine Learning by Professor Andrew Ng
Robot Framework Tutorial | Robot Framework With Python | Python Robot Framework | Edureka
** Edureka Python Certification Training: https://www.edureka.co/python ** This Edureka video on 'Robot Framework With Python' explains the various aspects of robot framework in python with a use case showing web testing using selenium library. Following are the topics discussed in this Ro
From playlist Python Programming Tutorials | Edureka
Applied ML 2020 - 03 Supervised learning and model validation
Class materials: https://www.cs.columbia.edu/~amueller/comsw4995s20/
From playlist Applied Machine Learning 2020
Adversarial Testing | Stanford CS224U Natural Language Understanding | Spring 2021
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai To learn more about this course visit: https://online.stanford.edu/courses/cs224u-natural-language-understanding To follow along with the course schedule and s
From playlist Stanford CS224U: Natural Language Understanding | Spring 2021
Aaditya Ramdas: Universal inference using the split likelihood ratio test
CIRM VIRTUAL EVENT Recorded during the meeting "Mathematical Methods of Modern Statistics 2" the June 05, 2020 by the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by worldwide mathematicians
From playlist Virtual Conference
What is a t-test? Brief overview of the t value and test, using Excel for the calculations.
From playlist t-test
Applied Machine Learning 2019 - Lecture 04 - Introduction to supervised learning
Nearest neighbors, nearest centroids, cross-validation and grid-search Materials on the course website: https://www.cs.columbia.edu/~amueller/comsw4995s19/schedule/
From playlist Applied Machine Learning - Spring 2019