Statistical inference | Parametric statistics

Parametric statistics

Parametric statistics is a branch of statistics which assumes that sample data comes from a population that can be adequately modeled by a probability distribution that has a fixed set of parameters. Conversely a non-parametric model does not assume an explicit (finite-parametric) mathematical form for the distribution when modeling the data. However, it may make some assumptions about that distribution, such as continuity or symmetry. Most well-known statistical methods are parametric. Regarding nonparametric (and semiparametric) models, Sir David Cox has said, "These typically involve fewer assumptions of structure and distributional form but usually contain strong assumptions about independencies". (Wikipedia).

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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

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07 Parametric tests

In this video I show you how to conduct a t-test, analysis of variance, and linear regression in SPSS.

From playlist Healthcare statistics with SPSS

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Introduction to Parametric Equations

This video defines a parametric equations and shows how to graph a parametric equation by hand. http://mathispower4u.yolasite.com/

From playlist Parametric Equations

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Calculus 2: Parametric Equations (1 of 20) What is a Parametric Equation?

Visit http://ilectureonline.com for more math and science lectures! In this video I will explain what is a parametric equation. A parametric equation is an equation that expresses each variable of an equation in terms of another variable. Next video in the series can be seen at: https://

From playlist CALCULUS 2 CH 17 PARAMETRIC EQUATIONS

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A Gentle Introduction to Non-Parametric Statistics (15-1)

We are now going to look at a special class of tests that give us the ability to do statistical analyses in circumstances when parametric tests just won’t do. They are called non-parametric statistics. Parametric statistics like t tests and ANOVA compare groups using scale-level data. Non-

From playlist WK15 Chi-Square & Non-Parametric Alternatives - Online Statistics for the Flipped Classroom

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ParamHypTestsP1.5.T-Test

This video is brought to you by the Quantitative Analysis Institute at Wellesley College. The material is best viewed as part of the online resources that organize the content and include questions for checking understanding: https://www.wellesley.edu/qai/onlineresources

From playlist Parametric Hypothesis Tests, Part 1

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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)

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7.1 Parametric Equations

OpenStax Calculus Volume 2

From playlist Calculus 2

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ParamHypTestsP1.6.2 Sample Z-Test

This video is brought to you by the Quantitative Analysis Institute at Wellesley College. The material is best viewed as part of the online resources that organize the content and include questions for checking understanding: https://www.wellesley.edu/qai/onlineresources

From playlist Parametric Hypothesis Tests, Part 1

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Parametric Statistics are ROBUST – Is that So? (16-8)

The good news is that parametric statistics are robust to violations of their assumptions. The bad news is that many people misunderstand what that means. I explain the limitations of robustness and when you should opt for a non-parametric alternative test. Chapters 0:00 What if assumpti

From playlist Assumptions, Significance, & Effect Size Wrap-Up (WK 16 - QBA 237)

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Non-Parametric Alternative Hypothesis Tests in Business Statistics

A parametric test may be used when your data are scale level and the assumptions of the test have been met. Each of the parametric tests we have learned about has an alternative non-parametric test that can be used when your data are nominal or ordinal, your scale data are skewed or non-no

From playlist Business Statistics Lectures (FA2020, QBA337 @ MSU)

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Statistics For Data Science | Data Science Tutorial | Simplilearn

🔥 Advanced Certificate Program In Data Science: https://www.simplilearn.com/pgp-data-science-certification-bootcamp-program?utm_campaign=StatisticsForDataScience-Lv0xcdeXaGU&utm_medium=DescriptionFirstFold&utm_source=youtube 🔥 Data Science Bootcamp (US Only): https://www.simplilearn.com/da

From playlist Data Science For Beginners | Data Science Tutorial🔥[2022 Updated]

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Check Your Assumptions – The Test Assumptions of Statistical Testing (8-12)

You know what happens when you assume? If your assumptions are wrong, it prevents you from looking at the world accurately. Parametric inferential statistics are built on certain assumptions about the data. And if those assumptions are violated, the conclusions based on those assumptions a

From playlist WK8 Statistical Hypothesis Testing (NHST) - Online Statistics for the Flipped Classroom

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Parametric vs. nonparametric statistics

This video lesson is part of a complete course on neuroscience time series analyses. The full course includes - over 47 hours of video instruction - lots and lots of MATLAB exercises and problem sets - access to a dedicated Q&A forum. You can find out more here: https://www.udemy.

From playlist NEW ANTS #5) Permutation-based statistics

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L'indice di Gini

In questo video parlo un po' dell'indice di Gini, importante misura di concentrazione utilizzata nello studio della disuguaglianza economica. Cerco di spiegare l'intuizione alla base dell'indice, e come evitare di farsi prendere per il naso, quando qualcuno ne parla. Indice: 00:00 Intro e

From playlist Sproloqui e commenti (in Italian)

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FRM: Parametric value at risk (VaR): Pros & Cons

Here is a quick explanation of parametric value at risk (VaR) as a means to illustrating its strengths/weaknesses. Please note: The essence of parametric VaR is "no data:" while historical data is surely used to select a distribution and calibrate its parameters, a parametric VaR leans on

From playlist Value at Risk (VaR): Introduction

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Check Your Assumptions for Hypothesis Testing: An Introduction (Week 16A)

If our assumptions are wrong, then any conclusions drawn from those assumptions will likely be wrong. Wrapping up Hypothesis Testing, we dive deeper into some ideas that are not in the textbook but are vital for real world analysis. First, we explore what it means to check the assumptions

From playlist Basic Business Statistics (QBA 237 - Missouri State University)

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Introduction to statistics

This lecturelet will introduce you to the series on statistical analyses of time-frequency data. For more online courses about programming, data analysis, linear algebra, and statistics, see http://sincxpress.com/

From playlist OLD ANTS #8) Statistics

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Eliminating the parameter for parametric trigonometric

Learn how to eliminate the parameter in a parametric equation. A parametric equation is a set of equations that express a set of quantities as explicit functions of a number of independent variables, known as parameters. Eliminating the parameter allows us to write parametric equation in r

From playlist Parametric Equations

Related pages

Sufficient statistic | Normal distribution | Independence (probability theory) | Statistical Methods for Research Workers | Statistical parameter | David Cox (statistician) | Standard deviation | Mean | All models are wrong | Probability distribution | Inverse problem | Parametric model