Confidence weighting (CW) is concerned with measuring two variables: (1) what a respondent believes is a correct answer to a question and (2) what degree of certainty the respondent has toward the correctness of this belief. Confidence weighting when applied to a specific answer selection for a particular test or exam question is referred to in the literature from cognitive psychology as item-specific confidence, a term typically used by researchers who investigate metamemory or metacognition, comprehension monitoring, or feeling-of-knowing. Item-specific confidence is defined as calibrating the relationship between an objective performance of accuracy (e.g., a test answer selection) with the subjective measure of confidence, (e.g., a numeric value assigned to the selection). Studies on self-confidence and metacognition during test taking (e.g.,) have used item-specific confidence as a way to assess the accuracy and confidence underlying knowledge judgments. Researchers outside of the field of cognitive psychology have used confidence weighting as applied to item-specific judgments in assessing alternative conceptions of difficult concepts in high school biology and physics (e.g.,), developing and evaluating computerized adaptive testing (e.g.,), testing computerized assessments of learning and understanding (e.g.,), and developing and testing formative and summative classroom assessments (e.g.,). Confidence weighting is one of three components of the Risk Inclination Model. (Wikipedia).
Lesson: Calculate a Confidence Interval for a Population Proportion
This lesson explains how to calculator a confidence interval for a population proportion.
From playlist Confidence Intervals
Statistics 5_1 Confidence Intervals
In this lecture explain the meaning of a confidence interval and look at the equation to calculate it.
From playlist Medical Statistics
How To Be Confident Without Being Arrogant
Conor McGregor: How To Be Confident Without Being Arrogant Get Our Best Tip To Turning On Confidence In Just 60 Seconds: https://goo.gl/AiIEjJ Conor McGregor is one of the most confident athletes in the world. He displayed that confidence in his flawless victory over Eddie Alvarez in UFC
From playlist How To Be Confident
Calculate a Confidence Interval for a Population Proportion (Plus Four Method)
This lesson explains how to calculator a confidence interval for a population proportion using the Plus Four Method.
From playlist Confidence Intervals
Calculate a Confidence Interval for a Population Proportion (Basic)
This example explains how to calculator a confidence interval for a population proportion.
From playlist Confidence Intervals
07 Data Analytics: Confidence Intervals
Lecture on confidence intervals. What are they? How to calculate them? How we can impact business decisions.
From playlist Data Analytics and Geostatistics
Using Excel to Construct One Sample Confidence Intervals for Means and Proportions
A Microsoft Excel tutorial on: Introduction to Confidence Intervals 0:39 Constructing a Confidence Interval for Means Where 𝜎 is Known 5:41 Constructing a Confidence Interval for Means Where 𝜎 is Unknown 14:20 Constructing a Confidence Interval for Proportions 22:19 This tutorial covers u
From playlist Using Excel in Statistics
How to find a confidence interval for a proportion
How to find a confidence interval for a proportion using a z-table.
From playlist Hypothesis Tests and Critical Values
Overfitting 3: confidence interval for error
[http://bit.ly/overfit] The error on the test set is an approximation of the true future error. How close is it? We show how to compute a confidence interval [a,b] such that the error of our classifier in the future is between a and b (with high probability, and under the assumption that f
From playlist Overfitting
Expected shortfall: approximating continuous, with code (ES continous, FRM T5-03)
In my previous video, I showed you how we retrieve expected shortfall under the simplest possible discrete case. That was a simple historical simulation, but that was discrete. In this video, I'm going to review expected shortfall when the distribution is continuous. Specifically, I will u
From playlist Market Risk (FRM Topic 5)
Hypothesis Test and Confidence Interval for Two Populations Means in StatCrunch
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Hypothesis Test and Confidence Interval for Two Populations Means in StatCrunch
From playlist Statistics
Confidence Interval for the Population Mean and Interpretation Example with T Stats in StatCrunch
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Confidence Interval for the Population Mean and Interpretation Example with T Stats in StatCrunch
From playlist Statistics
Method of Simulated Moments (MSM)
MIT 15.879 Research Seminar in System Dynamics, Spring 2014 View the complete course: http://ocw.mit.edu/15-879S14 Instructor: William Chernicoff, George Miller, Sergey Naumov, Jim Qian Video tutorial created by students as part of the class final project. License: Creative Commons BY-NC
From playlist MIT 15.879 Research Seminar in System Dynamics, Spring 2014
Statistics: Ch 8 Hypothesis Testing (33 of 35) Example Problem #4
Visit http://ilectureonline.com for more math and science lectures! To donate: http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071a Given: The wight of cereal boxes has a standard deviation of 0.27 ounces. A random sample of 18 boxes have a mean weight of 9.87 oun
From playlist STATISTICS CH 9 HYPOTHESIS TESTING
Construct and Interpret a Confidence Interval for the Population Mean
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Construct and Interpret a Confidence Interval for the Population Mean
From playlist Statistics
Lect.11E: Statistics For The Line: Confidence And Prediction Intervals Lecture 11
Lecture with Per B. Brockhoff. Lecture 11. Chapters: 00:00 - Confidence Interval For Aplha+Betha*X0; 14:00 - Prediction Interval;
From playlist DTU: Introduction to Statistics | CosmoLearning.org
Introduction to R: T-Tests (Hypothesis Testing)
This is lesson 24 of a 30-part introduction to the R programming language for data analysis and predictive modeling. Link to the code notebook below: Intro to R: Hypothesis Testing https://www.kaggle.com/hamelg/intro-to-r-part-24-Hypothesis-Testing This lesson covers statistical hypothes
From playlist Introduction to R
Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 15 - Batch Reinforcement Learning
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai Professor Emma Brunskill, Stanford University http://onlinehub.stanford.edu/ Professor Emma Brunskill Assistant Professor, Computer Science Stanford AI for Hu
From playlist Stanford CS234: Reinforcement Learning | Winter 2019
The Science of Collaboration - with Uta and Chris Frith
Humans are intensely social creatures. Learning from each other and working together was a key part in our evolutionary development. But what are the advantages of working together, and are two heads always better than one when making decisions? Join Chris and Uta Frith as they explore the
From playlist Ri Talks