№ files_lp_4_process_3_110076
File format: docx
Character count: 3384
File size: 89 KB
Note:
Year
Topic:
Statistical likelihood models
Document Type:
Technical Description
Target Audience:
Researchers, statisticians
Context:
Technical document explaining various statistical likelihood models, including binomial, normal, regression, exponential, censored exponential, and birth process likelihoods.
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The product description is provided for reference. Actual content and formatting may differ slightly.
Year:
2022
Region / City:
New South Wales, Australia
Subject:
Mathematics
Document Type:
Lesson Plan
Authority:
NSW Education Standards Authority (NESA)
Target Audience:
Students K–10
Curriculum Outcomes:
MAO-WM-01, MA5-ALG-C-01, MA5-ALG-P-01, MA5-ALG-P-02
Lesson Components:
Launch, Explore, Summarise, Apply
Teaching Strategies:
Think-Pair-Share, Pose-Pause-Pounce-Bounce, Gallery Walk, Notes to Future Forgetful Selves
Resources:
PowerPoint Areas for Expansion (AFE PPT), Appendices A–D
Mathematical Focus:
Binomial expansion, area model, monic and non-monic expressions, perfect squares
Year:
2023
Region / city:
N/A
Theme:
Taxonomy
Document Type:
Proposal
Institution:
ICTV
Authors:
McInnes CJ, Damon IK, Smith GL, McFadden G, Isaacs SN, Roper RL, Evans DH, Damaso CR, Carulei O, Wise LM, Takatsuka J, Traktman P, Lefkowitz E
Target Audience:
ICTV members, Taxonomy researchers
Period of validity:
N/A
Approval Date:
June 2023
Date of revisions:
N/A
Corresponding author:
Colin J McInnes
Study group involved:
Poxviridae Study Group
Proposal type:
Taxonomic
Approval votes:
12 in favor, 1 against
Taxon name derived from a living person:
No
Date first submitted:
June 2023
Date of this revision:
N/A
Context:
A proposal outlining the renaming of all species within the Poxviridae family to conform with a binomial species naming convention as per ICTV guidelines.
Note:
Year
Subject:
Algorithms
Document Type:
Technical Paper
Year:
2026
Region / City:
Not specified
Subject:
Statistics / Probability / Hypothesis Testing
Document Type:
Educational Case Study
Institution:
Not specified
Author:
Not specified
Target Audience:
Students or learners of statistics
Sample Size:
Various (30, 50, 120)
Significance Levels:
5%, 10%
Tests Conducted:
One-tailed and two-tailed binomial tests
Variables:
Dice rolls, coin flips, cucumber weights, egg yolks
Purpose:
Assess potential bias or effect of intervention in binomial outcomes
Year:
2023
Topic:
Binomial Distributions, Probability Theory
Document Type:
Educational Material
Author:
Not specified
Target Audience:
Students, Educators
Date Created:
Not specified
Period of Use:
Not specified
Statistical Methods:
Binomial Probability, Mean, Standard Deviation
Year:
2021
Region:
International
Subject:
Mathematics
Document Type:
Examination Resource
Organization:
Pearson Edexcel
Target Audience:
GCSE, AS and A level students and teachers
Purpose:
Provide additional assessment materials for practice and evaluation
Content Focus:
Geometric and negative binomial probability distributions, probability calculations, expected values, game-theory probability problems
Format:
Question sets derived from past papers, optional for teacher use
Series:
Summer 2021
Copyright:
Pearson Education Ltd 2021
Year:
2026
Subject:
Probability and Statistics
Topic:
Binomial Probability, Normal Approximation
Type of Document:
Educational Exercise / Free Response Questions
Target Audience:
High school or college students studying statistics
Sample Size:
21 days
Probability Parameter:
0.2 for daily traffic delay
Question Count:
3
Year:
2020
Region / City:
Not specified
Topic:
Deep learning, convolutional neural networks, survival analysis, radiomics
Document type:
Scientific article
Institution / Organization:
Not specified
Author:
He Kaiming, Sanghyun Woo, Zwanenburg A et al.
Target audience:
Researchers in machine learning, medical imaging, and survival analysis
Period of validity:
Not specified
Approval date:
Not specified
Date of changes:
Not specified
Year:
2023
Region / city:
Not specified
Theme:
Press release, Qualification renewal, Arborist industry
Document type:
Instructional document
Organization / institution:
ASCA (American Society of Consulting Arborists)
Author:
Not specified
Target audience:
Industry professionals, media, press
Validity period:
Not specified
Approval date:
Not specified
Date of change:
Not specified
Year:
2023
Region / City:
N/A
Topic:
Drug repurposing, machine learning models
Document Type:
Research article
Organization / Institution:
N/A
Author:
N/A
Target Audience:
Researchers, Data Scientists
Effective Period:
N/A
Approval Date:
N/A
Modification Date:
N/A
Description of Document:
A research article comparing the performance of different machine learning models in predicting drug-disease approval likelihood using various optimization techniques and cross-validation methods.
Year:
2026
Field:
Statistics / Mathematical Statistics
Document Type:
Academic Text / Lecture Notes
Institution:
Unspecified
Author:
Unspecified
Target Audience:
Graduate students in statistics or related fields
Topics:
Maximum Likelihood Estimation, Cramer-Rao Bound, Efficiency of Estimators, Information Inequality
Examples:
Normal, Binomial, Poisson distributions
Key Formulas:
Variance inequalities, Fisher information, asymptotic distribution of estimators
Notation:
X1, X2, …, Xn ~ i.i.d. f(x|θ), g(θ), θ̂, UMVUE, MLE
Year:
Not specified
Region / City:
Not specified
Theme:
Stock-recruitment relationship, Likelihood profile
Document Type:
Research Report
Organization / Institution:
Not specified
Author:
A. Ross-Gillespie
Target Audience:
Researchers in fisheries science
Period of validity:
Not specified
Approval Date:
Not specified
Date of changes:
Not specified
Year:
2012
Region / City:
Philadelphia, PA
Topic:
Evidence-based physical diagnosis
Document Type:
Reference table / Medical guideline
Institution / Publisher:
Elsevier Saunders
Author:
Steven McGee
Target Audience:
Healthcare professionals, medical students
Clinical Focus:
Diagnostic accuracy using likelihood ratios
Content Coverage:
Acute and chronic diseases, laboratory and imaging tests
Data Format:
Tabular with numerical likelihood ratios
Reference Source:
McGee, Steven. Evidence-Based Physical Diagnosis, 2012
Year:
2018
Region / Institution:
National University of Ireland Galway, Ireland
Subject:
Cognitive training, schizophrenia, neuroimaging
Document type:
Systematic review and meta-analysis
Authors:
David Mothersill, Gary Donohoe
Corresponding author:
Gary Donohoe, Professor of Psychology, School of Psychology, National University of Ireland Galway
Number of studies reviewed:
31
Neuroimaging methods:
fMRI, SPECT, PET, cortical thickness, VBM, DTI
Key findings:
Increased left prefrontal activation, distributed neural effects
Keywords:
neuroimaging; cognitive remediation therapy; psychosis; prefrontal
Word count abstract:
225
Word count main text:
3,007
Figures:
2
Tables:
2
Supplemental information:
1
Time period covered:
studies published until December 2018
Year:
2007
Region / City:
Madison, Wisconsin
Topic:
Climate change, statistical analysis
Document Type:
Educational Activity
Institution:
IPCC, University of Wisconsin-Madison
Author:
IPCC, Researchers at the University of Wisconsin-Madison
Target Audience:
Students, Climate Science Enthusiasts
Period of Validity:
Ongoing (based on annual data from 1855)
Approval Date:
N/A
Date of Changes:
N/A