№ files_lp_4_process_2_83281
File format: docx
Character count: 27620
File size: 1078 KB
Year:
2021
Region / City:
London
Theme:
Computational Psychiatry, Behavioral Science
Document Type:
Research Article
Organization / Institution:
University College London, Max Planck-UCL Centre for Computational Psychiatry and Ageing Research
Author:
Giles W. Story, Ryan Smith, Michael Moutoussis, Isabel M. Berwian, Tobias Nolte, Edda Bilek, Raymond J. Dolan
Target Audience:
Researchers in computational psychiatry, neuroscience
Period of Validity:
Not specified
Approval Date:
Not specified
Modification Date:
Not specified
Contextual Description:
A research article detailing a model for social inference through hidden Markov models, exploring the effects of internal and external states on behavior.
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Year:
2012
Region / City:
N/A
Topic:
Statistics, Chi-Square Test
Document Type:
Educational Material
Institution:
AP Statistics
Author:
N/A
Target Audience:
Students, Educators
Effective Period:
N/A
Approval Date:
N/A
Revision Date:
N/A
Context:
A chapter from an educational textbook explaining chi-square goodness of fit tests for categorical variables.
Year:
2023
Topic:
Statistical Inference and Sampling Methods
Document Type:
Educational Material
Author:
Unspecified
Intended Audience:
Students or professionals in statistics
Scope of Applicability:
General
Date of Approval:
Unspecified
Date of Changes:
Unspecified
Type of Document:
Examination Paper
Subject:
Statistics
Topics Covered:
Descriptive Statistics, Probability, Binomial Distribution, Normal Distribution, Confidence Intervals, Hypothesis Testing, Regression Analysis
Total Points:
100
Number of Questions:
10
Institution Context:
Local College / University
Statistical Tools Referenced:
Binomial Probability Tables, Excel Output, ANOVA
Data Contexts:
Student Age Distribution, Television Viewing Time, University Admissions, Airline Pilot Income, Soft Drink Filling Process, Product Demand and Price, Course Passing Probabilities, National Exam Scores, Stock Prices and Market Activity
Assessment Format:
Problem-Solving and Analytical Calculations
Year:
2023
Region / city:
Córdoba, Argentina
Topic:
Cognitive science, Philosophy of representation
Document type:
Research paper
Organization:
UNC, IDH-CONICET
Author:
Mariela Aguilera
Target audience:
Scholars in cognitive science, philosophy, and neuroscience
Period of validity:
N/A
Approval date:
N/A
Modification date:
N/A
Year:
1998–2016
Region / Country:
United Kingdom
Subject:
Epidemiology, Causal Inference, Psychosocial Measurement
Document Type:
Research Supplement / eAppendix
Institution:
Clinical Practice Research Datalink (CPRD)
Authors:
Bhaskaran et al.
Population:
Never-smokers aged 16 and above
Methodology:
Proportional hazards modeling with covariate adjustment
Variables:
BMI, age, sex, alcohol use, diabetes, socioeconomic status, calendar period
Outcome:
10-year mortality risk
Analytical Framework:
Multiple Versions of Treatment (MVT) theory
Year:
2014
Publication:
Sportscience
Volume:
18
Pages:
48
Author:
Martin Buchheit
Affiliation:
Performance Department, Paris Saint-Germain Football Club, Paris, France
Type:
Commentary / News & Comment
Topic:
Magnitude-Based Inference in Sports Science
Email:
Provided in document
Date published:
November 2014
Related authors:
Will Hopkins, Alan Batterham
Audience:
Scientists and practitioners in sports performance and research
Year:
2026
Region / city:
Goa, India
Topic:
AI/ML inference, distributed inference
Document type:
Technical report
Organization:
3GPP
Author:
CATT
Target audience:
3GPP TSG-SA5 members
Effective period:
February 9-13, 2026
Approval date:
TBD
Date of amendments:
TBD
Note:
Year
Topic:
Statistical Inference
Document Type:
Educational Material
Target Audience:
Students, Researchers
Note:
Year
Topic:
Probability theory, Multinomial distribution
Document Type:
Academic article
Target Audience:
Researchers, statisticians
Subject:
Science
Topic:
Observation and inference, metric measurement, scientific method, graphing
Document Type:
Educational worksheet
Educational Level:
School science education
Content Components:
Definitions, explanations, exercises, review questions
Concepts Covered:
Observation, inference, measurement, scientific method, variables, graph construction
Activities Included:
Fill-in-the-blank questions, classification tasks, experimental design prompts, graphing exercises
Instructional Context:
Classroom or laboratory science instruction
Assessment Elements:
Review questions and multiple-choice question
Practical Focus:
Laboratory safety, measurement rounding, data interpretation
Document type:
Research proposal section
Research area:
Systems biology and epigenetics
Scientific field:
Gene regulatory network modeling
Research focus:
Integration of epigenetic regulators into gene network inference
Model organism:
Arabidopsis thaliana
Key regulator studied:
SET Domain Group 8 (SDG8)
Homologous human protein:
SETD2
Epigenetic mechanism:
H3K36 histone methylation
Biological processes referenced:
Gene regulation and chromatin modification
Methodological approaches:
Time-course transcriptome analysis, predictive network modeling, dynamic Bayesian networks, state-space modeling
Data sources referenced:
Epigenomics datasets and ENCODE resources
Research objectives:
Identification of genomic targets of epigenetic regulators and evaluation of their role as predictors in gene regulatory network models
Proposed framework:
EpiNet
Research components:
Significance, Innovation, and Approaches
Experimental strategy:
Integration of experimental perturbation data with computational network inference
Note:
Year
Contextual description:
A scientific paper presenting supplementary methods related to polygenic analysis and causal inference in the relationship between loneliness, isolation, and schizophrenia.
Year:
2026
Location:
Goa, India
Document Type:
Technical Report Contribution
Organization:
3GPP TSG-SA5
Author:
CATT
Target Audience:
3GPP SA5 Members
Work Item:
FS_AIML_MGT_Ph3
Version:
0.2.0
Specification:
3GPP TR 28.882
Agenda Item:
6.20.2
Document Purpose:
Approval
Date:
9–13 February 2026
Scope:
Distributed AI/ML Inference Management
Key Topics:
AI/ML inference, distributed computing, network management, edge analytics
Department:
Department of Statistical and Actuarial Sciences
Course Number:
SS9030B
Course Name:
Statistical Inference
Academic Term:
Winter 2025
Institution:
Western University
Instructor:
Dr. Wenqing He
Teaching Assistant:
Not specified
Lecture Schedule:
Tuesday 10:00–11:30am; Thursday 10:00–11:30am
Classroom:
WSC 248
Instructor Office:
WSC 213
Office Hours:
Thursday 11:30am–12:30pm
Contact Email:
[email protected]
Course Delivery Mode:
In-person with contingency for online delivery
Classes Begin:
January 6, 2025
Reading Week:
February 15–23, 2024
Classes End:
April 4, 2024
Assignments Due Dates:
February 4, March 4, April 3
Tests Dates:
February 13; April 3
Final Take Home Exam:
April 6, 2025 10:00am – April 7, 2025 9:59am (Canadian Eastern Time)
Assessment Structure:
Assignments 15%; Tests 60%; Final Take Home Exam 25%
Main Reference Book:
Statistical Inference, 2nd Edition, George Casella and Roger Berger, Duxbury, 2002
Learning Topics:
Data reduction, point estimation, hypothesis testing, interval estimation, asymptotic inference
Target Audience:
Undergraduate students in statistical and actuarial sciences
Communication Requirement:
Use of official Western University email addresses (@uwo.ca)