Resources to mark the 100th day of school with math activities. Challenge students to generate 100 different ways to represent the number 100. Students will easily generate 99 + 1 and 50 + 50, but encourage them to think out of the box. Challenge them to include examples from all of the NCTM Standards strands: number sense, numerical operations, geometry, measurement, algebra, patterns, data analysis, probability, discrete math, Create a class list to record the best entries. Some teachers write 100 in big bubble numeral style and then record the entries inside the numerals.

The textbook is written as a series of Quarto Documents in RStudio and is aimed both as an educational resource on the topic of categorical data analysis and as an aid to the use of the R language for statistical computing. The rendered textbook is interactive with tasks and solution as well as a series of lab questions at the end of each chapter. It also includes OER resources for various introductory math and statistics courses.

The primary learning objective of this textbook is to introduce the reader to the fundamental statistical methods and basic analytical procedures associated with processing data in regard to healthcare research. It is intended that by working through the applications and practice problems, readers should be able to understand and apply some of the methods for developing, implementing, and applying healthcare statistic principles in research.

The aim of this course is to provide fundamental statistical concepts and tools relevant to the practice of summarizing, analyzing, and visualizing data. This course will build your knowledge of the fundamental principles of biostatistical inference. The course will focus on linear regression and generalized linear regression models. We will use a variety of examples and exercises from scientific, medical, and public health research.

This course addresses the challenges of defining a relationship between exposure to environmental chemicals and human disease. Course topics include epidemiological approaches to understanding disease causation; biostatistical methods; evaluation of human exposure to chemicals, and their internal distribution, metabolism, reactions with cellular components, and biological effects; and qualitative and quantitative health risk assessment methods used in the U.S. as bases for regulatory decision-making. Throughout the term, students consider case studies of local and national interest.

This course addresses the challenges of defining a relationship between exposure to environmental chemicals and human disease. Course topics include epidemiological approaches to understanding disease causation; biostatistical methods; evaluation of human exposure to chemicals, and their internal distribution, metabolism, reactions with cellular components, and biological effects; and qualitative and quantitative health risk assessment methods used in the U.S. as bases for regulatory decision-making. Throughout the term, students consider case studies of local and national interest.

Students are introduced to concepts of hypothesis testing using elementary hypothesis tests, t-tests, and p-values as they compare a given fish population for methylmercury levels (using real and hypothetical data) against real-world mercury standards.

Students are introduced to concepts of sampling distributions and hypothesis testing using a simulation applet, elementary hypothesis tests, t-tests, and p-values as they compare a given fish population for methylmercury levels (using real and hypothetical data) against real-world mercury standards.

Methylmercury contamination within fish populations is an important toxin that affect human, animal, and environmental health, serving as a carcinogen (cancer-causing agent) and endocrine-disruptor (compounds that in some way alter the signaling of the hormone system. The impacts of exceeding safe dietary methylmercury levels were tragically made clear in Ontario, Canada, where a First Nations community in Grassy Narrows are living with the consequences of methylmercury poisoning in the fish supply. The fish were contaminated due to the dumping of mercury in the traditional waterways of the First Nation community. In 2016, there were highly publicized protests in Muskrat Falls, Labrador, Canada, where the Inuit people raised direct concerns about the potential for a proposed Nalcor Energy hydroelectric dam, to increase mercury levels in fish in those waters, which are an integral part of their traditional diet. Despite significant protests, the project was completed in 2019 and 41 km were flooded. This module uses these real-world examples as a jumping-off point for exercises that will guide case-study driven discussion on mathematical, biological and ethical concerns.

Methylmercury contamination within fish populations is an important toxin that affect human, animal, and environmental health, serving as a carcinogen (cancer-causing agent) and endocrine-disruptor (compounds that in some way alter the signaling of the hormone system. The impacts of exceeding safe dietary methylmercury levels were tragically made clear in Ontario, Canada, where a First Nations community in Grassy Narrows are living with the consequences of methylmercury poisoning in the fish supply. The fish were contaminated due to the dumping of mercury in the traditional waterways of the First Nation community. In 2016, there were highly publicized protests in Muskrat Falls, Labrador, Canada, where the Inuit people raised direct concerns about the potential for a proposed Nalcor Energy hydroelectric dam, to increase mercury levels in fish in those waters, which are an integral part of their traditional diet. Despite significant protests, the project was completed in 2019 and 41 km were flooded. This module uses these real-world examples as a jumping-off point for exercises that will guide case-study driven discussion on mathematical, biological and ethical concerns.

Cette ressource propose un recueil de diapos utilisées à l'UCL pour un cours de probabilités et statistique destiné à des étudiants en sciences humaines. Ce cours est précédé, à l'UCL, par un cours de statistique descriptive. N'hésitez pas à contacter l'auteur - bernadette govaerts@uclouvain.be - qui dispose de ressources complémentaires sur le sujet (énoncés d'exercices, jeux de données...).
Contenu :
- Eléments de Probabilités
° P1 : Introduction
° P2 : Calcul de probabilités sur des événements
° P3 : Variables aléatoires : généralités et lois classiques
° P4 : Théorème central limite et combinaisons de variables aléatoires
-Inférence pour une et deux variables
° I1 : Principes de l’inférence statistique (rappels)
° I2 : Inférence sur les paramètres d’UNE variable quantitative normale
° I3 : Tests sur les paramètres d’une variable quantitative normale observée sur deux groupes indépendants ou pairés
° I4 : Inférence sur les paramètres d’une variable catégorielle
° I5 :Tests d’homogénéité et d’indépendance pour deux variables catégorielles
° I6 : Tests non paramétriques sur une ou deux valeurs centrales
° I7: Inférence sur un ou deux coefficients de corrélation
° I8 : Puissance d'un test, calcul de taille d'échantillon

Tables de probabilités et de statistiques : Table de calcul de probabilité pour la loi binomiale Table de calcul de probabilité pour la loi normale Table des quantiles de la v.a. Chi-Carré Table des quantiles de la v.a. Fisher Table des quantiles de la v.a. Normale réduite Table des quantiles de la v.a. Student

Cette ressource propose une série de vidéos permettant un apprentissage autonomne de SPSS ainsi que des fichiers utiles liés. N'hésitez pas à contacter le premier auteur - bernadette govaerts@uclouvain.be - qui dispose de ressources complémentaires sur le sujet (énoncés d'exercices, jeux de données...)

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Microbiome sequencing data are very complex. In order to simplify analyses, researchers often perform unsupervised clustering to identify naturally occurring clusters and then investigate the clusters’ associations with various characteristics of interest. However, clustering performance and related conclusions can vary depending on the algorithm or beta diversity metric used. To improve microbiome analysis methods, a new study tested the performance of several metrics on four datasets with well-separated groups and a clinical dataset with less-clear group separation. None of the metrics was universally superior, but certain metrics underperformed under certain conditions. For example, the Bray-Curtis metric performed poorly in a dataset with rare high-abundance OTUs (groups of related bacteria), while the unweighted UniFrac metric performed poorly in a dataset with prevalent low-abundance OTUs..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Students are introduced to concepts of sampling distributions, p-values, and hypothesis testing. Using both simulated and real data for methylmercury level in fish populations, students will determine whether observations fall within government safety guidelines for safe consumption.