#biost

[jupiter-aint-stupider]

I am Ahlam from Gaza

I am 54 years old and have 9 daughters and a son

I suffer from kidney failure, and with limited hospital resources, I ask you to help me go out to receive treatment so that I can take care of my children.

I am displaced in tents. I have been displaced more than 10 times, and my house was bombed, and I have no shelter, and this makes my condition worse.

Every €15 or €20 will contribute to saving

my family🙏🩸

https://gofund.me/61f1dd1f

My campaing Vetted by/ @gazavetters

@90-ghost

@gaza-evacuation-funds

Hello

Unfortunately I don't have money to spare this week, so the best I can do is boost you.

Sending you thoughts and prayers 🙏 🍉 🇵🇸

[robinsoncenter]

Spring 2018 Course Offering - BIOST 311: Regression Methods in the Health Sciences

BIOST 311: Regression Methods in the Health Sciences

Quarter: Spring 2018

Time and Location: MWF 12:30-1:20pm (LC), T 10:30-11:20am (QZ), SCC 301

Grading: Graded, 4 credits

Instructor: Kelsey Grinde ([email protected]) and Brian Williamson ([email protected]), Department of Biostatistics

Prerequisite: Open to all majors. Students should have a background in statistics at the level covered in BIOST 310. QMETH 201 and STAT 220 (or equivalent) are also acceptable, but students who have not taken BIOST 310 should request an add code at http://tinyurl.com/SPR-BIOST311. No prior programming experience is required.

SLN: 11496

The relationship between two variables is often impacted by other factors. In BIOST 311, you’ll learn how to use regression methods to account for these additional variables, and quantify the relationships among multiple variables in a variety of data types.

In particular, the course will cover three types of regression—linear, logistic, and proportional hazards—all at an introductory level. Students will get hands-on experience with data analysis using R, a freely available statistical computing software. Throughout the course, we will make use of examples drawn from the biomedical and health sciences literature.

[robinsoncenter]

BIOST 311: Regression Methods in the Health Sciences

Quarter: Spring 2017

Time and Location: MWF 1:30-2:20pm, Health Sciences RR134 (lecture), T 12:30-1:20pm, Health Sciences T473 (discussion)

Grading: Graded, 4 credits

Instructor: Anna Plantinga, Department of Biostatistics ([email protected])

Prerequisite: Open to all majors. No prior programming experience is required, but students should have a background in statistics at the level covered in BIOST 310. Students without BIOST 310 may contact the instructor for permission.

SLN: 11479

BIOST 311 introduces regression methods for analysis of continuous, binary, and time-to-event (survival) data.

This course will cover linear regression, logistic regression, and proportional hazards regression, all at an introductory level. Students will learn how to use R, a freely available statistical computing software, to display and analyze data. Throughout the course, we will make use of examples drawn from the biomedical and health sciences literature.

[whitetoque]

1 - Albaugh - First Complete Biological Seed Treatment Platform-BIOST | AgroNews

1 – Albaugh – First Complete Biological Seed Treatment Platform-BIOST | AgroNews

"Albaugh, LLC is launching a new biological seed treatment platform that includes a broad portfolio of highly effective and proven biological seed treatments.

The new BIOST biological seed treatment platform will deliver a broad portfolio of biological seed treatments that have been tested to enhance performance and grower return on investment when combined with traditional synthetic seed…

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[replicatore]

La biostampa 3D di organi “nasce” in Corea del Sud

La biostampa 3D di organi “nasce” in Corea del Sud

Per quanto possa sembrare lontana nel tempo, la creazione di organi stampati in 3D e pienamente funzionanti non è affatto fantascienza; almeno così sembrerebbe visto le ricerche all’avanguardia portate avanti dalla Postech University in Corea del Sud.

Un complesso e articolato sistema di sviluppo denominato Intelligent Manufacturing System Lab che, supervisionato dal professor Dong-Woo Cho…

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