Subject: Subject Sylbus: Quantitative Applications in Biotech - 098002

Quantitative Applications in Biotech - 098002
Will not be given the year
Credit
Points
2.0
 
  Lecture Exercise Laboratory Project or
Seminar
House
Work
Weekly
Hours
2        

Determination of the grade according to progress during the semester.


Prerequisites: Quantitative Methods for Managers 098730
or Statistics for Managers 098740


The Course Will Focus on the Acquisition of Quantative Methods for Managers in the Life Science Industries. Students Will Be Required to Prepare Assignments During the Course as Well as a Final Project Implementing the Quantitative Methods.Emphasis Will Be Put on Management of Database, Risk Evaluation and Analytic Tools.5

Learning Outcomes
At the End of the Course the Students Will Be Familiar with the Existing Trends in Information Managment in the Life Science Industry,Advanced Statistical Programs, Including Their Characteristics and Their Advantages and Disadvantages. the Students Will Practice the Tools They Learned on Real Problems. the Students Will Learn About the Development of Information and Data Processing. in Addition, Students Will Learn the Role of the Data Scientist, Managing of Big Data and Its Challenges,Expected Future Trends, and Risk Assessment,and the Challenges Facing Managers in Life Science. in Addition, Students Will Learn the Principles of Experimental Planning,Design Errors, Data Diagnossis, Detecting Outliers, Handling Missing Information, Simulations, Validation and Reliability Testing. in Addition, They Will Study Concepts and Methods of Data Analysis Used in Life Sciences Research, with Empirical Practice and Experience in Using Statistical Packages and Will Get Familiar with Tools for Data Mining,So That as Managers in the Life Science Industry They Will Better Understand the Needs, Abilities and Limitations and Will Know How to Connect Between the Research and Market Needs.




Textbooks
PublishedPublisherAuthorsBook
1979האוניברסיטה הפתוחהקרל המפלפילוסופיה של מדע הטבע
2013רסלינגאור דגןעל האבסורד במדע
2018john wiley and sons, inc.galit shmueli, peter c. brucedata mining for business analytics: concepts, tech applications in r 1st editionjohn
2017john wiley and sons, incfield cadythe data science handbook 1st edition
2012john wiley and sons, inc.william f. christensen lvin c. rencher amethods of multivariate analysis
2018springer international publishingpaul d. berger, robert e. maurer, giovexperimental design: with applications in manageme the sciences 2nd ed. 8102 edition
2015springer international publishingjohn lawsondesign and analysis of experiments with r (chapman in statistical science) 1st edition

Created in 06/03/2021 Time 01:20:22