SUBMIT
STATISTICAL DATA ANALYSIS
LEAH 
ISAKOV

We offer innovative university degrees taught in English by industry leaders from around the world, aimed at giving our students meaningful and creatively satisfying top-level professional futures. We think the future is bright if you make it so.

This advanced course is devoted to the vast array of statistical analysis methods with focus on the applications.

We would consider various standard data analysis tasks that require statistics, study the statistical methods, learn their limits and assumptions, evaluate model fit and results interpretation.

Also, the apply methodology to different datasets and problems using R.

Dr. Leah Isakov is a senior leader in the pharmaceutical industry with a unique combination of leadership and technical skills. She has worked in clinical trials for more than two decades and is known for delivering results. She has led NDA (New Drug Applications), PMA (Pre-Marketing Approvals) and BLA (Biologics License Applications) and has deep experience interacting with all the major regulatory bodies (FDA, EMEA, PMDA, Russian Ministry of Health, and Health Canada).

She also has direct experience successfully managing cross-cultural international teams (USA, China, Japan and Canada). Her recent therapeutic areas include Oncology, Infectious Diseases, Cardiovascular, Asthma, Renal Failure and HIV for Phase II-IV clinical trials in drugs and biologics.

As a leader, Leah strives to be at the forefront of management practice. She incorporates data-driven decision making and quantitative risk management, and focuses on building internal capabilities along with external collaborations. She believes that successful management comes from understanding the full organisational stack; that is, not only high-level strategy, but also the technical aspects that enable success.


Leah has a strong grasp of the technical side from two decades of hands-on experience in analytics, protocol design, sample size calculation, SAS programming, and integrated analysis (ISS and ISE), as well as strong GCP and regulatory knowledge.

After completing this course, a student will be able to:

- Identify cases where statistical analysis should be applied


- Select the most appropriate statistical method for the analysis


- Check if the data in hand satisfies the underlying assumptions of the method


- Run the analysis using R


- Interpret results

SKILLS:

-Analytics

-Business Strategy

-Clinical Development

-Biostatistics

ABOUT LEAH
HARBOUR.SPACE 
WHAT YOU WILL LEARN
RESERVE MY SPOT

DATE: 10 Jun - 28 Jun, 2019

DURATION: 3 Weeks

LECTURES: 3 Hours per day

LANGUAGE: English

LOCATION: Barcelona, Harbour.Space Campus

COURSE TYPE: Offline

HARBOUR.SPACE UNIVERSITY

RESERVE MY SPOT

DATE: 10 Jun - 28 Jun, 2019

DURATION:  3 Weeks

LECTURES: 3 Hours per day

LANGUAGE: English

LOCATION: Barcelona, Harbour.Space Campus

COURSE TYPE: Offline

All rights reserved. 2017

Harbour.Space University
Tech Heart
COURSE OUTLINE
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Session 1

Introduction/review, data types, probability and laws of probability. Random data types

Session 4

Central Limit Theorem
and sampling distribution
MLE

Session 3

Distribution, density function, expectations
Measures of Quality of Estimators
Sufficient Statistics
Completeness and Uniqueness

Session 2

Foundations of statistics: estimation and hypothesis testing

STATISTICAL
DATA ANALYSIS
BIBLIOGRAPHY

This advanced course is devoted to the vast array of statistical analysis methods with focus on the applications.

We would consider various standard data analysis tasks that require statistics, study the statistical methods, learn their limits and assumptions, evaluate model fit and results interpretation.

Also, the apply methodology to different datasets and problems using R.

After completing this course, a student will be able to:

- Identify cases where statistical analysis should be applied


- Select the most appropriate statistical method for the analysis


- Check if the data in hand satisfies the underlying assumptions of the method


- Run the analysis using R


- Interpret results

Dr. Leah Isakov is a senior leader in the pharmaceutical industry with a unique combination of leadership and technical skills. She has worked in clinical trials for more than two decades and is known for delivering results. She has led NDA (New Drug Applications), PMA (Pre-Marketing Approvals) and BLA (Biologics License Applications) and has deep experience interacting with all the major regulatory bodies (FDA, EMEA, PMDA, Russian Ministry of Health, and Health Canada).

She also has direct experience successfully managing cross-cultural international teams (USA, China, Japan and Canada). Her recent therapeutic areas include Oncology, Infectious Diseases, Cardiovascular, Asthma, Renal Failure and HIV for Phase II-IV clinical trials in drugs and biologics.

As a leader, Leah strives to be at the forefront of management practice. She incorporates data-driven decision making and quantitative risk management, and focuses on building internal capabilities along with external collaborations. She believes that successful management comes from understanding the full organisational stack; that is, not only high-level strategy, but also the technical aspects that enable success.


Leah has a strong grasp of the technical side from two decades of hands-on experience in analytics, protocol design, sample size calculation, SAS programming, and integrated analysis (ISS and ISE), as well as strong GCP and regulatory knowledge.

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