```LEAH ISAKOV
```

Learn basic concepts of theory and application for statistical inference. Get an introduction to statistical and critical thinking, including descriptive statistics, probability, sampling distributions, interval estimation, hypothesis testing and regression. Use of simulation technique for assessments of model fit, and estimations. Design of experiments from statistical perspectives. Some advanced topics.

```STATISTICAL DATA
ANALYSIS
```

Select and appropriate statistical technique to analyze and interpret observed data. Students should acquire quantitative skills that they can employ and build on in flexible ways. Goals are to learn concepts and master tools for working with data and have experience in analyzing real data.

DATE: 9 Mar - 27 Mar, 2020

DURATION: 3 Weeks

LECTURES: 3 Hours per day

LANGUAGE: English

LOCATION: Barcelona, Harbour.Space Campus

COURSE TYPE: Offline

```WHAT YOU WILL LEARN
```
```COURSE OUTLINE
```

Session 1

Introduction/ review, data types, probability and laws of probability. Random data types. Statistics, data and statistical thinking.
Data visualization.  Measures of central tendency.

Session 2

Measures of Quality of Estimators. MLE/ MOM
Central Limit Theorem and sampling distribution
Large-Sample Confidence Interval for a Population Mean and Proportions
t-Statistics and small sample confidence intervals for a population mean

Session 3

Introduction to hypothesis testing
Inference based on a single sample: test of hypothesis
Introduction to Theory of Statistical Tests
Likelihood Ratio Tests

Session 5

Estimating a proportion
Comparing groups on categorical data
Chi-square tests
Large sample confidence interval for a population proportion

Session 4

Comparing two population means: independent and paired sampling

Session 6

Small sample test, Yates’ correction, Fisher Exact test
Measures of association: Relative Risk and Odds Ratio

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.

SKILLS:

- Analytics

- Clinical Development

- Biostatistics

- C/C++

- OpenGL

- LATEX

- MS Visual Studio

- GNU Optimizing Compilers

- Sun OS

- Linux

```ABOUT LEAH
```

## RESERVE MY SPOT

```STATISTICAL
DATA
ANALYSIS
```

DATE: 9 Mar – 27 Mar, 2020

DURATION:  3 Weeks

LECTURES: 3 Hours per day

LANGUAGE: English

LOCATION: Barcelona, Harbour.Space Campus

COURSE TYPE: Offline

```ANDREY
KHOKHLOV
```

After getting his Ph.D. in Algebraic Topology in 1984 Andrey worked in several scientific and/or teaching organisations, among them are the Russian Academy of Sciences, Moscow State University, and Baumann Technology University. The Scientific advising of the graduate and thesis students was part of his activities, not only in Russia, but also in France.

Andrey’s main results in science are linked with geophysical data processing, so naturally his teaching interests are now concentrated in the applied methods of Statistics and their algorithmic implementations. He currently helps his students avoid some common errors within the probabilistic inferences and support their attempts to study Probability and Statistics theory in general.

```ABOUT ANDREY
```
```HARBOUR.SPACE
```

Harbour.Space is a university created by entrepreneurs for entrepreneurs. We focus on meeting the demands of the future, while traditional education providers are too often stuck in the past.

We’re one of the only European institutions completely dedicated to technology, design and entrepreneurship, and our interdisciplinary courses are taught by some of today’s leading professionals. Our aim is not only to equip students with the knowledge to take on the real world, but to nurture, create and shape tomorrow’s tech superstars.

```HARBOUR.SPACE UNIVERSITY
```
```BIBLIOGRAPHY
```
```Digital Spectral Analysis:
Second Edition by
S. Lawrence Marple Jr.
(Dover Publications, 2019)
```
```All of Statistics: A Concise Course
in Statistical Inference by
Larry Wasserman
(Springer New York, 2010)
```