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Studies
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The Institute
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DS409

Statistical Data Analysis

Barcelona Campus
Apr 11, 2022 - Apr 29, 2022
During the Statistical Data Analysis course, students learn the basic concepts of theory and application for statistical inference, including descriptive statistics and probability.
Barcelona Campus
Apr 11, 2022 - Apr 29, 2022
Leah Isakov

Faculty

Leah Isakov

Global Head of BioStatistics, Data Management, Programming and Medical Writing at Seqirus

Course length

3 weeks

Duration

3 hours
per day

Total hours

45 hours

Credits

6 ECTS

Language

English

Course type

Offline

Fee for single course

€1500

Fee for degree students

€750

Skills you’ll learn

Data AnalysisData ScienceProbability and StatisticsMathematical Statistics
OverviewCourse outlinePrerequisitesMethod & grading

Overview

Learn basic concepts of theory and application for statistical inference. Get an introduction to statistical analysis 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 experiments from statistical perspectives and explore some advanced topics.

Learning highlights

  • Select an appropriate statistical technique to analyze and interpret the observed data.
  • Students should acquire quantitative skills that they can employ and build on in flexible ways.
  • The goal is to learn concepts and master tools for working with data and understand experiment design.

Course outline

15 classes

Dive into the details of the course and get a sense of what each class will cover.
Monday
Tuesday
Wednesday
Thursday
Friday
Monday
1

Class 1

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

Tuesday
2

Class 3

Large-Sample Confidence Interval for a Population Mean and Proportions. T-Statistics and small-sample confidence intervals for a population mean.

Wednesday
3

Class 2

Measures of Quality of Estimators. MLE/ MOM. Central Limit Theorem and sampling distribution.

Thursday
4

Class 4

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

Friday
5

Class 5

Comparing two populations means independent and paired sampling.

Monday
6

Class 6

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

Tuesday
7

Class 7

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

Wednesday
8

Class 8

Midterm Exam

Thursday
9

Class 9

Association between measurement variables. Correlation and regression. Simple Linear Regression.

Friday
10

Class 10

Regression diagnostic. Data transformation. Multiple linear regression.

Monday
11

Class 11

Logistic Regression

Tuesday
12

Class 12

ANOVA

Wednesday
13

Class 13

Non-Parametric tests Non-parametric test about the population mean, comparing two populations paired test, sign test, Non-Parametric test for correlation.

Thursday
14

Class 14

More on regression diagnostic for multiple linear regression. Model building. Review

Friday
15

Class 15

Final projects presentation

Prerequisites

Working knowledge of R/Python or SAS, basic calculus and probability theory.

Methodology

Combination of the theoretical and applied methodology.

Grading

The final grade will be composed of the following criteria:
20% - Four homework assignments
25% - In class Quizzes + class participation
25% - Midterm exam
30% - Final Project
Leah Isakov

Faculty

Leah Isakov

Global Head of BioStatistics, Data Management, Programming and Medical Writing at Seqirus

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. Leah has led NDA (New Drug Applications), PMA (Pre-Marketing Approvals) and BLA (Biologics License Applications) and have 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). The 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, Dr. Isakov strives to be at the forefront of management practice. She incorporates data-driven decision making and quantitative risk management, and focus on building internal capabilities along with external collaborations. Leah 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.

See full profile

Apply for this course

Snap up your chance to enroll before all spaces fill up.

Statistical Data Analysis

by Leah Isakov

Total hours

45 Hours

Dates

Apr 11 - Apr 29, 2022

Fee for single course

€1500

Fee for degree students

€750

How to secure your spot

Complete the form below to kickstart your application

Schedule your Harbour.Space interview

If successful, get ready to join us on campus

FAQ

Will I receive a certificate after completion?

Yes. Upon completion of the course, you will receive a certificate signed by the director of the program your course belonged to.

Do I need a visa?

This depends on your case. Please check with the Spanish or Thai consulate in your country of residence about visa requirements. We will do our part to provide you with the necessary documents, such as the Certificate of Enrollment.

Can I get a discount?

Yes. The easiest way to enroll in a course at a discounted price is to register for multiple courses. Registering for multiple courses will reduce the cost per individual course. Please ask the Admissions Office for more information about the other kinds of discounts we offer and what you can do to receive one.