Applied Statistics
Faculty
Leah Isakov
Global Head of BioStatistics, Data Management, Programming and Medical Writing at Seqirus
Course length
Duration
Total hours
Credits
Language
Course type
Fee for single course
Fee for degree students
Skills you’ll learn
Overview
Introductory one-module applied statistical methods course that emphasize inference and sound decision-making through extensive coverage of data collection and analysis. This course gives students the skills to perform, present, and interpret basic statistical analyses. Topics include confidence intervals and hypothesis testing; sample size and power considerations; analysis of variance and multiple comparisons; correlation and regression; multiple regression and statistical control of confounding.
Learning highlights
- Develop statistical thinking
- Interpret and critique statistical methods and results encountered in real data applications
- Design, conduct, interpret, and present basic statistical analyses. After completing this course, students will understand the statistical language, notation and common methods. Students will have an understanding of study design, and be able to identify an appropriate statistical analysis for a study. Students will be able to interpret results of statistical analyses presented in literature, and will be able to evaluate the methodological strength of a published paper with respect to the study design and appropriateness of statistical methods.
Course outline
4 classes
Descriptive Statistics
Class Objectives: Distinguish measurement, categorical and ordinal data; create and interpret frequency tables, proportions and percentages to describe a research sample on categorical data; create and interpret frequency distributions and histograms to describe a research sample on measurement data; calculate and interpret means and standard deviations to describe a research sample on measurement data.
The Normal Distribution and Sampling Distributions
Class Objectives: Determine when the normal model is appropriate to describe data; apply the characteristics of the normal model to describe the distribution of a measurement variable; apply the standard normal distribution, using statistical tables and Excel, to describe the distribution of a measurement variable.
Estimation, sampling distributions, Introduction to confidence intervals
Class Objectives: Understand sampling distributions; distinguish between the standard deviation and the standard error for a measurement variable; calculate and interpret a confidence interval for a mean; determine means, standard deviations, and confidence intervals using statistical computing packages.
Introduction to hypothesis testing
Class Objectives: Understand the logic and notation of hypothesis testing, including the null and alternative hypothesis, Type I and Type II errors, significance levels and p-values, significant and non-significant results, one and two tailed tests; carry out and interpret a one-sample test for a mean; understand the relationship between a t-test and a confidence interval; conduct and interpret a one-sample t-test using statistical packages.
Prerequisites
This course is one of three in a wholistic series.
Students that have already taken MSL-111 and those with prior experience with HTML, CSS, and Javascript building simple web pages will be good candidates for this module.
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 profileApply for this course
Applied Statistics
by Leah Isakov
Total hours
45 Hours
Dates
Jun 12 - Jun 30, 2017
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.