Escuela Superior Politécnica del Litoral

What you'll study

This master's combines rigorous statistical theory with hands-on computational and applied work. Core topics typically include probability theory and statistical inference, multivariate analysis, regression and generalized linear models, time series and longitudinal data analysis, design of experiments and sampling methodology. Applied and computational modules cover statistical computing (R and Python), simulation methods, resampling and bootstrap techniques, Bayesian statistics, and machine learning methods for structured and unstructured data.

The programme is commonly structured as a sequence of taught modules followed by a research thesis or a practicum project with an external partner. Students can choose elective streams or specialised seminars in areas such as biostatistics, environmental and spatial statistics, econometrics, industrial statistics and quality control, big data analytics, or survey methodology. Emphasis is placed on data analysis projects using real datasets, reproducible workflows, and the presentation of results for technical and non-technical audiences.

Entry requirements

• A recognised undergraduate degree in statistics, mathematics, computer science, engineering, economics or a related quantitative discipline. Candidates with substantial relevant professional experience may also be considered.
• Demonstrated competence in calculus and linear algebra; prior coursework in probability, introductory statistics and computing is normally expected.
• Application materials usually include an academic transcript, a curriculum vitae, a statement of purpose outlining research or professional goals, and one or more academic or professional references.
• Proficiency in the language of instruction is required; the programme is primarily delivered in Spanish, and evidence of language ability may be requested. Familiarity with programming in R or Python is strongly recommended prior to entry.
• Some applicants may be invited to an interview or to submit a short quantitative assessment as part of the selection process.

Career prospects

Graduates from the Master of Applied Statistics are prepared for roles that require advanced data analysis, statistical modelling and decision support. Common career paths include statistician or data scientist positions in healthcare and public health agencies, environmental and natural resource management organisations, manufacturing and quality assurance in industry, financial services, market research firms and government statistical offices.

Other options include research and teaching in universities or research institutes, specialist roles in biostatistics or epidemiology, and consulting positions where robust experimental design and inference are required. The combination of theoretical grounding and computational skills also positions graduates for further doctoral study in statistics, data science or applied disciplines.

Why study at Escuela Superior Politécnica del Litoral

• ESPOL is a leading technical university in Ecuador with a strong emphasis on applied science and engineering, offering a graduate environment closely connected to regional industry and public institutions.
• The university provides access to computing facilities and research groups engaged in applied mathematics, statistics and data science; students benefit from opportunities for collaborative projects with industry partners and public-sector agencies in Ecuador and the region.
• Faculty members bring a mix of academic research and applied experience, enabling supervision of thesis projects across domains such as environmental monitoring, public health, industrial quality control and economic statistics.
• Located in Guayaquil, ESPOL offers proximity to a variety of private and public organisations where students can pursue internships, practicum projects and applied research placements, enhancing employability and real-world experience.