oThe Statistics program aims to train highly skilled professionals in data processing and analysis to solve complex problems in various fields of knowledge. A strong scientific foundation is essential for success in this field and for providing effective solutions to multidisciplinary issues. We offer opportunities for participation in research projects and collaboration with the industry. Our primary mission is to educate excellent statistical engineers who can contribute to improving the world we live in. Our faculty is highly qualified with research and practical application experiences. Explore the power of numbers, pattern interpretation, and informed decision-making. Join us on this exciting journey into the world of Statistics!
* Undergraduate tuition/fees:
The Constitution of the Republic of Ecuador in its Article 356, among other principles, establishes that third-level public higher education will be tuition/fees free. Zero cost education is linked to the academic responsibility of the students.
Number of admitted students per academic year
Number of graduates per year
Number of enrolled students per academic year
Graphs show the figures in real time, at the time of the query
oThe Statistics program is designed for individuals who are critical, analytical, reflective, and passionate about numbers, logic, and problem-solving. You should have a predisposition to work in computer and programming environments.
- Analytical Skills: The ability to break down complex problems, identify patterns, and derive logical conclusions from data.
- Interest in Research: A desire to explore, analyze, and understand phenomena through statistical research.
- Mathematical Proficiency: This is essential for tackling the analytical challenges of statistics.
- Effective Communication: The ability to translate statistical results into understandable terms for those who are not experts in the field.
- Critical Thinking: The ability to question, evaluate, and improve statistical approaches, contributing to the continuous development of the discipline.
- Technological Curiosity: Interest and willingness to work with advanced tools and technologies for data analysis.
If you consider yourself a curious, analytical, and passionate individual who enjoys uncovering stories behind the numbers, Statistics could be your ideal path!
Educational Objectives:
1. To carry out analysis, research, and consulting activities in areas such as Quality, Industry, Market Research, Insurance, Data Mining, Survey and Census Design, Biology, Medicine, Environment, among others.
2. To hold positions in public or private companies in line with the ethical principles and leadership advocated by ESPOL University.
3. To prepare students for a fourth-level program where they can engage in scientific research using their statistical knowledge.
4. To be a key part of multidisciplinary research and development teams at the forefront of their fields of action.
Learning Outcomes:
1. The ability to identify, formulate, and solve broadly defined technical or scientific problems using knowledge of mathematics for reliable data-driven decision-making.
2. The ability to formulate or design a system, process, or procedure for representing phenomena and making informed decisions.
3. The ability to develop and conduct experiments, test hypotheses, analyze and interpret data, and use scientific judgment to draw conclusions.
4a. The ability to communicate effectively with a variety of audiences.
4b. The ability to communicate effectively with a variety of audiences in English.
5. The ability to understand ethical and professional responsibilities and the impact of technical or scientific solutions in global, economic, environmental, and social contexts.
6. The ability to function effectively in teams that set goals, plan tasks, meet deadlines, and analyze risks and uncertainties.
First Year
Descripción:
It is a core course for Engineering, Natural Sciences, Exact Sciences, and Social Sciences and Humanities, students. Topics, such as, topological notions, limits and continuity of real variable functions, derivatives and their applications, antiderivatives and integration techniques, and the definite integral with its applications, are examined. This course is aimed to the development of student’s skills and know-how in the derivation and integration processes, as a fundamental basis for the following upper level courses in its academic training process
Descripción:
In this course, students apply the Design Thinking methodology to identify, analyze real-life problems or needs, to design innovative solutions. Students work in multidisciplinary teams to present solution proposals that add value to customers/users from private companies, public organizations and non-profit organizations.
Descripción:
The course presents students with strategies to solve common problems in various professional fields through the design and implementation of solutions based on the use of a programming language. It covers the basic principles so that the student can read and write programs; emphasizing the design and analysis of algorithms. In addition, it introduces students to the use of development and debugging tools.
Descripción:
This is a professional training subject for the Statistics career in which fundamental concepts are introduced for development of critical and statistical thinking. An approach is made to the visualization of information through the analysis of contextualized data. The application of Statistics in different areas of interest is shown, with presentations by profesional guest speakers from different application areas, with a business approach and applied and theoretical research. This makes it possible to demonstrate the importance of Statistics in society and to show the proffesional future of some of its possible fields of action.
Descripción:
This basic and general education subject presents grammatical structures to produce a simple paragraph based on a writing program. Additionally, it allows the identification of a specific argument in oral and written communication. It also considers learners’ personal opinions about different topics related to social, academic, and professional aspects. It includes the necessary vocabulary to make comparisons between present and past, books or movies description, creation of simple students’ profile, opinions about inventions, formal apologies and tell past events.
Descripción:
Vector calculus is a course aimed at the basic training of professionals in the areas of Engineering, Exact Sciences and Natural Sciences who developed problem-solving and problem-solving skills in the n-dimensional context. For this purpose, the course consists of 5 general themes: three-dimensional analytic geometry and functions of several variables, differential calculus of scalar and vector fields, optimization of scalar functions of several variables, line integrals and multiple integration, surface integrals and theorems of the vector theory; being the main applications of this course: the optimization of functions of several variables applied to practical problems, the calculation of lengths, area, volumes, work and flow, using objects of the plane and space.
Descripción:
The Statistics I course allows students to improve their ability to analyze, synthesize and solve problems, by studying the statistical foundations for obtaining information from a set of data, starting from their information gathering, procedure, analysis and interpretation of the data obtained. Also, the concept of probability will be studied as a measure of uncertainty, mathematical models of discrete and continuous random variables will be analyzed univariate and multivariate, to finally consolidate the bases of inferential statistics
Descripción:
This transversal course is basic for students of Computing, Statistics, and Logistics and Transportation. It provides an introduction to the study of a branch of contemporary mathematics that develops reasoning and the application of mathematics to solve problems discreet in nature. It includes the study of mathematical logic, proofs, sets, counting techniques, whole number structures, graphs and trees. Algorithms that allow obtaining results in discrete structures and grammars are also studied, an environment that the engineers that we train will surely face.
Descripción:
This subject of basic formation and general education presents the grammatical structures for the production of an academic paragraph, through the development of the writing program in a transversal way. In addition, it allows the identification of specific arguments in oral and written communication, considering the production of one's own criteria on different topics of a social, academic or professional nature. The necessary vocabulary is also applied to refer to the different forms of communication, share work experiences and the use of digitl technology, tell short stories about interpersoanl relationship and personalities, and comment on the future of the environment.
Descripción:
This is a basic training course for students of Statistics and Mathematics, which provides theory and procedures that are useful when posing, interpreting and solving problems, both in their curricular and professional activities. It begins by introducing the notions of vector spaces and linear transformations. Following this, vector spaces with inner product and their geometric interpretation are studied. Then, the fundamentals of diagonalization are given, both of matrices and linear operators. Finally, all this is applied to the solution of problems modelled by bilinear forms.
Second Year
Descripción:
In this subject, we study the development of the academic prosumer profile of the students, which should be consolidated throughout each individual's life, based on the processing of complex, holistic, and critical thinking. We aim to foster understanding and the production of academic knowledge through rigorous analysis of realities and readings from various academic/scientific sources.
Descripción:
In this basic training course in the area of statistics, the properties of real numbers are studied, such as: the axiom of the supreme and the Archimedean property, in order to develop the contents of the topology of metric spaces, which in turn will allow the definition of the Borellian algebras, necessary in the construction of Lebesgue's theory of measurement. Then, from the Lebesgue measure, the Lebesgue integral and its properties are studied. The following is a discussion of probability theory using the results of measurement theory. Finally, the convergence of random variables is studied.
Descripción:
It is a basic training subject for students from the undergraduate programs in Statistics and Mathematics. Statistical theory is studied that allows the student to analyze in a scientific and deep manner the procedures of Descriptive and Inferential Statistics, emphasizing the desirable characteristics of the obtained estimators, allowing him to apply this knowledge in the most effective way to research in his own area or cross-sectional embodiment. The connection of probability as a measure of uncertainty with the point estimators, the construction of confidence intervals and the theory of hypothesis testing is established. The emphasis of the course, more than numerical, is analytical, emphasizing conceptualization and demonstrations, looking after the applications. The sample sizes are in general finite but asymptotic approximations of the estimators and inference for large samples are also analyzed.
Descripción:
This core subject of basic formation in the engineering degrees begins with the study of convergence criteria for numerical series and power series, providing methods for obtaining the latter. Next, analytical solving methods of ordinary differential equations of first and superior order are examined, including solutions in power series. Then, the Laplace transform is defined and used as a solving method of linear ordinary differential equations. As a final part, solving methods for solving linear ordinary differential equation systems are studied. The subject examines application problems of engineering and sciences modelled by ordinary differential equations and series and includes the use of software in a part of each practical session.
Descripción:
Numerical Optimization is a professional subject aimed at students of Logistics and Transportation, and Statistics. It deals with optimization problems through the use of numerical methods that allow to find the stationary points in an approximate way, that is, a solution that meets a minimum tolerance level. The course begins with a review of the fundamentals of numerical analysis and how through it, we can solve: systems of linear and non-linear equations, and then apply these concepts in solving optimization problems without restrictions.
Descripción:
This subject of basic instruction and general education presents grammatical topics for the elaboration of an outline and a structured composition, through the development of the writing program in a transversal way. In addition, it allows the identification of arguments in oral and written communication on contemporary and academic topics. Additionally, appropriate vocabulary is applied to discuss issues related to different cultures, places where we live, everyday news, entertainment media, and past and future opportunities.
Descripción:
This course contributes to the basic training of Statistics and Audit and Management Control students, with regard to determining the size of a sample, its capture and selection of data. The first part consists of providing the basic introductory concepts to sampling, the techniques for the development of a data capture instrument such as the questionnaire, as well as all the factors that surround its design, structure, characteristics and restrictions.The second part consists of providing the necessary theory to be able, given a set of data, generally population-based, to select part of them, using various techniques, such as simple random sampling, stratified, cluster and systematic random sampling, non-probabilistic sampling and auxiliary techniques of sampling.
Descripción:
This professional training course in the area of statistics reviews the decomposition of single values and single and multiple correlations. Subsequently, the different multivariate statistical models are analyzed through practice with the use of specialized statistical software of free access, to detect the variations of the different individuals and variables, as well as their associations.
Descripción:
This professional training course addresses the basic fundamentals of quality and its philosophy, as well as the concepts and different methodologies of statistical process control applied to quality management and improvement. In this context, the main techniques offered by statistics for process control are studied, which allow the implementation of a quality management system, also methodologies associated with the improvement of production and service processes are discussed.
Descripción:
This professional training subject provides the student with the necessary knowledge to statistically treat categorical variables, which are immersed in many situations of daily life. The different scales of the categorical variables are distinguished as data on a nominal scale and data on an ordinal scale. Then, the contingency tables and the inferences that can be made with them are studied. Finally, generalized linear models are presented, specifically binomial, multinomial and "Poisson" logistic regressions.
Descripción:
This course focuses on the professional development of the student. It covers the linear regression model to describe, predict or infer about relationships between one or more explanatory variables and a quantitative response variable. During this course it is shown the equivalence between the linear regression model and the analysis of variance model (ANOVA model). Moreover, this course provides the foundations for the statistical and mathematical understanding of the structure of a statistical model. Practical classes are given in the lab and are based on the implementation of statistical techniques learned during the theoretical classes in real data using a statistical software.
Descripción:
This subject of basic formation and general education, presents the grammar structures to produce a persuasive essay, through the transversal development of the writing programme. In addition, it allows students to identify specific arguments in the oral and written communication, as well as, to express their own opinions about different topics of social, academic, or professional fields. It also includes the necessary vocabulary to stablish a conversation, narrate situations of their environment, activities to reach their goals, analyze cause and effect and personal and professional opportunities.
Third Year
Descripción:
This subject is a professional training which teaches in depth topics as linear regression model using observational and experimental data. Also, it includes advance experimental designs topics and multifactorial and repeated measures designs. This subject includes the use of statistical models for the correct and precise estimation of the effects of interest under these designs. It focuses in the treatment of one or more qualitative variables (or factors) in a model that seeks to explain a quantitative response variable. Furthermore, this subject study inferential procedures to estimate the effects of these qualitative variables of interest, where the levels can be fixed or random. It also addresses the formulation of statistical models for the analysis of designs with repeated measures (longitudinal data). Finally, it reviews non-linear models of population growth over time. The practical classes are given in the laboratory and are based on the implementation of the models learned with real data using statistical software.
Descripción:
This professional training course has a statistical approach powerful that introduces the Bayesian statistic be comparing it with the classical approach and focusing on modeling, estimation and interpretation of results that allows complex problems to be addressed in a way conceptually simple and unified; thus contributing to contact with a more advanced theory for the development of analytical and abstraction skills.
Descripción:
This subject of professional training in the area of statistics, emphasizes the knowledge to extract data from different sources as a preliminary part. Then, it introduces data engineering and the treatment of theoretical models, presents data collection and integration methods in preparation for statistical analysis, and finally summarizes the above topics through an implementation project.
Descripción:
This transversal training course for all students of the institution has five chapters. It introduces the key principles of sustainability and the path to sustainable development. Addresses ecological principles by deepen into biodiversity, ecosystems, human population and ecosystem services. Study the fundamentals of renewable and non-renewable resources as well as the alternatives for sustainable use. Analyzes environmental quality specifically in the air, water and soil components, delving into issues such as climate change, eutrophication and deforestation. Finally, it emphasizes on the economic axis with topics such as circular economy and on the social axis on topics such as governance and urban planning.
Descripción:
This transversal course addresses the conditions required to innovate and the process associated with developing an innovation from an entrepreneurial point of view. Subsequently, topics such as the identification of opportunities, value creation, and prototyping and validation of products/services proposals are reviewed, as well as the elements of the business model and financial considerations that are essential for the feasibility and adoption of an innovation. Finally, entrepreneurial competences and process associated with the development and adoption of an innovation are studied.
Descripción:
This is a professional course, which aims to provide students with the necessary knowledge to delineate experiments, whether exploratory or confirmatory. The course is focused on support for decision making using mathematical models to represent experiments in their design phase. Classical designs such as completely randomized, factorial arrangements and blocks are studied; in addition, it presents optimal designs, and response surfaces. The interpretation of the results obtained with statistical support in connection with real problems for decision making is emphasized.
Descripción:
The course is professional training and is aimed at Statistics and Logistics and Transportation students. It is aimed at learning the main mathematical - statistical models that allow studying random processes that maintain a periodic occurrence over time. It focuses on the identification of the components that make up the data series, the selection and application of the best model that describes their natural behavior for subsequent obtaining of forecasts.
Descripción:
This subject of professional training in the area of statistics, examines the essential computational problems behind statistical methods, also dealing with the application of numerical tools. It explains the numerical integration and the generation of random numbers, in a unified way, and reflects complementary views of the Monte Carlo methods.
Fourth Year
Descripción:
This professional training subject in the area of statistics provides basic techniques for the descriptive and inferential analysis of data taken in different geographical locations such as: mineral deposits, oil reservoirs, agricultural plantations and geotechnical characterizations. The general concepts of classical statistics and geostatistics are reviewed, starting with the exploratory analysis of data. Regionalized random variables, variograms and semivariograms, stationarity, Kriging interpolation methods and finally simulation are addressed.
Descripción:
This is an advanced course that focuses on professional development for students of the degree of statistics. This course addresses statistical techniques that are robust against parametric assumptions in the data, as well as methodologies for estimation that are resistant to outliers. This course is divided in two parts. In the first part, it reviews non-parametric techniques in the context of hypothesis testing and regression analysis. In the second part, it examines techniques that are resistant to outliers in the context of estimation of location and scatter as well as in the context of regression analysis. Moreover, this course reviews rules for outlier detection in univariate and multivariate settings based on robust fits. Practical classes are given in the lab and are based on the implementation of statistical techniques learned during the theoretical classes in real data using a statistical software.
Descripción:
This professional training course in the area of statistics reviews single and multiple linear stochastic models. Subsequently, the different models of supervised and unsupervised learning are analyzed from the perspective of modern statistical learning theory, through practice with the use of specialized statistical software, to make statistical forecasts and detect intrinsic structures from a data matrix.
Descripción:
The subject is aimed at students at level 400-1 of the Statistics career of the FCNM. The purpose of this course is that the students acquire the ability to recognize their strengths and weaknesses for the benefit of their personal, academic and work development through the knowledge of the predominant type of intelligence, the application of a decision-making process for the elaboration of a matrix that allows them in turn to become people with high command of the effective communication process before an audience.
Descripción:
This professional training course in the area of statistics, aims to address the essential contents of web scrapping, NoSQL databases, sentiment analysis, text analysis and social network analysis to discover new knowledge, from statistical analysis to data that do not follow an identified internal structure.
Descripción:
In this end-of-career course, the student carries out a project where the application of the profiles declared in the career is evidenced, developing processes of creativity, organization and relevance that involve them in a professional design experience. In the first part of the course, the needs of the client/user/public are identified, the problem/opportunity is defined, the data is collected and the critical factors are analyzed. In the second part, alternative solutions are created framed in the regulations and restrictions of each user. It concludes with the design and/or the implementation of feasible solutions or the elaboration of prototypes; in addition to the validation of the results and control plans.
Additional
ARTS, SPORTS AND LANGUAGES ELECTIVE COURSES
1 credits - 1.9 ECTS
HUMANITIES ELECTIVE COURSES
1 credits - 1.9 ECTS
SELECTED ELECTIVE COURSE
3 credits - 5.8 ECTS
SELECTED ELECTIVE COURSE
3 credits - 5.8 ECTS
Upon completing the four years of the Statistics Engineering program at the Faculty of Natural Sciences and Mathematics, graduates possess a strong and versatile professional profile. We are committed to developing professionals capable of tackling complex challenges with advanced statistical skills. Here is the professional profile you can achieve:
1. Data Analysis Expertise: Mastery in using statistical tools and specialized software to analyze complex data sets and extract valuable insights.
2. Informed Decision-Making: The ability to provide evidence-based guidance through the interpretation and effective communication of statistical results.
3. Statistical Modeling: The skill to develop and apply advanced statistical models to predict trends, identify patterns, and support strategic decision-making.
4. Applied Research: Experience in applying statistical methodologies in research projects, contributing to the advancement of knowledge in various fields.
5. Communication: The ability to communicate findings clearly and comprehensibly to both technical and non-technical audiences, facilitating interdisciplinary collaboration.
6. Business Problem Solving: Application of statistical approaches to solve business problems and improve processes, optimizing efficiency and decision-making.
7. Ethics and Professional Responsibility: Commitment to ethical standards in data collection, analysis, and presentation, ensuring integrity at all stages of the process.
8. Interdisciplinary Collaboration: The ability to work in multidisciplinary teams, bringing valuable statistical insights to projects in various application areas.
Upon graduation, you will be prepared to tackle analytical challenges in any industry and make a significant contribution to the development and advancement of statistics and applied research. Get ready for an exciting and highly promising career!
Occupational Profile
The Statistician Engineer is qualified to design and lead data acquisition processes, analyze and interpret qualitative and quantitative information in small or large volumes, using statistical models that enable decision-making under conditions of uncertainty in various fields of social, scientific, and productive activities. They collaborate with multidisciplinary research and development teams in designing experiments and analyzing their results.
In an increasingly data-driven world, the ability to translate information into meaningful knowledge that can be utilized by companies and organizations is one of the most valuable skills that a Statistician Engineer possesses.
Some common positions include:
-Data analyst
-Data scientist
-Actuary
-Financial risk specialist
-Investment analyst
-Business intelligence specialist
-Market researcher
Some of the organizations and industries that frequently seek Statistician Engineers are involved in:
-Engineering
-Finance
-Insurance
-Public health
-Marketing
-Education
-Medicine
-Artificial intelligence
-Agriculture
To obtain the title of Statistics Engineer, the following requirements must be met:
- Having passed a minimum of 43 credits in Professional Formation.
- Having passed a minimum of 54 credits in Basic Formation.
- Having passed a minimum of 2 credits in Complementary Formation.
- Having passed a minimum of 6 credits in Itinerary Formation.
- Completion of a minimum of 336 hours of pre-professional practice, divided into 96 hours of community practice and 240 hours of pre-professional practice in the industry.
- Approval of the graduation process, equivalent to 8 credits.
The Capstone Project is a culminating requirement for graduation. These projects provide students with the experience of applying acquired knowledge and skills to the needs of society, with a focus on sustainability.
The IDEAR Fair showcases all Capstone projects, offering students a valuable opportunity to showcase their work and hone soft skills such as communication and teamwork. It is also a space for students to network with potential clients and future employers.
Explore all of the Capstone projects completed by the Statistics program.
DID YOU KNOW?
Did you know that statistics is applied to almost everything we know? That's where the importance of this science and data scientists lies.
