Statistical Engineering

Career Objectives

The mathematical study of processes which response is not possible to determine accurately, or events in which there is no certainty that they will occur; in order to help make decisions about them.

Professional Profile

-Professional in mathematics qualified in data analysis, the use of *statistical procedures and computer tool to efficiently support decision making under uncertainty conditions, in different fields of the social, economic and productive activity.

He works with professionals from other areas, related to the management of large data volumes, in order to explain, solve and/or predict a phenomenon.

He applies statistics to scientific, industrial or social problems. For that, it is necessary to collect and record data and obtain their patterns in order to describe their characteristics and build a *statistical model, which will be the information base for decision making.

Specific tasks or activities carried out in the profession

He designs, plans and organizes censuses and statistical surveys.

In censuses, he operates statistically on the total population, meanwhile in statistical surveys, he operate on a *sample of the population from which he makes estimates regarding the population, showing margins of error of said estimates; this way he obtains very similar results to those he would get from a study of the entire population, but at much lower cost.

In the statistical study, he performs the following process:

Problem Statement

He lays out the problem to be studied, setting the objectives or questions, such as: which will be the mean (average) of this population with respect to that characteristic? Example: what will be the mean of the young population in relation to drug use?, Is there any relationship between this and that variable? Example: What relationship will there be between the economic income level and the level of drug use in the youth population?

Besides, he analyzes the means available to carry out this research and the procedure to be followed.


He determines and administers the obtaining of a *sample of data from the *population, so that this sample is *representative of said population. For that, he must apply *sampling or data collection techniques.

Example: A representative group of the youth population is consulted regarding their drug use.

Data Processing

In this stage, the sample is filtered by deleting possible errors; the data are analyzed and summarized.

Data can be summarized numerically or graphically, from which statistical *parameters are obtained. One of these parameters is the arithmetic mean (average) and the *standard deviation or degree of dispersion.

Example: a sample with x average frequency of drug use; its dispersion is analyzed, that is, to know if this average is produced because most have that consumption of consumption (low dispersion) or this average occurs because a few have a very high frequency of consumption and the rest is very low (high dispersion).

Basically, it is about a series of measures of central tendency, to see how data is grouped or scattered around a central value.

From this statistical study of data, information of the characteristic studied is obtained, such as: its existence, location, distribution and value.

He interprets (the meaning) the statistical data and prepare them for publication.

Estimation of Population Parameters

He studies the *probability of occurrence (frequency in which the fact is repeated) of the *sample information and, based on that, he creates models (*statistical models) of the behavior of the event that is being studied, showing the probability that this event occurs in the whole population.

(Example: probability of occurrence of drug use in the entire youth population).

Based on the *statistical model, he *infers regarding the population, providing the margin of error of those inferences.

For instance: from the study, he concludes which fraction of young people in the youth population use drugs and the margin of error of this estimation.

He investigates, perfects and develops statistical *theories, *methods and *techniques.

He advises on various data collection methods.

He advises on statistical *methods and *techniques.

He creates his own instruments or adopts the existing ones to face the problems he addresses.

He advises on the study of information in fields and disciplines such as economics and management, medicine and other fields of the exact, biological, and natural or social science.

He leads multidisciplinary teams responsible for decision making in conditions of uncertainty and risk such as opinion and market *surveys, production efficiency studies, risk analysis in the insurance area.

In the practice of his profession, he uses modern *calculation and telecommunication techniques.

Occupational Field

-Large trading companies

-Public services

-Government offices

-Financial companies

-Agricultural, forest, fishing, chemical, metalworking, oil and mining industries.

-Insurance companies

-Pension Funds Administrations


-Market Research Departments

-Health Services

-Research Institutes


-Consulting firms


Estimated time of College years

5 years

Main courses considered in the syllabus

Professional Training Courses

*Mathematics (8 semesters)

*Statistics and *Probability (2 semesters)

*Sampling (2 semesters)

*Statistical Inference

*Design of Experiments

-Computing and Survey Design

-Management (2 semesters)

*Economics (2 semesters)

*IT (4 semesters)

*Physics (2 semesters)

*Operation Research

*Project Evaluation

*Research Methodology

Complementary Training Courses

Expression Techniques

*English (5 semesters)


Statistics applied in areas of:

Industrial Production



Urban Planning


Social Science

Scientific Research

Among others

Vocation, Skills and Interests required in the candidate to this career


-Interest in numbers

-Motivation for computer management

-Interest in the development of calculation methods

*Analytical and *deductive mentality

-Tendency to quantify facts

-Interest in meticulous and extensive work

-Satisfaction to be able to solve a mathematical problem

-Natural and frequent tendency to relate the facts numerically

-Appreciation for accuracy, preciseness and exactness that mathematics provides

-Curiosity for sciences

-Interest in dealing with industrial, business or scientific problems through mathematics

-Tendency to the use of patters, schematizations and graphs when studying or analyzing something.


-Good level of mathematical reasoning

-Ability to follow a mathematical reasoning and retain it mentally while the reason lasts

-Skill in mathematical and numerical operations

-Understanding of Sciences, in general

-*Analysis capacity to diagnose and solve problems

-*Abstraction ability

-*Deduction and *synthesis capability

-Ease to take a real situation to a scheme


Contribute to social and productive systems through mathematical rigor and numerical management.

Or any specific dream or longing which feels involved or oriented towards this direction.

Candidate Personality

Tidy and organized in his chore



Practical and specific

Team work ability

Work Scope


Office Environment

Computer Management

Related Careers

Mathematical Science, Engineering Mathematics, Technology in Statistics, Economics

*Glossary of Terms

*Abstraction: Isolate mentally or considering the attribute of an object separately. Also, to consider an object in its essence; For instance: mathematics is a symbolic language of the behavior of physical phenomena or relations between entities. All of them are abstractions of reality, expressed as symbols.

*Linear Algebra: Part of mathematics which works based on vectors.

*Algorithms: Sequences of steps to be followed by the program.

*Analysis: Method that starts by focusing the whole to end up separating it into the basic parts to see the relation between its parts.

*Numerical Analysis: Numerical analysis is the branch of mathematics that is charge of designing *algorithms that, through numbers and simple mathematical rules, simulate more complex mathematical processes, applied to processes of the real world.

*Database: It is a set of programs that manage a stock of data that is organized in a way that is easy to access, store and update them (These programs act as a librarian who manages a stock of books).

The subject studies the creation of a database as well as the functions that operate in it.

*Calculus, *Differential Equations: Part of mathematics that takes charge of the dynamic factors of reality, dealing with concepts like derivatives and antiderivatives (or integral), where the derivative of a function gives the notion of how quickly a function grows (or decreases) at a certain point.

*Calculation: Procedure that determines the value of a quantity through mathematical operations.

*Deduction: From a general principle known, conclude regarding a particular case.

*Standard Deviation: It is the measure of dispersion of data in its distribution with respect to the arithmetic mean (average).

*Design of Experiments (Course): Models from “Design of Experiments” are statistic models which objective is to find out if certain factors influence a variable of our interest, and if there is an influence to quantify it.

Example: The study of the performance of a specific type of machine (units produced per day).

It is desired to study the influence of the worker who handles it and the brand of the machine in the production performance.

*Economics (Course): Science to which subject of study is the social organization of the economic activity, in which, through statistic and mathematical techniques, tries to quantify the main existing relations between several variables in an economic model.

The subject describe the basic concepts of the *macroeconomic and *microeconomic theory and shows applications in the industry.

*Project Evaluation (Course): Useful concepts and methods in the analysis of development alternatives of a project, in relation to its costs, using as requirement economic feasibility (that it is economically possible).

*Statistics (Course): Study of techniques of data collection, presentation, treatment and analysis, in order to summarize and describe the characteristics of a data set. To know a data set in detail, it is not enough to know the measures of central tendency, but we also need to know the deviation (*Measure of Dispersion) which represent data in its distribution with regard to its *arithmetic mean (average), in order to have a vision of them more in line with reality when describing and interpreting them.

*Data Structure: The most appropriate order of data with which the *computer programs will work.

*Physics (Course): Subject that establishes foundations of Mechanics, a field of knowledge necessary for the study and understanding of a wide diversity of natural phenomena.

In the subject, the principles and laws of electromagnetism are addressed.

Problems that involve the concepts and laws of electricity and magnetism are solved.

Basic concepts of mechanics of a particle and the statistical study of the behavior of a particle system are addressed, with emphasis on the mathematical aspects involved.

*Analytic Geometry: It is the one that deals with geometric problems through graphs with the use of coordinates. This is achieved by transforming them into algebraic expressions.

*Statistical Inference (Course): Methods that make possible the estimation of a characteristic of a population, or making a decision regarding a population, based on the result of the study of a sample, as well as the use of computer programs referred to these topics.

*Infer: Conclude.

*IT: Study of information.

*IT (Course): It studies computer tools such as *Operating system, *Word processor and *Spreadsheets *Software. *Programming tools. –Problem solving through algorithms. *Data Structure concepts. –Know conceptually the design and modeling of *databases. –Introduction to Structured *programming, among other topics.

*English (Course): Vocabulary, grammar and syntax to read and understand texts in that language in this area of competence at intermediate level.

*Operations Research (Course): It concentrates practical applications of decision making in organizations.

*Microeconomics: Economic analysis related to the individual behavior of consumers, trades, producers, companies and industries, etc.

*Macroeconomics: Regarding the production and consumption of the wealth of a country and the problems related to the level of employment.

*Marketing: Commercialization.

*Mathematics (Course): It includes topics of Algebra, *Analytic Geometry, *Linear Algebra, *Calculus, *Differential Equations, *Numerical Analysis, among others.

*Measures of Dispersion: They are numbers that indicate dispersion; they show to what extent the individual values ​​of a data set differ from each other, and differ from their average.

*Research Methodology (Course): Methods to indentify the stages and the importance of the scientific method and apply it to the resolution of problems.

*Methods: Procedures, ways of doing something.

*Statistical Models: It is a mathematical model of the behavior of the event that is being studied, indicating the probability that this event will occur in the population.

*Sample: It is a chosen subset of the population. Due to material reasons, human resources, physical impossibility and ultimately costs, you can’t conduct a survey to the entire population under study, so a part of it is consulted, which is a sample of that population.

*Sampling: It is the technique for the selection of a sample of the population, so that it is representative of said population and therefore valid, and an adequate study can be carried out.

*Sampling (Course): The basic elements of the theory of efficient data collection and its implications for the quality of information are studied.

*Statistical Parameter: A parameter is a numerical value representative of a population, such as the proportion of individuals that have a certain characteristic.

*Spreadsheet: It is an electronic calculation sheet.

*Population: It is the set of all the possible elements that intervene in a study or experiment, of which we want to know some characteristics.

*Probability: Study of the frequency with which an event occurs or a result (or set of results) is obtained when carrying out a random experiment, of which all possible results are known under sufficiently stable conditions.

*Probability (Course): Fundamental concepts of the probability theory and its relation with mathematical models.

*Word Processor: Program intended to the creation or modification of written documents by means of a computer.

It represents a modern alternative to the ancient typewriter, but much more powerful and versatile than this one.

*Programming: Study of the design and development of programs firstly in an algorithmic language (sequences of steps to be followed by the program) to later translate it into a *computer language.

*Structured Programming: It is a way to write computer programs in a clear way, where the structure of the program is arranged in modules in a hierarchical way.

*Representative of the population: That is, a very small number of queries; to young people of different social classes, different ages and sex, etc.

*Operating System: Set of programs devoted to the internal functioning of the computer and interpretation of the commands given by the user.

*Synthesis: Gather isolated parts or facts in a unifying idea. -Summary.

*Software: General term that is designated to different types of computer programs.

*Statistical Techniques: Statistical tools for analysis.

*Theory: Proposition or attempt to explain a phenomenon at the beginning.