You will master the techniques used in business economics and statistics that are fundamental to consolidate the growth of any organization” 

Why Study at TECH?

TECH is the world's largest 100% online business school. It is an elite business school, with a model based on the highest academic standards. A world-class centre for intensive managerial skills training.   

TECH is a university at the forefront of technology, and puts all its resources at the student's disposal to help them achieve entrepreneurial success"

At TECH Global University

Innovation

The university offers an online learning model that combines the latest educational technology with the most rigorous teaching methods. A unique method with the highest international recognition that will provide students with the keys to develop in a rapidly-evolving world, where innovation must be every entrepreneur’s focus.

"Microsoft Europe Success Story", for integrating the innovative, interactive multi-video system.  

The Highest Standards

Admissions criteria at TECH are not economic. Students don't need to make a large investment to study at this university. However, in order to obtain a qualification from TECH, the student's intelligence and ability will be tested to their limits. The institution's academic standards are exceptionally high...  

95% of TECH students successfully complete their studies.

Networking

Professionals from countries all over the world attend TECH, allowing students to establish a large network of contacts that may prove useful to them in the future.  

100,000+ executives trained each year, 200+ different nationalities.

Empowerment

Students will grow hand in hand with the best companies and highly regarded and influential professionals. TECH has developed strategic partnerships and a valuable network of contacts with major economic players in 7 continents.  

500+ collaborative agreements with leading companies.

Talent

This program is a unique initiative to allow students to showcase their talent in the business world. An opportunity that will allow them to voice their concerns and share their business vision. 

After completing this program, TECH helps students show the world their talent. 

Multicultural Context

While studying at TECH, students will enjoy a unique experience. Study in a multicultural context. In a program with a global vision, through which students can learn about the operating methods in different parts of the world, and gather the latest information that best adapts to their business idea. 

TECH students represent more than 200 different nationalities.   

Learn with the best

In the classroom, TECH teaching staff discuss how they have achieved success in their companies, working in a real, lively, and dynamic context. Teachers who are fully committed to offering a quality specialization that will allow students to advance in their career and stand out in the business world. 

Teachers representing 20 different nationalities. 

TECH strives for excellence and, to this end, boasts a series of characteristics that make this university unique:   

Analysis

TECH explores the student’s critical side, their ability to question things, their problem-solving skills, as well as their interpersonal skills.  

Academic Excellence

TECH offers students the best online learning methodology. The university combines the Relearning method (a postgraduate learning methodology with the highest international rating) with the Case Study. A complex balance between tradition and state-of-the-art, within the context of the most demanding academic itinerary.  

TECH is the world’s largest online university. It currently boasts a portfolio of more than 10,000 university postgraduate programs. And in today's new economy, volume + technology = a ground-breaking price. This way, TECH ensures that studying is not as expensive for students as it would be at another university.  

At TECH, you will have access to the most rigorous and up-to-date case studies in the academic community”

The syllabus for this Postgraduate diploma has been designed by a team of experts in the field to respond specifically to the needs of Business Science professionals. This compendium of content has also been created with a focus on applied learning, which will allow professionals to successfully intervene by means of a broad vision of real environments in the profession. 

This curriculum will lead you to job success through comprehensive learning about Business Statistics” 

Syllabus

The TECH Global University Postgraduate diploma in Business Statistics is an intensive program that prepares students to face business challenges and decisions at a global scale. The content is designed to develop managerial skills, allowing for more thorough decision making in uncertain environments. 

Over 600 hours, students will analyze a multitude of practical cases to gain a deep and complete understanding that will be very useful in professional practice. It is, therefore, an authentic immersion in real business situations. 

This Postgraduate diploma deals with the different areas of a company in depth, and it is designed for managers to understand business management from a strategic, international and innovative perspective. 

A plan designed for students focused on their professional development, which prepares them for excellence in business management and administration. A program that understands your needs and those of your company and, therefore, offers innovative content based on the latest trends, supported by the best educational methodology and an exceptional teaching staff, which will provide you with the necessary skills to creatively and efficiently resolve critical situations. 

This Postgraduate diploma takes place over six months completely online.

Module 1. Business Mathematics
Module 2. Statistics I
Module 3. Statistics II
Module 4. Econometrics

Where, When and How is it Taught? 

TECH offers the possibility of developing this Postgraduate diploma in Business Statistics completely online. Over the course of 6 months, you will be able to access all the contents of this program at any time, allowing you to self-manage your study time.

Module 1. Business Mathematics

1.1. Basic Elements of Linear and Matrix Algebra

1.1.1. The Vector Space of IRn, Functions and Variables

1.1.1.1. Graphical Representation of Sets in R
1.1.1.2. Basic Concepts of Functions of Several Real Variables. Operations with Functions
1.1.1.3. Function Types
1.1.1.4. Weierstrass Theorem

1.1.2. Optimization with Inequality Constraints

1.1.2.1. Two-Variable Graphical Method

1.1.3. Function Types

1.1.3.1. Separate Variables
1.1.3.2. Polynomial Variables
1.1.3.3. Rational Variables
1.1.3.4. Quadratic Forms

1.2. Matrices: Types, Concepts and Operations

1.2.1. Basic Definitions

1.2.1.1. Matrix of Order m by n
1.2.1.2. Square Matrices
1.2.1.3. Identity Matrix

1.2.2. Matrix Operations

1.2.2.1. Matrix Addition
1.2.2.2. Scalar Multiplication
1.2.2.3. Matrix Multiplication

1.3. Transpose

1.3.1. Diagonalizable Matrix
1.3.2. Transpose Properties

1.3.2.1. Involution

1.4. Determinants: Calculation and Definition

1.4.1. The Concept of Determinants

1.4.1.1. Determinant Definition
1.4.1.2. Square Matrix of Order 2.3 and Greater Than 3

1.4.2. Triangular Matrices

1.4.2.1. Determinant of Triangular Matrices
1.4.2.2. Determinant of Non-Triangular Square Matrices

1.4.3. Properties of Determinants

1.4.3.1. Simplifying Calculations
1.4.3.2. Calculation in any Case

1.5. Invertible Matrices

1.5.1. Properties of Invertible Matrices

1.5.1.1. The Concept of Inversion
1.5.1.2. Definitions and Basic Concepts

1.5.2. Invertible Matrix Calculation

1.5.2.1. Methods and Calculation
1.5.2.2. Exceptions and Examples

1.5.3. Expression Matrices and Matrix Equations

1.5.3.1. Expression Matrices
1.5.3.2. Matrix Equations

1.6. Solving Systems of Equations

1.6.1. Linear Equations

1.6.1.1. Discussion of the System: Rouché–Capelli Theorem
1.6.1.2. Cramer's Rule: Solving the System
1.6.1.3. Homogeneous Systems

1.6.2. Vector Spaces

1.6.2.1. Properties of Vector Spaces
1.6.2.2. Linear Combination of Vectors
1.6.2.3. Linear Dependence and Independence
1.6.2.4. Coordinate Vectors
1.6.2.5. The Basis Theorem

1.7. Quadratic Forms

1.7.1. Concept and Definition of Quadratic Forms
1.7.2. Quadratic Matrices

1.7.2.1. Law of Inertia for Quadratic Forms
1.7.2.2. Study of the Sign by Eigenvalues
1.7.2.3. Study of the Sign by Minors

1.8. Functions of One Variable

1.8.1. Analysis of the Behavior of a Magnitude

1.8.1.1. Local Analysis
1.8.1.2. Continuity
1.8.1.3. Restricted Continuity

1.9. Limits of Functions, Domain and Image in Real Functions

1.9.1. Functions of Several Variables

1.9.1.1. Vector of Several Variables

1.9.2. The Domain of a Function

1.9.2.1. Concept and Applications

1.9.3.Function Limits

1.9.3.1. Limits of a Function at a Point
1.9.3.2. Lateral Limits of a Function
1.9.3.3. Limits of Rational Functions

1.9.4. Indeterminacy

1.9.4.1. Indeterminacy in Functions with Roots
1.9.4.2. Indetermination 0/0

1.9.5. The Domain and Image of a Function

1.9.5.1. Concept and Characteristics
1.9.5.2. Domain and Image Calculation

1.10. Derivatives: Behavior Analysis

1.10.1. Derivatives of a Function at a Point

1.10.1.1. Concept and Characteristics
1.10.1.2. Geometric Interpretation

1.10.2. Differentiation Rules

1.10.2.1. Derivative of a Constant
1.10.2.2. Derivative of a Sum or Differentiation
1.10.2.3. Derivative of a Product
1.10.2.4. Derivative of an Opposite Function
1.10.2.5. Derivative of a Composite Function

1.11.Application of Derivatives to Study Functions

1.11.1.Properties of Differentiable Functions
1.11.2.Valuation of Economic Quantities
1.11.3.Differentiable Functions

1.12. Optimization of Functions of Several Variables

1.12.1. Function Optimization

1.12.1.1. Optimization with Equality Constraint
1.12.1.2. Critical Points
1.12.1.3. Relative Extremes

1.12.2.Convex and Concave Functions

1.12.2.1. Properties of Convex and Concave Functions
1.12.2.2. Inflection Points
1.12.2.3. Growth and Decay

1.13. Antiderivatives

1.13.1. Antiderivatives

1.13.1.1. Basic Concepts
1.13.1.2. Calculation Methods

1.13.2. Immediate Integrals

1.13.2.1. Properties of Immediate Integrals

1.13.3. Integration Methods

1.13.3.1. Rational Integrals

1.14. Definite Integrals

1.14.1. Barrow's Fundamental Theorem 

1.14.1.1. Definition of the Theorem
1.14.1.2. Calculation Basis
1.14.1.3. Applications of the Theorem

1.14.2. Curve Cut-off in Definite Integrals

1.14.2.1. Concept of Curve Cut-off
1.14.2.2. Calculation Basis and Operations Study
1.14.2.3. Applications of Curve Cut-off Calculation

1.14.3. Mean Value Theorem

1.14.3.1. Concept and Closed Interval Theorem
1.14.3.2. Calculation Basis and Operations Study
1.14.3.3. Applications of the Theorem

Module 2. Statistics I

2.1. Introduction to Statistics

2.1.1. Basic Concepts
2.1.2. Types of Variables
2.1.3. Statistical Information

2.2.Data Record Sorting and Classifying

2.2.1. Description of Variables
2.2.2. Frequency Distribution Table
2.2.3. Quantitative and Qualitative Frequency Distribution Tables

2.3.ICT Applications and Practical Systems

2.3.1. Basic Concepts
2.3.2. Tools
2.3.3. Data Representation

2.4.Summary Statistics I

2.4.1.Descriptive Statistics
2.4.2. Centralization Measurements
2.4.3.Measures of Dispersion
2.4.4. Measures of Shape and Position

2.5.Summary Statistics II

2.5.1.Box Plots
2.5.2. Identifying Outliers
2.5.3. Transformation

2.6.Statistical Analysis of the Relationship between the Two Variables

2.6.1. Tabulation
2.6.2. Contingency Tables and Graphical Representations
2.6.3. Linear Relationship between Quantitative Variables

2.7. Time Series and Index Numbers

2.7.1. Time Series
2.7.2. Variation Rates
2.7.3. Index Numbers
2.7.4. Consumer Prices Index (CPI) and Deflated Time Series

2.8. Introduction to Probability: Calculation and Basic Concepts

2.8.1. Basic Concepts
2.8.2. Set Theory
2.8.3. Probability Calculation

2.9. Random Variables and Probability Distributions

2.9.1. Random Variables
2.9.2. Variable Measurements
2.9.3. Probability Distribution

2.10. Probability Models for Random Variables

2.10.1. Probability Calculation
2.10.2. Discrete Random Variables
2.10.3. Continuous Random Variables
2.10.4. Models Derived from Normal Distribution

Module 3. Statistics II

3.1.Probability: Random Variables

3.1.1. Random Experiments
3.1.2. Axioms of Probability
3.1.3. Elementary Properties

3.2. Probability Models

3.2.1. Random Variables
3.2.2. Bernoulli’s Distribution
3.2.3. Binomial Distribution
3.2.4. Multinomial Distribution

3.3. Calculating Probabilities and Critical Points with R

3.3.1. Normal or Gaussian Distribution
3.3.2. R Commander
3.3.3. Properties

3.4. Statistical Inference: Some Preliminary Concepts

3.4.1. Definition and Preliminary Concepts
3.4.2. Binomial Distribution and Calculation
3.4.3. Normal Curve and Calculation

3.5. Point Estimators: Sampling Distributions and Properties

3.5.1. General Concepts of Sampling Distribution
3.5.2. Point Estimation
3.5.3. Interval Estimation

3.6. Confidence Intervals (CI): Mean, Proportion, Variance. CI in Two Populations

3.6.1. Intervals for One or Several Samples
3.6.2. Bootstrap Method
3.6.3. Bayesian Intervals

3.7. Hypothesis Testing in Statistical Inference Methods

3.7.1. Statistical Hypothesis Testing
3.7.2. Region of Rejection and Acceptance
3.7.3. Decision Rules

3.8. Particular Cases: Population Mean, Variance and Proportion. Parametric Contrasts

3.8.1. Known and Unknown Variances
3.8.2. Likelihood Ratio
3.8.3. Equality Test

3.9. Chi-Squared Goodness-of-Fit Test

3.9.1. Data Grouping
3.9.2. Critical Region
3.9.3. Expected Frequency

3.10. Normality Assumption Test: Jarque-Bera Test

3.10.1. Significant Variables
3.10.2. Central Limit Theorem
3.10.3. Estimators, Histogram

3.11. Hypothesis of Independence with Two Qualitative Variables

3.11.1. Concept of Independent Variables
3.11.2. Observed and Expected Frequencies
3.11.3. Calculating the Contrast Ratio

3.12. Simple Linear Regression Models and Point Estimation

3.12.1. Regression and Linear Correlation Coefficient
3.12.2. Parameter Inference
3.12.3. Model Assumptions

3.13. Confidence Interval and Regression Lines

3.13.1. Linear Functions and Regression
3.13.2. Simple Linear Regression
3.13.3. Exogenous and Endogenous Variables 

3.14. Predictions and Applications of Information and Communication Technology

3.14.1. Theoretical and Conceptual Framework
3.14.2. Collection and Analysis Techniques
3.14.3. General and Specific Objectives

3.15. Multiple Regression Models and Point Estimation

3.15.1. Hypothesis and Estimation
3.15.2. Types of Error and Model Adjustments
3.15.3. Linear Model Extensions

3.16. Global Significance Test of Regression

3.16.1. ANOVA Table
3.16.2. Multicollinearity

Module 4. Econometrics 

4.1. The Ordinary Least Squares (OLS) Method

4.1.1. Linear Regression Models
4.1.2. Types of Content
4.1.3. General Line and OLS Estimation

4.2. OLS Method in Other Scenarios

4.2.1. Abandoning Basic Assumptions
4.2.2. Method Behavior
4.2.3. Effect of Measurement Changes

4.3. Properties of OLS Estimators

4.3.1. Moments and Properties
4.3.2. Variance Estimation
4.3.3. Matrix Forms

4.4. OLS Variance Calculation 

4.4.1. Basic Concepts
4.4.2. Hypothesis Testing
4.4.3. Model Coefficients

4.5. Hypothesis Testing in Linear Regression Models

4.5.1. T-Contrast
4.5.2. F-Contrast
4.5.3. Global Contrasts

4.6. Confidence Intervals

4.6.1. Objectives
4.6.2. In a Coefficient
4.6.3. In a Combination of Coefficients

4.7.Specification Problems

4.7.1.Use and Concept
4.7.2.Types of Problems
4.7.3.Unobservable Explanatory Variables

4.8.Prediction in Linear Regression Models

4.8.1.Prediction
4.8.2.Average Value Intervals
4.8.3.Applications

4.9. Residual Analysis in Linear Prediction

4.9.1. Objectives and General Concepts
4.9.2. Analysis Tools
4.9.3. Waste Analysis

4.10. Qualitative Variables in GLRM I

4.10.1. Fundamentals
4.10.2. Models with Various Types of Information
4.10.3. Linear Metrics

4.11. Qualitative Variables in GLRM II

4.11.1. Binary Variables
4.11.2. Use of Dummy Variables
4.11.3. Time Series

4.12. Autocorrelation

4.12.1. Basic Concepts
4.12.2. Consequences
4.12.3. Contrast

4.13.Heteroscedasticity

4.13.1. Concept and Contrasts
4.13.2.Consequences
4.13.3.Time Series

A unique, key, and decisive educational experience to boost your professional development and make the definitive leap"