Estadística Aplicada a los Negocios
Learn applied statistics for business intelligence with descriptive and inferential techniques to analyze data and make informed business decisions.
Learn applied statistics for business intelligence with descriptive and inferential techniques to analyze data and make informed business decisions.
This online course provides an introduction to data analysis for business intelligence. You'll learn essential tools and techniques of descriptive and inferential statistics to analyze data and transform it into valuable information for decision-making. The course teaches you how to use data to achieve specific business objectives like identifying your most valuable customers, controlling expenses, optimizing production chains, forecasting new product performance, understanding how events affect sales, determining which products to eliminate from your portfolio, and identifying the best timing for product positioning efforts. You'll master fundamental concepts and learn to use estimators, histograms, measurement scales, variance, standard deviation, normal probability, informal probability, expected value of random variables, confidence intervals, Poisson distribution, and more. This is the first course in the Business Intelligence Professional Certification Program, complemented by a second course on Business Intelligence Tools.
Instructors:
Preng Biba
Jorge Samayoa
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What you'll learn
Learn to analyze data with Excel for business intelligence Understand and apply inferential statistics in business contexts Perform hypothesis testing and interpret results Master regression analysis for real-world business cases Calculate confidence intervals for business decision-making Use measurement scales, frequency distribution, and graphical representations Apply central tendency statistical measures to business data Differentiate between discrete and continuous random variables
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Desktop, Tablet
Limited Access access
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There are 10 modules in this course
This comprehensive course covers essential concepts in business statistics and data analysis using Excel. Students will learn both descriptive and inferential statistical techniques that can be applied to real business scenarios. The curriculum includes data analysis with Excel, statistical measures, frequency distribution, central tendency measures (mean, median, mode), estimators, confidence intervals, hypothesis testing, and regression analysis. The course also explores probability concepts, random variables (discrete and continuous), and various probability distributions (binomial, geometric, Poisson, uniform, normal, and exponential). All concepts are taught with a focus on practical business applications, enabling students to transform raw data into valuable insights for decision-making.
Análisis de datos con Excel
Module 1
Análisis de datos, medidas estadísticas, distribución de frecuencias y datos
Module 2
Medidas de tendencia central (media, mediana, modo, mínimo, máximo, cuartil, varianza y desviación estandar)
Module 3
Estimadores, intervalos de confianza y pruebas de hipótesis
Module 4
Análisis regresional
Module 5
Conceptos básicos de estadística
Module 6
Probabilidad informal y variables aleatorias discretas y continuas
Module 7
Probabilidad binomial, probabilidad geométrica, probabilidad de Poisson
Module 8
Variables aleatorias continuas, probabilidad uniforme, probabilidad normal, probabilidad exponencial
Module 9
Estadística aplicada a negocios
Module 10
Fee Structure
Payment options
Financial Aid
Instructors
Preng Biba
3 Courses
Operations Research Institute at Galileo University
Preng Biba is a mechatronics engineer and researcher at Galileo University, specializing in operations research and network protocol interoperability.
Jorge Samayoa
3 Courses
Director of the Operations Research Institute at Galileo University
Jorge Samayoa, PhD from Purdue, is Director of the Operations Research Institute at Galileo University, specializing in industrial engineering and analytics.
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