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Autor Tópico: Econometrics in Excel for MBA and professionals  (Lida 324 vezes)

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Econometrics in Excel for MBA and professionals
« em: 23 de Abril de 2021, 11:22 »
Duration: 2h16m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 44.1 kHz, 2ch | Size: 966 MB
Genre: eLearning | Language: English
Gentle introduction to key regression techniques using the Excel Analysis ToolPak from an experienced MBA instructor

What you'll learn
Identify links in business data using econometric techniques
Learn how to interpret regression output
Apply regression analyses in Excel using Analysis ToolPak
Build and test models for predictive analytics
Analyze continuous and discrete variables as well as time series data
Focus on examples and interpretation with a necessary minimum of theory

Requirements
Basic Excel

Description
There are many great Econometrics courses on Udemy which sell in thousands of copies. However, busy MBA students and professionals might not have sufficient programming experience to run econometric models in Python, R, Stata or Eviews. MS Excel, on the other hand, is a familiar and accessible tool which can be used for advanced data analytics.

In this concise course I have carefully selected the most important econometric tools and techniques that are really needed to understand the complicated relationships that exist in your data. Linear regression is the absolute must for data analysis and Analysis ToolPak is a simple yet powerful feature available in MS Excel. The key concepts used in this course have been distilled based on my experience with many groups of business students that I have taught in three MBA programs and various industries.

Improved English subtitles (not automatically generated)

تحليل البيانات في Excel مع ترجمة باللغة العربية

Datenanalyse in Excel mit Untertiteln in deutscher Sprache

带有简体中文字幕的Excel中的数据分析

हिंदी भाषा में उपशीर्षक के साथ एक्सेल में डेटा विश्लेषण

한국어 자막으로 Excel 데이터 분석

Uchambuzi wa data huko Excel na manukuu kwa lugha ya Kiswahili

Who this course is for:
pre-MBA students
MBA students
Business analysts working in Excel
Professionals working in data analytics


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