返回到 Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions

4.7

星

1,698 個評分

•

280 條評論

The ability to understand and apply Business Statistics is becoming increasingly important in the industry. A good understanding of Business Statistics is a requirement to make correct and relevant interpretations of data. Lack of knowledge could lead to erroneous decisions which could potentially have negative consequences for a firm. This course is designed to introduce you to Business Statistics. We begin with the notion of descriptive statistics, which is summarizing data using a few numbers. Different categories of descriptive measures are introduced and discussed along with the Excel functions to calculate them. The notion of probability or uncertainty is introduced along with the concept of a sample and population data using relevant business examples. This leads us to various statistical distributions along with their Excel functions which are then used to model or approximate business processes. You get to apply these descriptive measures of data and various statistical distributions using easy-to-follow Excel based examples which are demonstrated throughout the course.
To successfully complete course assignments, students must have access to Microsoft Excel.
________________________________________
WEEK 1
Module 1: Basic Data Descriptors
In this module you will get to understand, calculate and interpret various descriptive or summary measures of data. These descriptive measures summarize and present data using a few numbers. Appropriate Excel functions to do these calculations are introduced and demonstrated.
Topics covered include:
• Categories of descriptive data
• Measures of central tendency, the mean, median, mode, and their interpretations and calculations
• Measures of spread-in-data, the range, interquartile-range, standard deviation and variance
• Box plots
• Interpreting the standard deviation measure using the rule-of-thumb and Chebyshev’s theorem
________________________________________
WEEK 2
Module 2: Descriptive Measures of Association, Probability, and Statistical Distributions
This module presents the covariance and correlation measures and their respective Excel functions. You get to understand the notion of causation versus correlation. The module then introduces the notion of probability and random variables and starts introducing statistical distributions.
Topics covered include:
• Measures of association, the covariance and correlation measures; causation versus correlation
• Probability and random variables; discrete versus continuous data
• Introduction to statistical distributions
________________________________________
WEEK 3
Module 3: The Normal Distribution
This module introduces the Normal distribution and the Excel function to calculate probabilities and various outcomes from the distribution.
Topics covered include:
• Probability density function and area under the curve as a measure of probability
• The Normal distribution (bell curve), NORM.DIST, NORM.INV functions in Excel
________________________________________
WEEK 4
Module 4: Working with Distributions, Normal, Binomial, Poisson
In this module, you'll see various applications of the Normal distribution. You will also get introduced to the Binomial and Poisson distributions. The Central Limit Theorem is introduced and explained in the context of understanding sample data versus population data and the link between the two.
Topics covered include:
• Various applications of the Normal distribution
• The Binomial and Poisson distributions
• Sample versus population data; the Central Limit Theorem...

EM

Aug 27, 2020

This is one of the best courses i have atended since, the exercises are all related to the topic.Great job. .\n\nThanks to Mr Sharad Borle for explaining very well the content in this course .

GG

Aug 23, 2017

The course has been designed in a manner to give maximum understanding of the concept. The Quizzes are really grilling. and helps you strengthen the knowledge gained from the lecture videos.

篩選依據：

創建者 Shreya M

•Jul 08, 2017

THE INSTRUCTOR WAS GOOD AND THE COURSE CONTENT WAS SIMPLE AND YET AMAZING. I ENJOYED EACH BIT OF THE CLASS. THANKS A TON!

創建者 Viviana C

•Mar 25, 2019

the last portion was really difficult to understand, the material was too general for the questions covered in the quiz.

創建者 Berly E

•Aug 01, 2020

I was not able to resolve the Question #5 using the Poisson formula. Not sure I understood this topic correctly.

創建者 Saurabh M

•Aug 02, 2017

This course was a little difficult compared to the previous course and involved a lot of theoretical concepts.

創建者 Chintan D

•Jun 12, 2020

The content was good and explained in simple words. However, I would have liked more real-life examples

創建者 MO H

•Jan 30, 2019

Showing the key important thing for learning the basic statistical concept; Nice example and practice.

創建者 Santiago R R

•Jul 21, 2020

Excellent course, would really be 5 stars if the feedback on the assignments was a bit more helpful

創建者 Ashis G

•May 14, 2020

The interactive design of the course is instrumental in motivating the learners greatly.

創建者 Tim L

•Apr 30, 2018

Very good introduction to statistical distributions as it relates to business problems.

創建者 EV B

•May 26, 2020

Clear explanations of concepts I haven't studied in any detail previously

創建者 Daniel L

•May 24, 2017

Overall, great course and straightforward expectations for the end goals.

創建者 Samuel G

•May 17, 2020

Good course but the quizzes could use better feedback on wrong answers.

創建者 shashank j

•May 10, 2020

Course is good .It gives you business applications of all the concepts

創建者 Darryl F

•Sep 18, 2018

Tough Course at the end. Definitely needed to review multiple times

創建者 adriana P

•Dec 31, 2016

It was a clear explanation to the statistical, and the examples are

創建者 Hesham M H S

•Dec 01, 2019

it is interesting, but with more examples it would add more value.

創建者 Michelle G

•Apr 27, 2020

Topics covered well. Good basic understanding of topics covered.

創建者 Dhiraj J

•Jun 27, 2020

The course was really good and was a good learning experience

創建者 Catherine S

•May 21, 2020

A bit slow but well explained which make it somewhat easy.

創建者 David A

•Aug 02, 2020

that was a lot harder than course 1 and really tests you.

創建者 Harsha M

•Apr 24, 2019

Very nice course, helped to clear my basic understanding.

創建者 Patrick W

•Jul 05, 2019

Useful refresher for business context of statistics

創建者 Renier B

•Dec 02, 2019

Good course, learned some really new applications.

創建者 Kim K

•Aug 08, 2018

Rigorous and rewarding when you put the work in.

創建者 Surapa K

•Oct 14, 2019

short, concise, informative and practical

- Finding Purpose & Meaning in Life
- Understanding Medical Research
- Japanese for Beginners
- Introduction to Cloud Computing
- Foundations of Mindfulness
- Fundamentals of Finance
- 機器學習
- 使用 SAS Viya 進行機器學習
- 幸福科學
- Covid-19 Contact Tracing
- 適用於所有人的人工智能課程
- 金融市場
- 心理學導論
- Getting Started with AWS
- International Marketing
- C++
- Predictive Analytics & Data Mining
- UCSD Learning How to Learn
- Michigan Programming for Everybody
- JHU R Programming
- Google CBRS CPI Training

- Natural Language Processing (NLP)
- AI for Medicine
- Good with Words: Writing & Editing
- Infections Disease Modeling
- The Pronounciation of American English
- Software Testing Automation
- 深度學習
- 零基礎 Python 入門
- 數據科學
- 商務基礎
- Excel 辦公技能
- Data Science with Python
- Finance for Everyone
- Communication Skills for Engineers
- Sales Training
- 職業品牌管理職業生涯品牌管理
- Wharton Business Analytics
- Penn Positive Psychology
- Washington Machine Learning
- CalArts Graphic Design

- 專業證書
- MasterTrack 證書
- Google IT 支持
- IBM 數據科學
- Google Cloud Data Engineering
- IBM Applied AI
- Google Cloud Architecture
- IBM Cybersecurity Analyst
- Google IT Automation with Python
- IBM z/OS Mainframe Practitioner
- UCI Applied Project Management
- Instructional Design Certificate
- Construction Engineering and Management Certificate
- Big Data Certificate
- Machine Learning for Analytics Certificate
- Innovation Management & Entrepreneurship Certificate
- Sustainabaility and Development Certificate
- Social Work Certificate
- AI and Machine Learning Certificate
- Spatial Data Analysis and Visualization Certificate

- Computer Science Degrees
- Business Degrees
- 公共衛生學位
- Data Science Degrees
- 學士學位
- 計算機科學學士
- MS Electrical Engineering
- Bachelor Completion Degree
- MS Management
- MS Computer Science
- MPH
- Accounting Master's Degree
- MCIT
- MBA Online
- 數據科學應用碩士
- Global MBA
- Master's of Innovation & Entrepreneurship
- MCS Data Science
- Master's in Computer Science
- 公共健康碩士