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

4.7

星

1,754 個評分

•

290 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 Nitish A

•Feb 02, 2018

It was a well explained course, but I believe the course should have been more extensive. Also, the reading material was exactly the same as the slides the professor already presented in the video but still have been allotted independent reading times. It feels like a topic spread out as a course.

創建者 Courtney G

•Jun 22, 2017

Overview of normal distribution was much more comprehensive than the discrete distributions. More time/attention could have been given to explaining the concepts behind the two discrete distributions in order to use them in a practical context (i.e., business application questions).

創建者 Noel E D

•May 06, 2018

I wish there were more business cases and deep dives. I found the content a bit short and lacking. It did however introduce the concepts well and allowed me to understand much better material googled elsewhere

創建者 Prachi M

•Jul 08, 2019

binom.inv is not explained. Also, determining the number of trials needed for a specific probability is not explained as asked in the test for week 4

創建者 Ken Y

•Jul 23, 2020

Some quiz questions can be confusing and not all assumptions are given. Read carefully and check the forum for people with similar questions.

創建者 Davida C

•Sep 22, 2017

A bit too technical for me. I really just needed to master Excel, and I got that from Part 1 of the course.

創建者 Anza T

•Apr 14, 2020

the questions were tricky

創建者 renu m

•Mar 17, 2019

Too much focus on the excel functions. I had to use supporting materials to understand the concepts better so that the excel application can be put into context.

創建者 Lyn S

•Aug 10, 2017

Using the internet and its loads of detailed info and teachings to support this learning. Just wading thru this to get the certificate.

創建者 Albert C

•Feb 21, 2019

Too basic, not enough of actual Excel usage

創建者 Timothea N S E

•May 04, 2020

barely any explanations when answer is wrong.

- 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