Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions
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Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions
This course is part of Business Statistics and Analysis Specialization
Instructor: Sharad Borle
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2,696 reviews
Skills you'll gain
- Statistical Modeling
- Data Literacy
- Business Analytics
- Statistical Methods
- Statistical Inference
- Correlation Analysis
- Descriptive Analytics
- Decision Making
- Box Plots
- Probability Distribution
- Statistics
- Sampling (Statistics)
- Probability & Statistics
- Descriptive Statistics
- Excel Formulas
- Data Analysis
- Statistical Analysis
Tools you'll learn
Details to know
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There are 4 modules in this course
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
What's included
8 videos8 readings7 assignments
8 videos•Total 38 minutes
- Meet the Professor•2 minutes
- Descriptive Statistics•7 minutes
- Descriptive Statistics Continued•8 minutes
- Introduction to the Box Plot and Standard Deviation•7 minutes
- The Standard Deviation "Rule of Thumb"•4 minutes
- Testing the "Rule of Thumb"•7 minutes
- Chebyshev's Theorem•2 minutes
- Week 1 Recap•1 minute
8 readings•Total 80 minutes
- Course FAQs•10 minutes
- Pre-Course Survey•10 minutes
- Slides, Lesson 1•10 minutes
- Slides, Lesson 2•10 minutes
- Slides, Lesson 3•10 minutes
- Slides, Lesson 4•10 minutes
- Slides, Lesson 5•10 minutes
- Slides, Lesson 6•10 minutes
7 assignments•Total 214 minutes
- Basic Data Descriptors and Data Distributions•60 minutes
- Descriptive Statistics•4 minutes
- Descriptive Statistics Continued•30 minutes
- Introduction to the Box Plot and the Standard Deviation•30 minutes
- The Standard Deviation “Rule of Thumb”•30 minutes
- Testing the “Rule of Thumb”•30 minutes
- Chebyshev’s Theorem•30 minutes
What's included
6 videos5 readings6 assignments
6 videos•Total 34 minutes
- Covariance•8 minutes
- Correlation•9 minutes
- Causation•4 minutes
- Probability and Random variables•6 minutes
- Statistical Distributions•7 minutes
- Week 2 Recap•1 minute
5 readings•Total 50 minutes
- Slides, Lesson 1•10 minutes
- Slides, Lesson 2•10 minutes
- Slides, Lesson 3•10 minutes
- Slides, Lesson 4•10 minutes
- Slides, Lesson 5•10 minutes
6 assignments•Total 184 minutes
- Descriptive Measures of Association, Probability, and Data Distributions•60 minutes
- Covariance•30 minutes
- Correlation•4 minutes
- Causation•30 minutes
- Probability•30 minutes
- Statistical Distributions•30 minutes
What's included
5 videos5 readings6 assignments
5 videos•Total 42 minutes
- Probability Density Function and Area Under the Curve•10 minutes
- The Normal Distribution•8 minutes
- The NORM.DIST Function•9 minutes
- The NORM.DIST Function Continued•8 minutes
- The NORM.INV Function•8 minutes
5 readings•Total 50 minutes
- Slides, Lesson 1•10 minutes
- Slides, Lesson 2•10 minutes
- Slides, Lesson 3•10 minutes
- Slides, Lesson 4•10 minutes
- Slides, Lesson 5•10 minutes
6 assignments•Total 210 minutes
- The Normal Distribution•60 minutes
- PDF and PMF•30 minutes
- The Normal Distribution•30 minutes
- The NORM.DIST Function•30 minutes
- The NORM.DIST Function Continued•30 minutes
- The NORM.INV Function•30 minutes
What's included
7 videos7 readings7 assignments
7 videos•Total 46 minutes
- Applying the Normal Distribution, Standard Normal Distribution•10 minutes
- Population and Sample data•6 minutes
- Central Limit Theorem•8 minutes
- The Binomial Distribution•10 minutes
- Business Application of the Binomial Distribution•5 minutes
- Poisson Distribution•5 minutes
- Weeks 3 and 4 Recap•1 minute
7 readings•Total 70 minutes
- Slides, Lesson 1•10 minutes
- Slides, Lesson 2•10 minutes
- Slides, Lesson 3•10 minutes
- Slides, Lesson 4•10 minutes
- Slides, Lesson 5•10 minutes
- Slides, Lesson 6•10 minutes
- End-of-Course Survey•10 minutes
7 assignments•Total 240 minutes
- Working with Distributions (Normal, Binomial, Poisson), Population and Sample Data•60 minutes
- Applying the Normal Distribution, Standard Distribution•30 minutes
- Population and Sample data•30 minutes
- Central Limit Theorem•30 minutes
- The Binomial Distribution•30 minutes
- Business Application of the Binomial Distribution•30 minutes
- Poisson Distribution•30 minutes
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Reviewed on Feb 6, 2023
The most exciting and challenging excel course i have ever taken. It kept me on my toes and provided real life application of statistics. I didn't regret taking this course.
Reviewed on Jul 3, 2018
Loved studing and learning about normal distributions, continuous vs discrete data and how to estimate probabilities by different distributions approach. Learning is fascinating
Reviewed on Jan 8, 2018
I personally loved it!! Coming from a technical background, it really helped me to understand how we can apply the concepts and techniques to real world/practical problems.
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