Data Analysis for Business
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Data Analysis for Business
This course is part of Data & Finance for the future Specialization
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29 reviews
Skills you'll gain
- Statistical Hypothesis Testing
- Data Presentation
- Probability & Statistics
- Analytics
- Data Strategy
- Statistical Modeling
- Data Visualization
- Correlation Analysis
- Statistical Analysis
- Descriptive Statistics
- Data Science
- Data-Driven Decision-Making
- Business Analytics
- Statistical Inference
- Strategic Decision-Making
- Data Analysis
- Statistical Methods
- Regression Analysis
Details to know
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There are 5 modules in this course
The Data Science in Business course equips participants with the tools and techniques to leverage data for informed decision-making in the corporate world. Covering data analysis, and data-driven strategies, this course empowers individuals to extract valuable insights, enhance business processes, and drive strategic initiatives through data-driven approaches. Combining theoretical foundations with hands-on applications, learners will be well-prepared to navigate the intersection of data science and business analytics.
This week, you’ll learn the impact of data analysis and its elements on business. Also, the diferences of variables, measurement scales and types of data analysis.
What's included
5 videos5 readings4 assignments1 discussion prompt
5 videos•Total 24 minutes
- Information, Database and Statistics•7 minutes
- Types of Variable and Measurement Scales•5 minutes
- Types and Sources of Data•5 minutes
- Types of Data Analysis•3 minutes
- Example in Excel of a Database Construction•5 minutes
5 readings•Total 127 minutes
- My Bio•2 minutes
- Syllabus•10 minutes
- Week 1 - Slide deck•45 minutes
- Introduction•30 minutes
- Data, data analysis, and descriptive statistics•40 minutes
4 assignments•Total 45 minutes
- Types of variables•10 minutes
- Information, database and statistic•10 minutes
- Types of data•10 minutes
- Data Analysis•15 minutes
1 discussion prompt•Total 10 minutes
- Why being data-driven is so important?•10 minutes
This week, you’ll learn how to tell something through data. Managing data in graphs and tables, and the principals pitfalls about data visualization.
What's included
7 videos2 readings4 assignments1 discussion prompt
7 videos•Total 62 minutes
- Tables•7 minutes
- Charts for Categorical Variables•4 minutes
- Charts for Numerical Variables - Part 1•2 minutes
- Charts for Numerical Variables - Part 2•2 minutes
- Other Types of Chart and the Pitfalls of DCOVA•7 minutes
- Excel Example•5 minutes
- Recording of Data Analysis for Business Live Session on 22-03-17 20:07:20 [21:09]•35 minutes
2 readings•Total 135 minutes
- Week 2 - Slide deck•45 minutes
- Week 2 reading: Data Visualization •90 minutes
4 assignments•Total 45 minutes
- Pitfalls of DCOVA•15 minutes
- Tables•10 minutes
- Chart•10 minutes
- Numerical Charts•10 minutes
1 discussion prompt•Total 10 minutes
- What is a good data visualization?•10 minutes
This week, you’ll learn how to deal with data and how to describe data in terms of some parameters: the differences between dispersion and central tendcy measures.
What's included
8 videos2 readings4 assignments1 discussion prompt
8 videos•Total 30 minutes
- Measures of Central Tendency•5 minutes
- Measures of Variation and Shape•5 minutes
- Skewness and Kurtosis•2 minutes
- Quartiles and Percentiles•3 minutes
- Boxplot•1 minute
- Population and Sample•3 minutes
- Covariance and Correlation•3 minutes
- Excel Example•7 minutes
2 readings•Total 120 minutes
- Week 3 - Slide deck•45 minutes
- Week 3 reading: Descriptive Measures•75 minutes
4 assignments•Total 55 minutes
- Boxplot•15 minutes
- Population and sample•15 minutes
- Central Tendency•15 minutes
- Shape•10 minutes
1 discussion prompt•Total 10 minutes
- Sampling•10 minutes
In this week you will see some probability principles which are linked with datasets and data visualization. Also, statistical principles which are applied in data analysis.
What's included
7 videos5 readings4 assignments1 discussion prompt
7 videos•Total 85 minutes
- Probability Basics for Inferential Statistics•9 minutes
- Main probability distributions: uniform, binomial, Poisson, normal, and exponential•11 minutes
- Sampling and Confidence Interval•5 minutes
- Confidence Interval for the Mean•10 minutes
- Hypothesis Testing Fundamentals•5 minutes
- T and Z Test for the Mean•19 minutes
- Recording of Data Analysis for Business Live Session on 22-03-31 20:01:35 [04:00]•25 minutes
5 readings•Total 225 minutes
- Week 4 - Slide deck•45 minutes
- Probability Concepts and their analysis•30 minutes
- Probability fundamentals - part 2•30 minutes
- Sampling and Confidence Interval•90 minutes
- Hypothesis testing•30 minutes
4 assignments•Total 55 minutes
- Confidence Interval•10 minutes
- Hypothesis testing•20 minutes
- Probability•15 minutes
- Probability•10 minutes
1 discussion prompt•Total 10 minutes
- Predictive vs. Analytics•10 minutes
In this week you will see topics in linear regressions. Regression analysis is used to investigate the relationship between two or more variables. Often used in predicting some characteristic using one or more independent variables .
What's included
8 videos2 readings4 assignments1 discussion prompt
8 videos•Total 45 minutes
- Linear Models and Regressions•8 minutes
- Measures of Variation and Coefficient of Determination•4 minutes
- Regression Assumptions•4 minutes
- Point and Interval Estimates•5 minutes
- Multiple Regression Model•4 minutes
- Evaluating Multiple Regression Models•6 minutes
- Excel example•5 minutes
- Qualitative Variables in Multiple Regressions•8 minutes
2 readings•Total 120 minutes
- Week 5 - Slide deck•45 minutes
- Week 5 reading: Linear Models and Regression Analysis•75 minutes
4 assignments•Total 40 minutes
- Causation and correlation•10 minutes
- OLS - Ordinary Least Squares•10 minutes
- Multiple Regression•10 minutes
- Dummies•10 minutes
1 discussion prompt•Total 10 minutes
- How linear models could predict real life?•10 minutes
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University of Colorado Boulder
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Campus BBVA
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Reviewed on Apr 17, 2024
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