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36 students
Business Statistics A-Z
Master Business Statistics techniques with hands on lessons in GRETL Software
Created byRicky Lahiri
Last updated 3/2023
English
What you'll learn
- Students will learn econometrics techniques
- Students will learn advanced statistics techniques
- Students will gain hands on experience in conducting statistical and econometrics analysis on GRETL Software
- Students will learn about different kinds of regression techniques for different kinds of data
- Students will learn advanced forms of binary choice modelling ( Multinomial logistic regression, ordinal models, profit models)
- Students will learn time series analysis
- students will learn how to deal with panel data and panel data regression
- Students will learn about instrumental variable regression and count data models
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Course content
15 sections • 42 lectures • 5h 45m total length
Requirements
- Knowledge of basic statistics- mean, median, mode, standard deviation, variance etc
- Knowledge of statistical plots such as scatter plots
- High School Mathematics.
- A Mac or windows computer for installing GRETL Software
Description
Business Statistics A-Z: Master Business Statistics techniques with hands on lessons a course that exposes students to statistical and econometrics concepts (basic, intermediate and advanced) that are used to solve business problems. In this course students will learn statistical concepts and techniques, and econometrics tools and techniques through a mix of lectures on theoretical concepts and intuitions underlying statistical techniques, and practical application of statistical methods in solving real world business problems. The course covers basic to advanced level concepts, and allows students to learn both concepts and applications. After finishing this course students will have learnt how to use different statistical models to analyse any type of data to solve business problems; and how to study trends in data and use these trends to infer about the business setting they are studying. The course will also allow students to gain a better understanding of key concepts and the nuances in statistical methods. Statistics isn't a one size fits all discipline, and hence for different types of data and contexts, different analytical tools and models are required. This course goes beyond the simple linear regression and logistic regression techniques that are taught in most data analysis and data science classes, and exposes the students to advanced techniques meant for datasets which aren't appropriate for linear regression. The course also has hands on practical lessons on the GRETL ( GNU Regression, time series and econometrics library) software , through which students will learn how to use GRETL to implement advanced statistics and econometrics models. The course covers the following topics:
1. Hypothesis Testing
2. Correlation.
3. Simple Linear Regression.
4. Multiple linear regression.
5. Logistic Regression.
6. Multinomial Logistic Regression.
7. Ordinal Logit Model.
8. Probit Model.
9. Limitations of Linear Regression.
10. Time Series analysis and autocorrelation.
11. Panel Dta Regression.
12. Fixed effect models.
13. Random effect models.
14. Instrumental Variable Regression.
15. Count Data Models.
16. Duration Model.
Who this course is for:
- People with knowledge of basic statistics who want to learn intermediate and advanced statistics
- People who want to learn econometrics
- People who want to learn techniques in statistics that go beyond linear and logistic regression
- People who want to prepare for data science careers by learning advanced statistical modelling
- People who want to learn advanced business intelligence and data analysis skills
- People who want to learn how to deal with different types of data such as panel data and time series data
- People who want to learn regression techniques for different types of discrete, ordinal, panel and time series data