Business Statistics A-Z

Business Statistics A-Z, available at $49.99, has an average rating of 4.58, with 42 lectures, based on 6 reviews, and has 20 subscribers.

You will learn about 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 This course is ideal for individuals who are People with knowledge of basic statistics who want to learn intermediate and advanced statistics or People who want to learn econometrics or People who want to learn techniques in statistics that go beyond linear and logistic regression or People who want to prepare for data science careers by learning advanced statistical modelling or People who want to learn advanced business intelligence and data analysis skills or People who want to learn how to deal with different types of data such as panel data and time series data or People who want to learn regression techniques for different types of discrete, ordinal, panel and time series data It is particularly useful for People with knowledge of basic statistics who want to learn intermediate and advanced statistics or People who want to learn econometrics or People who want to learn techniques in statistics that go beyond linear and logistic regression or People who want to prepare for data science careers by learning advanced statistical modelling or People who want to learn advanced business intelligence and data analysis skills or People who want to learn how to deal with different types of data such as panel data and time series data or People who want to learn regression techniques for different types of discrete, ordinal, panel and time series data.

Enroll now: Business Statistics A-Z

Summary

Title: Business Statistics A-Z

Price: $49.99

Average Rating: 4.58

Number of Lectures: 42

Number of Published Lectures: 42

Number of Curriculum Items: 43

Number of Published Curriculum Objects: 43

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will 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

Who Should Attend

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

Target Audiences

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

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.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Introduction to GRETL Software

Lecture 1: Downloading and Installing GRETL

Lecture 2: GRETL Walkthrough

Lecture 3: Mathematical Operations in GRETL

Chapter 3: Types of Data

Lecture 1: Different types of data

Chapter 4: Association and Correlation

Lecture 1: Association and Correlation Intuition

Lecture 2: Correlation in GRETL

Lecture 3: Reading Correlation Matrix

Chapter 5: Data Screening

Lecture 1: Data Screening

Lecture 2: Dealing with missing data in GRETL

Chapter 6: Hypothesis Testing

Lecture 1: Hypothesis Testing

Chapter 7: Linear Regression

Lecture 1: Simple Linear Regression Intuition

Lecture 2: Reading Regression Output

Lecture 3: Simple Linear Regression in GRETL

Lecture 4: Multiple Linear Regression Intuition

Lecture 5: Multiple Linear regression in GRETL

Lecture 6: Moderation Intuition

Lecture 7: Moderation in GRETL

Lecture 8: Mediation Intuition

Lecture 9: Mediation in GRETL

Chapter 8: Discrete Coice models

Lecture 1: Binary Logistic Regression or Logit Model Intuition

Lecture 2: Binary Logistic Regression in GRETL

Lecture 3: Multinomial Logistic Regression Model Intuition

Lecture 4: Multinomial Logistic Regression in GRETL

Lecture 5: Probit Regression Intuition

Lecture 6: Probit Model in GRETL

Lecture 7: Ordered Logit Model Intuition

Lecture 8: Ordered Logit Model in GRETL

Chapter 9: Linear Regression Assumptions and Violations

Lecture 1: Linear Regression Assumptions and Violations

Chapter 10: Time Series Analysis

Lecture 1: Autocorrelation

Lecture 2: Autoregression and Time Series Analysis Intuition

Lecture 3: Time Series Analysis in GRETL

Chapter 11: Panel Data Regression

Lecture 1: Panel Data Intuition

Lecture 2: Variations in Panel Data

Lecture 3: Types of Panel Data Models Intuition

Lecture 4: Panel Data Regression in GRETL

Chapter 12: Instrumental Variable Regression

Lecture 1: Instrumental Variable Regression and Endogeneity Intuition

Lecture 2: Instrumental Variable Regression in GRETL

Chapter 13: Count Data Models

Lecture 1: Count Data Regression Intuition

Lecture 2: Count Data Regression (Poisson Regression) in GRETL

Chapter 14: Survival/Duration Regression Models

Lecture 1: Survival/Duration Models Intuition

Lecture 2: Survival/Duration Models in GRETL

Chapter 15: Practice Activity

Instructors

Ricky Lahiri
Data Scientist, Digital Marketer and Doctoral Student.

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