Statistics for Business Analytics: Data Analysis with Excel

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Diogo Alves de Resende

5:24:11

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1 - Introduction

1 - Introduction.mp4

03:15

2 - IMPORTANT Download Course Material.html

2 - Statistics-with-Excel.zip

3 - CASE STUDY Statistics in the FAANG Companies.mp4

03:38

2 - Introduction to Statistics

1 - Key Statistical Concepts.html

1 - Types of variables.html

2 - Population vs Sample.html

3 - Mean.html

4 - Game Plan for Introduction to Statistics.mp4

01:05

4 - Median.html

5 - Mode.html

5 - Types of Variables.mp4

02:23

6 - Population vs Sample.mp4

02:37

6 - Standard Deviation.html

7 - Case Study Briefing.mp4

01:16

7 - Normal Distribution.html

8 - Covariance.html

8 - Measures of Central Tendency.html

9 - Correlation.html

9 - Mean.mp4

03:11

10 - EXCEL Mean.mp4

09:42

11 - Median.mp4

02:48

12 - EXCEL Median.mp4

03:39

13 - Mode.mp4

01:24

14 - EXCEL Mode.mp4

07:36

15 - CHALLENGE EXCEL Central Tendency.mp4

08:31

16 - Standard Deviation.mp4

04:07

17 - EXCEL Standard Deviation.mp4

03:16

18 - Coefficient of Variation.mp4

03:54

19 - EXCEL Coefficient of Variation.mp4

01:14

20 - Normal Distribution.mp4

03:42

21 - EXCEL Normal Distribution.mp4

10:02

22 - Covariance.mp4

03:29

23 - EXCEL Covariance.mp4

02:04

24 - Correlation.mp4

04:58

25 - EXCEL Correlation.mp4

03:08

3 - Confidence Intervals

10 - Standard Error of the Sample Mean.html

11 - Zscore and Standardization.html

13 - Confidence Interval with Large Samples.html

14 - TStudent Distribution.html

15 - Confidence Interval with Small Samples.html

26 - Game Plan for Confidence Intervals.mp4

01:03

27 - Case Study Briefing.mp4

01:20

28 - Standard Error of the Sample Mean.mp4

02:10

29 - EXCEL Standard Error of the Sample Mean.mp4

04:23

30 - Zscore and Standardization.mp4

02:25

31 - EXCEL Zscore and Standadization.mp4

05:09

32 - Confidence Level.mp4

04:08

33 - EXCEL Confidence Level.mp4

03:30

34 - Confidence Interval with Large Samples.mp4

05:06

35 - EXCEL Confidence Interval with Large Samples.mp4

07:05

36 - CASE STUDY Guinness Beer and the Tstudent distribution.mp4

02:33

37 - TStudent Distribution.mp4

03:22

38 - Confidence Interval with Small Samples.mp4

03:22

39 - EXCEL Confidence Interval with Small Samples.mp4

08:01

40 - Your feedback is valuable.html

4 - Hypothesis Testing

16 - Hypothesis Testing.html

17 - Pvalue.html

18 - Type I and Type II errors.html

19 - Twotailed tests.html

20 - Onetailed Hypothesis Testing.html

41 - Game Plan for Hypothesis Testing.mp4

02:37

42 - CASE STUDY Improving Amazon Fashion Product Returns using Business Analytics.mp4

02:32

43 - What is Hypothesis Testing.mp4

04:48

44 - Pvalue.mp4

05:14

45 - Type I and Type II errors.mp4

03:53

46 - CASE STUDY Publication Bias in Statistics.mp4

02:57

47 - How to test your hypothesis Known Variance and 2Tails.mp4

06:34

48 - CASE STUDY BRIEFING Tesla Production.mp4

01:44

49 - EXCEL How to test your hypothesis known Variance and 2Tails.mp4

07:58

50 - How to test your hypothesis unknown Variance and 2Tails.mp4

02:14

51 - EXCEL How to test your hypothesis known Variance and 2Tails.mp4

04:52

52 - Paired TTest 2Tails.mp4

04:42

53 - Excel Paired TTest 2Tails.mp4

07:09

54 - Two Sample TTest 2Tails.mp4

05:33

55 - Excel Two Sample TTest 2Tails.mp4

09:00

56 - Onetailed tests.mp4

04:34

57 - EXCEL Onetailed tests part 1.mp4

09:03

58 - EXCEL One tailed tests part 2.mp4

09:16

5 - Regression Analysis

21 - Linear Regression.html

22 - Multilinear Regression.html

59 - Game Plan for Regression Analysis.mp4

01:18

60 - CASE STUDY BRIEFING Pricing Diamonds.mp4

01:31

61 - Linear Regression.mp4

04:53

62 - EXCEL Scatterplot.mp4

05:37

63 - EXCEL Linear Regression.mp4

04:56

64 - Linear Regression Statistics and Output.mp4

04:24

65 - EXCEL Linear Regression Statistics and Output.mp4

03:21

66 - Dummy Variable Trap.mp4

04:47

67 - EXCEL Linear Regression with Dummy Variables.mp4

06:43

68 - CASE STUDY Linearity Bias in Statistics and Business Analytics.mp4

04:00

69 - Multilinear Regression.mp4

02:36

70 - EXCEL Multilinear Regression.mp4

08:24

71 - Under and Overfitting.mp4

03:20

72 - Training and Test Set.mp4

03:00

73 - EXCEL Training and Test Set.mp4

04:57

74 - EXCEL Predictions.mp4

04:12

75 - Assessing Regression Models.mp4

06:39

76 - EXCEL Assessing Regression Model.mp4

07:26

77 - STATISTICS CASE STUDY Dangers of Regression Analysis.mp4

02:51

6 - Bonus Section

78 - Bonus Lecture.html

Description

Improve your Statistics & Analysis Skills. Enhance your Business and Data Analytics with Statistical Modelling & Excel.

What You'll Learn?

Comprehend the fundamental concepts and principles of statistics and their application in business analytics
Complete several data analysis projects in Excel to demonstrate mastery of statistical concepts and business analytics skills
Perform data analysis using Excel and apply statistical methods to business problems
Utilize Excel to perform hypothesis testing and make decisions based on business data
Analyze business data using descriptive and inferential statistics in Excel
Construct and interpret statistical models to make informed business decisions
Implement regression analysis in Excel to predict future trends and make data-driven decisions
Utilize data analytics techniques to analyze large datasets and extract meaningful insights
Evaluate real-world business scenarios and critically assess the use of statistical models and data analytics
Analyze data using linear regression techniques in Excel to make predictions and understand relationships

Who is this for?

Aspiring data analysts who are interested in developing their expertise in statistics and business analytics

Business professionals who want to develop their data analysis skills to make informed business decisions

Entrepreneurs and small business owners who want to use data analysis to make informed business decisions and grow their businesses

IT professionals who want to develop their skills in data analysis and data modeling to advance their careers

Managers and executives who want to understand the role of data analytics in decision making and lead their teams in data-driven decision making

More details

Description
Data is everywhere and plays a crucial role in the success of businesses across all industries. As the world becomes more and more data-driven, the demand for professionals who can effectively analyze and interpret data is growing rapidly.
If you're ready to take your place at the forefront of this exciting and rapidly evolving field, "Statistics for Business Analytics: Data Analysis with Excel" is the course for you!
This comprehensive online course is designed for anyone looking to develop their skills in data analysis, statistical modeling, and business analytics. Whether you're just starting out or looking to advance your career, this course will provide you with the knowledge and hands-on experience you need to succeed.
With its engaging curriculum, practical case studies, and supportive community, this course is the perfect opportunity to build your skills, advance your career, and stay ahead of the curve in a rapidly changing landscape. Here are four reasons why you should take this course:
1Â | Course Relevance - Stay Ahead of the Curve in a Data-Driven World
In today's business world, having a solid understanding of statistics and data analysis is more important than ever. This course will give you the skills and knowledge you need to succeed in business analytics, helping you stay ahead of the curve in a rapidly changing landscape.
2 | Skills Gained - Master Data Analysis, Statistical Modeling, and Business Analytics
In this course, you'll gain a deep understanding of data analysis, statistical modeling, and business analytics. You'll learn how to use Excel to perform data analytics, how to apply regression analysis and hypothesis testing, and how to make informed decisions based on your data analysis.
3 | Case Studies and Practice Activities - Apply Your Skills to Real-World Problems
One of the best ways to learn is by doing, and this course includes a range of case studies and practice activities to help you apply your skills to real-world problems. Whether you're working through a case study or practicing data analysis in Excel, you'll have the chance to put your newfound skills into action.
4 | Q&A Support and Instructor Engagement - Get the Help You Need When You Need It
Learning can be challenging, but you don't have to go it alone. The Q&A and student communities are great places to get help and connect with others. I am also available to answer any questions you have and provide support as you progress through the course.
In conclusion, "Statistics for Business Analytics: Data Analysis with Excel" is the perfect course for anyone looking to build their skills and advance their career in business analytics. With its comprehensive curriculum, practical case studies, and supportive community, you'll gain the skills and confidence you need to succeed in today's data-driven business world.
Don't miss out on this opportunity to transform your career. Enroll in "Statistics for Business Analytics: Data Analysis with Excel" today and start your journey to becoming a data analysis expert.
Who this course is for:
Aspiring data analysts who are interested in developing their expertise in statistics and business analytics
Business professionals who want to develop their data analysis skills to make informed business decisions
Entrepreneurs and small business owners who want to use data analysis to make informed business decisions and grow their businesses
IT professionals who want to develop their skills in data analysis and data modeling to advance their careers
Managers and executives who want to understand the role of data analytics in decision making and lead their teams in data-driven decision making

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Diogo is a data analytics and business analytics professional with years of experience in the field. He has expertise in various methodologies, including time series forecasting for predicting sales trends, econometrics for analyzing economic data, and machine learning for optimizing marketing campaigns. His background includes working for a major e-commerce company, where he used these techniques to drive business growth, and collaborating with the United Nations on a Mobile Money project in Lesotho, where he helped increase financial inclusion in the country. In his courses, Diogo aims to provide practical and applicable knowledge through real-life examples and datasets. For example, he often uses case studies from his own work experiences to illustrate key concepts and demonstrate their relevance in the professional world. His goal is to equip students with the skills and tools necessary to succeed in their own careers in data science.

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