Statistics for Business Analysis and Data Science

Details

Description

About This Class

Statistics you need in the office: Descriptive statistics, Inferential Statistics and Hypothesis Testing

Is statistics a driving force in the industry you want to enter? Do you want to work as a Data Analyst, a Business Intelligence Analyst, a Marketing Analyst, Data Scientist or are you a small business owner that needs statistical knowledge for your business?

Well then, you’ve come to the right place!

In no time, you will acquire the fundamental skills that will enable you to understand complicated statistical analysis directly applicable to real-life situations. We have created a course that is:

Easy to understand

Comprehensive

Practical

To the point

Packed with plenty of exercises and resources

Data-driven

Introduces you to the statistical scientific lingo

Teaches you about data visualisation

Shows you the main pillars of quantitative research

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Objectives

How to plot different type of data
To understand the fundamentals of statistics
Learn how to work with different types of data
Calculate the measures of central tendency, asymmetry and variability
Calculate correlation and covarriance
Distinguish and work with different types of distributions
Estimate confidence intervals
Perform hypothesis testing
Make Data Driven Decisions

Instructional level

Multilevel

Requirements

Absolutely no experience is required. We will start from the basics and gradually build up your knowledge. Everything is in the course.
A willingness to learn and practice

Who should take this online course

Who this course is for:

People who want a career in Data Science

People who want a career in Business Intelligence

Business analysts

Business executives

Individuals who are passionate about numbers and quant analysis

Anyone who wants to learn the subtleties of Statistics and how it is used in the business world

People who want to start learning statistics

People who want to learn the fundamentals of statistics

Chapter 1: Chapter 1: Descriptive Statistics
- 1 Lesson 1: Population Vs Sample 04:18 min
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- 2 Lesson 2: Types of Data and Levels of Measurement 08:02 min
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- 3 Lesson 3: Visualisation Techniques for Categorical and Numerical Variables 12:43 min
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- 4 Lesson 4: Calculating Measures of Central Tendency 04:29 min
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- 5 Lesson 5:Calculating Measures of Asymmetry 02:49 min
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- 6 Lesson 6: How to Quantify Variability 05:44 min
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- 7 Lesson 7: Standard Deviation and Coefficient of Variation 04:40 min
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- 8 Lesson 8:Measures of the Relationships between Two Variables 03:33 min
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- 9 Lesson 9: Correlation Coefficient 03:20 min
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Chapter 2: Chapter 2: Inferential Statistics
- 1 Lesson 1: Distribution 05:08 min
- 2 Lesson 2:Normal Distribution 03:54 min
- 3 Lesson 3: Standardisation 03:13 min
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- 4 Lesson 4:Central Limit Theorem 03:57 min
- 5 Lesson 5:Standard Error 01:20 min
- 6 Lesson 6:Estimators and Estimates 05:03 min
- 7 Lesson 7: Confidence Intervals 05:53 min
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- 8 Lesson 8:Confidence Intervals Clarification with Student's T D 06:50 min
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- 9 Lesson 9: Population Variance Unknown 08:40 min
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Chapter 3: Chapter 3: Hypothesis Testing
- 1 Lesson 1: The Null and Alternative Hypothesis 04:46 min
- 2 Lesson 2: Establishing a Rejection Region 06:29 min
- 3 Lesson 3:Type 1 and Type 11 Error 01:40 min
- 4 Lesson 4:Test for the Mean Population Variance Known 05:30 min
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- 5 Lesson 5:What is the P-Value and Why is it an Important tool in Statistics 04:10 min
- 6 Lesson 6: Test for the Mean Population Variance Unknown 04:30 min
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- 7 Lesson 7: Test for the Mean Dependent Sample 05:07 min
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- 8 Lesson 8:Test for the Mean Independent Sample Part 1 04:14 min
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- 9 Lesson 9: Test for the Mean Independent Sample Part 2 03:49 min
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The Teachlr

KARIMAT LOUIS-MAALIK

Business Intelligence Analyst/Data Scientist