About this Course
3.6
100 ratings
27 reviews
Specialization
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100% online

Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Hours to complete

Approx. 17 hours to complete

Suggested: 4 weeks of study, 5 hours per week...
Available languages

English

Subtitles: English...
Specialization
100% online

100% online

Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Hours to complete

Approx. 17 hours to complete

Suggested: 4 weeks of study, 5 hours per week...
Available languages

English

Subtitles: English...

Syllabus - What you will learn from this course

Week
1
Hours to complete
3 hours to complete

Using Graphs to Describe Data

In our study of statistics, we learn many methods to help us summarize, analyze, and interpret data with the aim of making informed decisions in an uncertain environment. In this first week we introduce tables and graphs that help us get a handle of data. These tools provide visual support for better decision making. With this in mind, we will guide you through the concept of decisions based on incomplete information. Beginning from here, we will introduce you to the concept of population vs. sample, of parameter vs. statistic and of descriptive statistics vs. inferential statistics. We will then go through the concept of describing data, and we will introduce the idea of creating and interpreting graphs to describe categorical and continuous random variables. ...
Reading
9 videos (Total 42 min), 3 quizzes
Video9 videos
Introduction - Using graphs to describe data3m
1. Decision Making in an Uncertain Environment3m
2. Population and Sample4m
3. Parameters and Statistics3m
4. Descriptive and Inferential Statistics11m
5. Graphs to Describe Numerical Values7m
6. Shape of a Distribution2m
Summary2m
Quiz2 practice exercises
Quiz: Categorical and Numerical Variables8m
End of Week Quiz10m
Week
2
Hours to complete
1 hour to complete

Using Measures to Describe Data

This week we will describe and summarize the information in the data using numerical values or measures that are able to summarise information. This is a crucial extension to the analysis of the previous week. While graphs are informative it is usually crucial for improved understanding of the data at hand to discuss their numerical properties. In this week, we will look at a range of measures, such as measures of central tendency, the range, variance, standard deviation, and so on....
Reading
10 videos (Total 55 min), 2 quizzes
Video10 videos
1. Descriptive Statistics- Using Measures to Describe Data3m
2. Measures of Central Tendency and Location8m
3. Mean, Median, and Mode- Which is Best?3m
4. Shape of a Distribution5m
5. Measures of Variability12m
5.1 Measures of Variability: Examples9m
6. Weighted Mean1m
7. Measures of Relationships Between Variables4m
Summary2m
Quiz2 practice exercises
Summative Questions12m
End of Week Quiz10m
Week
3
Hours to complete
1 hour to complete

Probability and Probability Distributions

Probability theory is a young arrival in mathematics- and probability applied to practice is almost non-existent as a discipline. We should all understand probability, and this lecture will help you to do that. It’s important for you to understand first that the world in which your future occurs is not deterministic- and there are future outcomes where a probability model cannot be developed… This week, we will cover the basic definition of probability, the rules of probability,random variables, -probability density functions, expectations of a random variable and Bivariate random variables. ...
Reading
18 videos (Total 43 min), 2 quizzes
Video18 videos
1. Introduction1m
2. Random Experiment2m
3. Events4m
4: Probability1m
4.1: The Definition of Probability3m
4.2: Probability Rules1m
4.3: The Addition Rule of Probabilities2m
4.4: Conditional Probability2m
4.5: The Multiplication Rule of Probabilitiesm
5: Random Variables2m
5.1: The Probability Distribution Function2m
6: Properties of Discrete Random Variables1m
6.1: The Variance of a Discrete Random Variable1m
7. Continuous Random Variables3m
8. The Probability Density Function1m
9. The Expectations for Continuous Random Variables3m
Probability and Probability Distributions - Summary2m
Quiz2 practice exercises
Summative Questions10m
End of Week Quiz10m
Week
4
Hours to complete
5 hours to complete

Statistical Estimation

For statistical analysis to work properly, it’s essential to have a proper sample, drawn from a population of items of interest that have measured characteristics. This week, we will cover statistical estimation, sampling distribution of the mean, point estimation, interval estimation, hypothesis testing, the Null hypothesis and look at some real life examples of their use. ...
Reading
22 videos (Total 84 min), 4 readings, 3 quizzes
Video22 videos
1. Statistical Estimationm
2. Estimator and Estimate1m
2.1. Point Estimator and Point Estimate1m
2.2. Unbiased2m
2.3. Efficiency2m
3. Confidence Interval Estimation4m
3.1 Confidence Intervals, Part 112m
3.1 Confidence Intervals, Part 24m
4. Testing Hypothesis2m
4.1. Formulation of the Null Hypothesis and the Alternative Hypothesis3m
4.2. Test Statisticm
4.2.1. The Decision Rule2m
4.2.2. Types of Errors1m
4.2.3. Performing the Test and the Decision Rule3m
4.2.3.1 Hypothesis Testing: Examples7m
5. Regression Model5m
Statistical Estimation - Summary3m
1. Further on the Linear Regression Model3m
2. Deriving the OLS b2m
3.The Statistical Properties of the OLS b4m
4. Gauss-Marcov Theorem Proof3m
Reading4 readings
Practice exercise10m
Solution to practice exercise10m
Practice exercise10m
Solutions to practice exercise10m
Quiz2 practice exercises
End of Week8m
End of Course Quiz56m
3.6
27 ReviewsChevron Right

Top Reviews

By AMAug 17th 2017

Very challenging , kind of forgetting my college statistics

Instructor

Avatar

George Kapetanios

Professor of Finance and Econometrics
King's College London

About University of London

The University of London is a federal University which includes 18 world leading Colleges. Our distance learning programmes were founded in 1858 and have enriched the lives of thousands of students, delivering high quality University of London degrees wherever our students are across the globe. Our alumni include 7 Nobel Prize winners. Today, we are a global leader in distance and flexible study, offering degree programmes to over 50,000 students in over 180 countries. To find out more about studying for one of our degrees where you are, visit www.london.ac.uk...

About the International Business Essentials Specialization

This specialisation from the University of London is designed to help you develop and build the essential business, academic, and cultural skills necessary to succeed in further study and in international business. If completed successfully, you may be able to use your certificate from this specialisation as part of the application process for the University of London Global MBA. This Specialisation is endorsed by CMI....
International Business Essentials

Frequently Asked Questions

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  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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