Statistics for International Business

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  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

About this course: This course introduces core areas of statistics that will be useful in business and for several MBA modules. It covers a variety of ways to present data, probability, and statistical estimation. You can test your understanding as you progress, while more advanced content is available if you want to push yourself. This course forms part of a specialisation from the University of London designed to help you develop and build the essential business, academic, and cultural skills necessary to succeed in international business, or in further study. If completed successfully, your certificate from this specialisation can also be used as part of the application process for t…

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When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

About this course: This course introduces core areas of statistics that will be useful in business and for several MBA modules. It covers a variety of ways to present data, probability, and statistical estimation. You can test your understanding as you progress, while more advanced content is available if you want to push yourself. This course forms part of a specialisation from the University of London designed to help you develop and build the essential business, academic, and cultural skills necessary to succeed in international business, or in further study. If completed successfully, your certificate from this specialisation can also be used as part of the application process for the University of London Global MBA programme, particularly for early career applicants. If you would like more information about the Global MBA, please visit www.londoninternational.ac.uk/mba This course is endorsed by CMI

Created by:  University of London
  • Taught by:  George Kapetanios, Professor of Finance and Econometrics

    King's College London
Basic Info Course 4 of 6 in the International Business Essentials Specialization Commitment 4 weeks of study, 5 hours per week Language English How To Pass Pass all graded assignments to complete the course. User Ratings 3.5 stars Average User Rating 3.5See what learners said Задания курса

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University of London The University of London is a federal University which includes 17 world leading Colleges. Our International 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, search for 'London International'.

Syllabus


WEEK 1


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.


9 videos expand


  1. Video: Welcome to Statistics for International Business
  2. Video: Introduction - Using graphs to describe data
  3. Video: 1. Decision Making in an Uncertain Environment
  4. Video: 2. Population and Sample
  5. Video: 3. Parameters and Statistics
  6. Video: 4. Descriptive and Inferential Statistics
  7. Video: 5. Graphs to Describe Numerical Values
  8. Video: 6. Shape of a Distribution
  9. Video: Summary

Graded: Quiz: Categorical and Numerical Variables
Graded: Peer Review: Using Graphs to Describe Data
Graded: End of Week Quiz

WEEK 2


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.


9 videos expand


  1. Video: Introduction- Using Measures to Describe Data
  2. Video: 1. Descriptive Statistics- Using Measures to Describe Data
  3. Video: 2. Measures of Central Tendency and Location
  4. Video: 3. Mean, Median, and Mode- Which is Best?
  5. Video: 4. Shape of a Distribution
  6. Video: 5. Measures of Variability
  7. Video: 6. Weighted Mean
  8. Video: 7. Measures of Relationships Between Variables
  9. Video: Summary

Graded: Summative Questions
Graded: End of Week Quiz

WEEK 3


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.


18 videos expand


  1. Video: Probability and Probability Distributions - An Introduction
  2. Video: 1. Introduction
  3. Video: 2. Random Experiment
  4. Video: 3. Events
  5. Video: 4: Probability
  6. Video: 4.1: The Definition of Probability
  7. Video: 4.2: Probability Rules
  8. Video: 4.3: The Addition Rule of Probabilities
  9. Video: 4.4: Conditional Probability
  10. Video: 4.5: The Multiplication Rule of Probabilities
  11. Video: 5: Random Variables
  12. Video: 5.1: The Probability Distribution Function
  13. Video: 6: Properties of Discrete Random Variables
  14. Video: 6.1: The Variance of a Discrete Random Variable
  15. Video: 7. Continuous Random Variables
  16. Video: 8. The Probability Density Function
  17. Video: 9. The Expectations for Continuous Random Variables
  18. Video: Probability and Probability Distributions - Summary

Graded: Summative Questions
Graded: End of Week Quiz

WEEK 4


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.


19 videos, 4 readings expand


  1. Video: Statistical Estimation - An Introduction
  2. Video: 1. Statistical Estimation
  3. Video: 2. Estimator and Estimate
  4. Video: 2.1. Point Estimator and Point Estimate
  5. Video: 2.2. Unbiased
  6. Video: 2.3. Efficiency
  7. Video: 3. Confidence Interval Estimation
  8. Video: 4. Testing Hypothesis
  9. Video: 4.1. Formulation of the Null Hypothesis and the Alternative Hypothesis
  10. Video: 4.2. Test Statistic
  11. Video: 4.2.1. The Decision Rule
  12. Video: 4.2.2. Types of Errors
  13. Video: 4.2.3. Performing the Test and the Decision Rule
  14. Материал для самостоятельного изучения: Practice exercise
  15. Материал для самостоятельного изучения: Solution to practice exercise
  16. Video: 5. Regression Model
  17. Материал для самостоятельного изучения: Practice exercise
  18. Материал для самостоятельного изучения: Solutions to practice exercise
  19. Video: Statistical Estimation - Summary
  20. Video: 1. Further on the Linear Regression Model
  21. Video: 2. Deriving the OLS b
  22. Video: 3.The Statistical Properties of the OLS b
  23. Video: 4. Gauss-Marcov Theorem Proof

Graded: End of Week
Graded: Summative Assignment
Graded: End of Course Quiz
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