Об этом курсе: 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

Автор: Лондонский университет

Преподаватели: George Kapetanios, Professor of Finance and Econometrics
King's College London

Основные сведения	Course 4 of 6 in the International Business Essentials Specialization
Выполнение	4 weeks of study, 5 hours per week
Язык	English
Как пройти курс	Чтобы пройти курс, выполните все оцениваемые задания.
Оценки пользователей	3.4 звезды Средняя оценка пользователей: 3.4Посмотрите, что пишут учащиеся

Программа курса

НЕДЕЛЯ 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 видео

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

Оцениваемый: Quiz: Categorical and Numerical Variables

Оцениваемый: Peer Review: Using Graphs to Describe Data

Оцениваемый: End of Week Quiz

НЕДЕЛЯ 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.

10 видео

Видео: Introduction- Using Measures to Describe Data
Видео: 1. Descriptive Statistics- Using Measures to Describe Data
Видео: 2. Measures of Central Tendency and Location
Видео: 3. Mean, Median, and Mode- Which is Best?
Видео: 4. Shape of a Distribution
Видео: 5. Measures of Variability
Видео: 5.1 Measures of Variability: Examples
Видео: 6. Weighted Mean
Видео: 7. Measures of Relationships Between Variables
Видео: Summary

Оцениваемый: Summative Questions

Оцениваемый: End of Week Quiz

НЕДЕЛЯ 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 видео

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

Оцениваемый: Summative Questions

Оцениваемый: End of Week Quiz

НЕДЕЛЯ 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.

22 видео, 4 материалов для самостоятельного изучения

Видео: Statistical Estimation - An Introduction
Видео: 1. Statistical Estimation
Видео: 2. Estimator and Estimate
Видео: 2.1. Point Estimator and Point Estimate
Видео: 2.2. Unbiased
Видео: 2.3. Efficiency
Видео: 3. Confidence Interval Estimation
Видео: 3.1 Confidence Intervals, Part 1
Видео: 3.1 Confidence Intervals, Part 2
Видео: 4. Testing Hypothesis
Видео: 4.1. Formulation of the Null Hypothesis and the Alternative Hypothesis
Видео: 4.2. Test Statistic
Видео: 4.2.1. The Decision Rule
Видео: 4.2.2. Types of Errors
Видео: 4.2.3. Performing the Test and the Decision Rule
Видео: 4.2.3.1 Hypothesis Testing: Examples
Reading: Practice exercise
Reading: Solution to practice exercise
Видео: 5. Regression Model
Reading: Practice exercise
Reading: Solutions to practice exercise
Видео: Statistical Estimation - Summary
Видео: 1. Further on the Linear Regression Model
Видео: 2. Deriving the OLS b
Видео: 3.The Statistical Properties of the OLS b
Видео: 4. Gauss-Marcov Theorem Proof

Оцениваемый: End of Week

Оцениваемый: Summative Assignment

Оцениваемый: End of Course Quiz

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Авторы

Лондонский университет

The University of London is a federal University which includes 18 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'.

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