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Want to study MBA? Worried how to do data analysis? The [course_title] course teaches you the data analysis process that will help you to your MBA study. At first, you will learn how to present and summarise your data. Then, you will learn data-based decision making and modelling for decision making

The purpose of the course is to teaches you essential data analysis skill so that you can able to effort your MBA curriculum.

Assessment

This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.

Certification

Edukite courses are free to study. To successfully complete a course you must submit all the assignment of the course as part of the assessment. Upon successful completion of a course, you can choose to make your achievement formal by obtaining your Certificate at a cost of £49.

Having an Official Edukite Certification is a great way to celebrate and share your success. You can:

  • Add the certificate to your CV or resume and brighten up your career
  • Show it to prove your success

 

Course Credit: Imperial College London

Course Curriculum

Module: 1
Welcome 00:03:00
1.1 Introduction a 00:02:00
1.1 Introduction b 00:03:00
1.2 Sourcing good data a 00:02:00
1.2 Sourcing good data b 00:06:00
1.2 Sourcing good data c 00:04:00
1.2 Sourcing good data d 00:02:00
1.6 Measures of central tendency 00:03:00
Module: 2
2.2 Review of set theory 00:04:00
2.6 Probability trees 00:01:00
2.7 Decision trees 00:01:00
Module: 3
3.1 Introduction 00:02:00
3.3 The normal distribution 00:02:00
3.4 Using the normal distribution to find the probability of a range of values a 00:04:00
3.4 Using the normal distribution to find the probability of a range of values b 00:07:00
3.5 Sampling from a wider population a 00:03:00
3.5 Sampling from a wider population b 00:02:00
3.5 Sampling from a wider population c 00:01:00
3.5 Sampling from a wider population d 00:02:00
3.5 Sampling from a wider population e 00:02:00
3.5 Sampling from a wider population f 00:02:00
3.5 Sampling from a wider population g 00:02:00
3.6 Confidence intervals: Estimating population parameters using sample statistics a 00:05:00
3.6 Confidence intervals: Estimating population parameters using sample statistics b 00:05:00
3.7 Hypothesis testing: Introduction 00:01:00
3.9 Hypothesis testing: two types of error a 00:02:00
3.9 Hypothesis testing: two types of error b 00:01:00
Module: 4
4.1 Introduction a 00:02:00
4.1 Introduction b 00:02:00
4.2 Correlation a 00:06:00
4.2 Correlation b 00:04:00
4.2 Correlation c 00:04:00
4.4 Correlation: Spurious relationships and notions of causality a 00:03:00
4.4 Correlation: Spurious relationships and notions of causality b 00:03:00
4.5 Regression: Linear regression a 00:05:00
4.5 Regression: Linear regression b 00:05:00
4.6 Regression: Establishing whether the relationship is statistically significant 00:03:00
4.7 Regression: Introduction to multiple regression 00:03:00
4.8 On your MBA: The CAPM 00:02:00
Assessment
Submit Your Assignment 00:00:00
Certification 00:00:00

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