Moocable is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Data analysis: hypothesis testing

The Open University via OpenLearn

Description

Making decisions about the world based on data requires a process that bridges the gap between unstructured data and the decision. Statistical hypothesis testing helps decision-making by formulating beliefs about the world, including people, organisations or other objects, and formally testing these beliefs.In this free course, you will study the principles of hypothesis testing, including the specification of significance levels, as well as one-sided and two-sided tests. Finally, you will learn how to perform a hypothesis test of the mean of a variable, as well as the proportion of individuals in a dataset with a certain characteristic.You will use spreadsheets throughout the course as the central tool used by professionals for simple data management and analysis.This OpenLearn course is an adapted extract from the Open University course B126 Business data analytics and decision making.

Tags
Cybersecurity Fitness

Syllabus

  • 1 Two types of hypotheses
  • 1.1 Formulating null and alternative hypotheses
  • 1.2 Population mean (µ)
  • 2 Testing with data
  • 3 Alpha (α) levels
  • 4 One-tailed vs two-tailed test
  • 4.1 The normal distribution
  • 4.2 Two-tailed tests
  • 4.3 One-sided tests
  • 4.4 Check your understanding
  • 5 Mean and z-score ranges
  • 5.1 Acceptance and rejection regions
  • 5.2 Test your understanding
  • 5.3 Using the z-score
  • 6 P-value
  • 6.1 Defining the p-value
  • 6.2 Calculating the p-value
  • 6.3 Example: testing a hypothesis
  • 6.4 Test your understanding
  • 7 Hypothesis testing for population proportions
  • 7.1 Example: testing a proportion
  • 7.2 Test your understanding

Start Learning Find study partner
Online Courses
OpenLearn

Data analysis: hypothesis testing

The Open University
Start Learning Find study partner
Affiliate notice

  • Type
    Online Courses
  • Provider
    OpenLearn

Making decisions about the world based on data requires a process that bridges the gap between unstructured data and the decision. Statistical hypothesis testing helps decision-making by formulating beliefs about the world, including people, organisations or other objects, and formally testing these beliefs.In this free course, you will study the principles of hypothesis testing, including the specification of significance levels, as well as one-sided and two-sided tests. Finally, you will learn how to perform a hypothesis test of the mean of a variable, as well as the proportion of individuals in a dataset with a certain characteristic.You will use spreadsheets throughout the course as the central tool used by professionals for simple data management and analysis.This OpenLearn course is an adapted extract from the Open University course B126 Business data analytics and decision making.

  • 1 Two types of hypotheses
  • 1.1 Formulating null and alternative hypotheses
  • 1.2 Population mean (µ)
  • 2 Testing with data
  • 3 Alpha (α) levels
  • 4 One-tailed vs two-tailed test
  • 4.1 The normal distribution
  • 4.2 Two-tailed tests
  • 4.3 One-sided tests
  • 4.4 Check your understanding
  • 5 Mean and z-score ranges
  • 5.1 Acceptance and rejection regions
  • 5.2 Test your understanding
  • 5.3 Using the z-score
  • 6 P-value
  • 6.1 Defining the p-value
  • 6.2 Calculating the p-value
  • 6.3 Example: testing a hypothesis
  • 6.4 Test your understanding
  • 7 Hypothesis testing for population proportions
  • 7.1 Example: testing a proportion
  • 7.2 Test your understanding

Tags

Cybersecurity Fitness

Related Courses

Quick Links

Browse by subject

Browse by provider

Browse by university

Browse by publisher

Browse by institution

Roadmaps

Posts