What is a 'Type II Error'
A type II error is a statistical term used within the context of hypothesis testing that describes the error that occurs when one accepts a null hypothesis that is actually false. The error rejects the alternative hypothesis, even though it does not occur due to chance. A type II error fails to reject, or accepts, the null hypothesis, although the alternative hypothesis is the true state of nature.
BREAKING DOWN 'Type II Error'
A type II error confirms an idea that should have been rejected, claiming the two observances are the same, even though they are different. When conducting a hypothesis test, the probability, or risks, of making a type I error or type II error should be considered.Differences Between Type I and Type II Errors
The difference between a type II error and a type I error is a type I error rejects the null hypothesis when it is true. The probability of committing a type I error is equal to the level of significance that was set for the hypothesis test. Therefore, if the level of significance is 0.05, there is a 5% chance a type I error may occur.
The probability of committing a type II error is equal to the power of the test, also known as beta. The power of the test could be increased by increasing the sample size, which decreases the risk of committing a type II error.
Hypothesis Testing Example
Assume a biotechnology company wants to compare how effective two of its drugs are for treating diabetes. The null hypothesis states the two medications are equally effective. The alternative hypothesis states the two drugs are not equally effective.
The biotech company implements a large clinical trial of 3,000 patients with diabetes to compare the treatments. The company expects the two drugs to have an equal number of patients to indicate that both drugs are effective. It selects a significance level of 0.05, which indicates it is willing to accept a 5% chance it may reject the null hypothesis when it is true, or a 5% chance of committing a type I error.
Assume the beta is calculated to be 0.025, or 2.5%. Therefore, the probability of committing a type II error is 2.5%. If the two medications are not equal, the null hypothesis should be rejected. However, if the biotech company does not reject the null hypothesis when the drugs are not equally effective, a type II error occurs.

Type I Error
A type of error that occurs when a null hypothesis is rejected ... 
Hypothesis Testing
A process by which an analyst tests a statistical hypothesis. ... 
Alpha Risk
The risk in a statistical test that a null hypothesis will be ... 
Beta Risk
The probability that a false null hypothesis will be accepted ... 
OneTailed Test
A statistical test in which the critical area of a distribution ... 
Accounting Error
An error in an accounting item that was not caused intentionally. ...

Trading
Hypothesis Testing in Finance: Concept & Examples
When you're indecisive about an investment, the best way to keep a cool head might be test various hypotheses using the most relevant statistics. 
Investing
How Statistical Significance is Determined
If something is statistically significant, itâ€™s unlikely that it happened by chance. 
Trading
What's a TTest?
TTest is a term from statistics that allows for the comparison of two data populations and their means. The test is used to see if the two sets of data are significantly different from one another. ... 
ETFs & Mutual Funds
3 Reasons Tracking Error Matters
Discover three ways investors can use tracking error to measure performance for a mutual fund or ETF, whether indexed or actively managed. 
Investing
Efficient Market Hypothesis
An investment theory that states it is impossible to "beat the market". 
Investing
Explaining Standard Error
Standard error is a statistical term that measures the accuracy with which a sample represents a population. 
Investing
10 Steps To Help Erase Errors On Your Credit Report
According to a study conducted by the Federal Trade Commission, one in four consumers identified errors on their reports that might affect their credit rating in 2013. 
Personal Finance
What Does Errors and Omissions Insurance Cover?
Errors and omissions insurance protects companies and individuals against claims made by clients for inadequate work or negligent actions. 
ETFs & Mutual Funds
Efficient Market Hypothesis: Is The Stock Market Efficient?
Deciding whether it's possible to attain aboveaverage returns requires an understanding of EMH. 
Managing Wealth
Top 3 Mistakes That Cause Traders To Fail
Find out how to avoid these common investing errors that have sunk many investors' portfolios.

What does a strong null hypothesis mean?
Find out what null hypothesis is and why it is important to the scientific method. See how statisticians and economists use ... Read Answer >> 
What is the relationship between confidence inferrals and a null hypothesis?
Learn about the relationship between confidence intervals and the null hypothesis in scientific research and empirical experimentation. Read Answer >> 
How is the standard error used in trading?
Understand how the standard error is used in statistics and what it measures. Learn how the standard error is used in trading ... Read Answer >> 
How can I calculate the tracking error of an ETF or indexed mutual fund?
Understand what tracking error is and learn about the significant difference it can represent for investors who favor index ... Read Answer >> 
How do I fix an error on my credit report?
Take control over your credit report by disputing false claims, accounts and information to the three major credit reporting ... Read Answer >> 
Is tracking error a significant measure for determining expost risk?
Before we answer your question, let's first define tracking error and expost risk. Tracking error refers to the amount by ... Read Answer >>