What is a 'Two-Tailed Test'

A two-tailed test is a statistical test in which the critical area of a distribution is two-sided and tests whether a sample is greater than or less than a certain range of values. If the sample being tested falls into either of the critical areas, the alternative hypothesis is accepted instead of the null hypothesis. The two-tailed test gets its name from testing the area under both tails of a normal distribution, although the test can be used in other non-normal distributions.

BREAKING DOWN 'Two-Tailed Test'

A basic concept of inferential statistics is the hypothesis testing, which is run to determine whether a claim is true or not, given a population parameter. A testing that is programmed to show whether the mean of a sample is significantly greater than and significantly less than the mean of a population is referred to as a two-tailed test.

A two-tailed test is designed to examine both sides of a specified data range as designated by the probability distribution involved. The probability distribution should represent the likelihood of a specified outcome based on predetermined standards. This requires the setting of a limit designating the highest (or upper) and lowest (or lower) accepted variable values included within the range. Any data point that exists above the upper limit or below the lower limit is considered out of the acceptance range and in an area referred to as the rejection range.

There is no inherent standard in regards to the number of data points that must exist within the acceptance range. In instances where precision is required, such as in the creation of pharmaceutical drugs, a rejection rate of 0.001% or less may be instituted. In instances where precision is less critical, such as the number of food items in a product bag, a rejection rate of 5% may be appropriate.

Using a Two-Tailed Test

A two-tailed test can be used during certain production activities, such as with the production and packaging of candy at a particular facility. If the production facility designates 50 candies per bag as its goal, with an acceptable distribution of 45 to 55 candies, any bag found with an amount below 45 or above 55 is considered within the rejection range.

Random Sampling

To confirm the packaging mechanisms are properly calibrated to meet the expected output, a random sampling may be taken to confirm accuracy. For the packaging mechanisms to be considered accurate, an average of 50 candies per bag with an appropriate distribution is desired. Additionally, the number of bags that fall within the rejection range need to fall within the probability distribution limit considered acceptable as an error rate.

If an unacceptable rejection rate is discovered, or an average deviating too far from the desired mean, adjustments to the facility or associated equipment may be required to correct the error. Regular use of two-tailed testing methods can help ensure production stays within limits over the long term.

One-Tailed Test

When a hypothesis test is set up to show that the sample mean would be higher or lower than the population mean, this is referred to as a one-tailed test. The one-tailed test gets its name from testing the area under one of the tails (sides) of a normal distribution. When using a one-tailed test, an analyst is testing for the possibility of the relationship in one direction of interest, and completely disregarding the possibility of a relationship in another direction.

  1. Acceptance Testing

    Acceptance testing, in the engineering and software industries, ...
  2. Runs Test

    A runs test is a statistical technique to test the hypothesis ...
  3. Z-Test

    A z-test is a statistical test used to determine whether two ...
  4. Cost Test

    A cost test is an analysis applied to a process to determine ...
  5. Type I Error

    A type I error is a kind of error that occurs when a null hypothesis ...
  6. Sampling Distribution

    A sampling distribution is a probability distribution of a statistic ...
Related Articles
  1. Personal Finance

    2 Ways To Finish Undergraduate And MBA Programs Faster

    Testing out of courses and challenging course credit decisions can allow you to save money and time at college.
  2. Investing

    CPA Exam Tips

    Tips for the CPA exam - how to approach it, what to expect, and the time it takes to complete.
  3. Investing

    Stock Market Risk: Wagging The Tails

    The bell curve is an excellent way to evaluate stock market risk over the long term.
  4. Investing

    Optimize your portfolio using normal distribution

    Normal or bell curve distribution can be used in portfolio theory to help portfolio managers maximize return and minimize risk.
  5. Trading

    Four Stocks For Range Traders

    These four stocks are locked in ranges, offering low risk and high reward opportunities if the ranges continue.
  6. Personal Finance

    Birch Box Review: Is It Worth It?

    Learn more about the convenience of the subscription beauty box industry, and discover why the Birchbox company in particular has become so popular.
  7. Financial Advisor

    LabCorp's Challenges Ahead (DGX, LH)

    LabCorp, the second largest clinical lab company, faces many challenges. Regulatory changes, reimbursement cuts, strong competition and the inability to set price all impact profitability.
  8. Trading

    Trading with Gaussian models of statistics

    The study of statistics originated from Carl Friedrich Gauss and helps us understand markets, prices and probabilities, among other applications.
  9. Trading

    Beginner Trading Fundamentals

  10. Trading

    Gauging Entry and Exit Signals With Range Bars

    Price bars often generate important signals that traders can use for timely entry or exit.
  1. Can your insurance company drug test you?

    Learn why insurance companies conduct drug tests and how a lifestyle free of drugs can save you big money on health and life ... Read Answer >>
  2. When is it better to use systematic over simple random sampling?

    Learn when systematic sampling is better than simple random sampling, such as in the absence of data patterns and when there ... Read Answer >>
  3. What assumptions are made when conducting a t-test?

    Learn what a t-test is and discover the five standard assumptions made regarding the validity of sampling and data used in ... Read Answer >>
  4. What is stress testing in Value at Risk (VaR)?

    Discover the difference between Value at Risk, or VaR, and stress testing, and learn how the two concepts might be used together ... Read Answer >>
  5. How do I calculate the standard error using Matlab?

    Learn how to calculate the standard error for a sample statistical measure, such as the sample mean, using standard Matlab ... Read Answer >>
Trading Center