What is a 'P-Test'

A p-test is a statistical method used to assess one or more hypotheses within a population or a proportion within a population.

When testing a hypothesis about a population proportion (p) within a large population, meaning one in which the sample size, "n," is not greater than 5 percent of the overall population, the formula is:

x = (m/n-P) / SqRt[P(1-P)/n]

m= "yes" response

n = random sample size

p = proportion

P = population

This formula is used to test three hypotheses:

  1. p ≤ P

  2. p ≥ P

  3. p = P

The p-test statistic typically follows a standard normal distribution when large sample sizes are used, and researchers use z-tests to determine whether a hypothesis passes based on a specific significance level will be rejected. The larger the p-value in the p-test, the more likely the hypothesis is true.


A p-test can be applied in any number of scenarios. For example, a polling group contacted a group of investors and asked if they felt that the economy would fall into a recession. Of the 1000 people contacted, 700 said that they thought that the economy was heading toward recession.

The researchers then applied the p-test to determine if p ≤ 0.60, p ≥ 0.60, or p = 0.60; basically, what percentage of the population believe that the economy will fall into a recession.

As one website explains, "for a study to be considered significant it needs to pass a statistical test called a p-test. If the p-value, resulting from this test, is less than 0.05 this means that there is less than a 5 percent chance of the results arising due to random chance. Essentially this means that the likelihood of the result being due to the reasons prescribed by the researchers is over 95 percent. This is a high level of probability and means that, if the studies were all carried out correctly, they should have been at least 95 percent repeatable."

How a P-Test Can Help with Picking Good Stocks

An article from The Motley Fool explained the value of being able to parse statistics to truly understand the inner mechanisms of how things operate. That comes especially handy when analyzing stocks, not least, as the Fool explained, those from complex spaces such as biotechnology.

"The success or failure of biotechs depends heavily on statistics used in clinical trials," the website noted. "And few statistical factors are as important as the p-test."

The simplest way to understand p-tests is their focus on probability, the site explains that "in particular, the probability that a hypothesis is true. With clinical trials of a drug, it's critical to ensure that any perceived effectiveness of the drug isn't due to chance. Trials are structured to show statistically what the probability of results being due to chance are."

For investors, a basic working knowledge of how statistics inform clinical trials can help them better understand clinical results, often enabling them to make better assessments of a biotech stock's potential returns.

  1. Regulation P

    Regulation P is one of the regulations which addresses standards ...
  2. Accumulated Earnings and Profits

    Accumulated earnings and profits (E & P) are a corporation's ...
  3. Statistically Significant

    Statistically significant is likelihood that a result or relationship ...
  4. Population

    Population is the entire pool from which a statistical sample ...
  5. Hypothesis Testing

    A process by which an analyst tests a statistical hypothesis. ...
  6. Sampling

    Sampling is a process used in statistical analysis in which a ...
Related Articles
  1. Retirement

    Florida Retirement Hub The Villages is the Fastest Growing U.S. Metro

    Fatstest growing metros have significant chunks of retirees in their population.
  2. Investing

    How to Use Stratified Random Sampling

    Stratified random sampling is a technique best used with a sample population easily broken into distinct subgroups. Samples are then taken from each subgroup based on the ratio of the subgroup’s ...
  3. Investing

    Using DCF In Biotech Valuation

    Valuing firms in this sector can seem like a black art, but there is a systematic way to pin a price on potential.
  4. Investing

    SIRI Down Despite Price Target Increase

    Today, Macquarie increased its price target on SIRI from $4.85 to $5
  5. Financial Advisor

    Keep an Eye on These Emerging Economies

    Emerging markets have been hammered lately, but these three countries (and their large and young populations) are worth monitoring.
  6. Insights

    How Demographics Drive The Economy

    Demographics can have a profound effect on the economy. An aging population coupled with a declining birthrate points to a decline in economic growth.
  7. Investing

    It's No Accident That Drugs Are Expensive

    Branded drugs are expensive in large part because it's expensive and risky to develop them
  8. Insights

    Pharmaceutical Vs. Biotech Investing: Is It Worth The Risk?

    Investopedia explains: Both pharma and biotech stocks are faced with a costly process that, when successful, can produce extremely profitable products. However, the process is unpredictable.
  9. Investing

    Pandora's Plunging Market Value May Shrink Further

    Bad Vibes: The bad news for Pandora may not be over
  10. Managing Wealth

    Getting Rich: What Are Your Odds?

    America is home to some of the richest people in the world - so how good are your chances of joining the ranks of the wealthy?
  1. What are the advantages of using a simple random sample to study a larger population?

    Learn how simple random sampling works and what advantages it offers over other sampling methods when selecting a research ... Read Answer >>
  2. What are the pros and cons of stratified random sampling?

    Stratified random sampling provides a more accurate sampling of a population, but can be disadvantageous when researchers ... Read Answer >>
  3. How do I calculate convexity in Excel?

    Learn how to approximate the effective convexity of a bond using Microsoft Excel using a modified and simpler version of ... Read Answer >>
  4. How do systematic sampling and cluster sampling differ?

    Systematic sampling and cluster sampling differ in how they pull sample points from the population included in the sample. Read Answer >>
  5. 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 >>
  6. Has the Efficient Market Hypothesis been proven correct or incorrect?

    Explore the efficient market hypothesis and understand the extent to which this theory and its conclusions are correct or ... Read Answer >>
Trading Center