Loading the player...

What is 'Statistically Significant'

Statistically significant is the likelihood that a relationship between two or more variables is caused by something other than chance. Statistical hypothesis testing is used to determine whether the result of a data set is statistically significant. This test provides a p-value, representing the probability that random chance could explain the result; in general, a p-value of 5% or lower is considered to be statistically significant.

BREAKING DOWN 'Statistically Significant'

Statistical significance is used to accept or reject the null hypothesis, which hypothesizes that there is no relationship between measured variables.  A data set is statistically significant when the set is large enough to accurately represent the phenomenon or population sample being studied. A data set is typically deemed to be statistically significant if the probability of the phenomenon being random is less than 1/20, resulting in a p-value of 5%. When the test result exceeds the p-value, the null hypothesis is accepted.  When the test result is less than the p-value, the null hypothesis is rejected.

Statistically Significant Data in Theory

Suppose Joe Sample works for a company that manufactures running shoes. For optimal production, he considers how many shoes should be made in each sex's size. Joe does not rely on anecdotal evidence that males have bigger sizes relative to females; he opts to use statistical study that shows the correlation between sex and foot size to make accurate forecasts. 

If the study's p-value was 2% (<5%), it would have a statistically significant result. The p-value indicates there is only a 2% chance that the connection between foot size and gender was the result of chance.  He could then reasonably use the study's data to prepare his company's production plans. On the other hand, if the p-value was 6% (>5%), it would not be reasonable to use the study as a basis for his production plans. So, if the study with the 2% p-value said that most men have shoe sizes between 8 and 12 and women have shoe sizes between 4 and 8, he could develop plans to produce most of the shoes in those sizes.

Statistically Significant Data in Practice

Often, the idea of statistical significance is used for new pharmaceutical drug trials, to test vaccines, and in the study of pathology. This is important for two reasons: The first is that the drug is tested for effectiveness, and the second is that it tells investors how successful the company is at releasing new products.

For example, Novo Nordisk, the pharmaceutical leader in diabetes medication, reported that there was a statistically significant reduction in type 1 diabetes when it tested its new insulin. The test consisted of 26 weeks of randomized therapy among diabetes patients; the result was a reduction in type 1 diabetes and a p-value of less than 5%, meaning that the reduction in diabetes was not due to random chance.

RELATED TERMS
  1. P-Value

    The level of marginal significance within a statistical hypothesis ...
  2. Hypothesis Testing

    A process by which an analyst tests a statistical hypothesis. ...
  3. Runs Test

    A runs test is a statistical technique to test the hypothesis ...
  4. Beta Risk

    Beta risk is the probability that a false null hypothesis will ...
  5. Z-Test

    A z-test is a statistical test used to determine whether two ...
  6. Random Factor Analysis

    Random factor analysis is a statistical technique to decipher ...
Related Articles
  1. Investing

    Hypothesis testing in finance: Concept and 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.
  2. Insights

    Can Investors Trust Official Statistics?

    The official statistics in some countries need to be taken with a grain of salt. Find out why you should be skeptical.
  3. Investing

    Investing For The Diabetes Epidemic

    Sadly, diabetes is quickly becoming a global epidemic. Nearly 300 million people suffer from the disease worldwide.
  4. Investing

    Roche Restructuring Shows Trouble in US Diabetes Biz

    Roche announced a reorganization and job cuts as the U.S. diabetes market continues to struggle.
  5. Investing

    Novel Diabetes Drugs Improve Heart Protection

    SGLT-2 inhibitors have been found to protect Type 2 diabetics from heart ailments.
  6. Trading

    Financial Markets: Random, Cyclical or Both?

    Are the markets random or cyclical? Depends on whom you ask. We look at both sides of the argument.
  7. Investing

    Novo’s Basal Insulin Gets CHMP Nod to Update Label

    Novo’s next-gen basal insulin, Tresiba, got a positive opinion from an EU body to update its label.
  8. Trading

    The Seasonality Of The U.S. Dollar

    The long-term history of the U.S. dollar suggests that it is often stronger earlier in the year.
  9. Investing

    Is This Diabetes Stock a Better Bet Than MannKind? (MNKD, NVO)

    MannKind's (NASDAQ: MNKD) inhaled insulin, Afrezza, is incredibly intriguing, but Novo Nordisk's (NYSE: NVO) long-standing dominance in diabetes treatment and its research to develop insulin ...
RELATED FAQS
  1. What are the disadvantages of using a simple random sample to approximate a larger ...

    Learn here what a simple random sample is, how researchers use it as a statistical tool and the disadvantages it carries ... Read Answer >>
  2. 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 >>
  3. 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 >>
  4. Do financial advisors get drug tested?

    Financial advisor regulatory bodies do not require drug testing but many individual firms that hire advisors do. Read Answer >>
  5. What's an example of stratified random sampling?

    Stratified random sampling divides a population into subgroups or strata, whereby the members in each of the stratum formed ... Read Answer >>
  6. What is the "random walk theory" and what does it mean for investors?

    The random walk theory is the occurrence of an event determined by a series of random movements - in other words, events ... Read Answer >>
Trading Center