A study is statistically significant
if the p-value is less than the pre-specified alpha
. Stated succinctly: A p-value less than alpha is a statistically significant result. A p-value greater than or equal to alpha is not a statistically significant result.
How do you know if evidence is statistically significant?
A p-value less than 0.05 (typically ≤ 0.05) is statistically significant
. … A p-value higher than 0.05 (> 0.05) is not statistically significant and indicates strong evidence for the null hypothesis. This means we retain the null hypothesis and reject the alternative hypothesis.
What makes a research finding statistically significant?
Statistically significant findings indicate
not only that the researchers’ results are unlikely the result of chance
, but also that there is an effect or relationship between the variables being studied in the larger population.
What makes something statistically significant?
A result of an experiment is said to have statistical significance, or be statistically significant,
if it is likely not caused by chance for a given statistical significance level
. … It also means that there is a 5% chance that you could be wrong.
How do you know if a significance is significant?
The level at which one can accept whether an event is statistically significant is known as the significance level. Researchers use a test statistic known as the p-value to determine statistical significance: if
the p-value falls below the significance level
, then the result is statistically significant.
What is significance level in research?
The significance level (also called Type I error rate or the level of statistical significance) refers
to the probability of rejecting a null hypothesis that is in fact true
. … The significance level is sometimes referred to as the probability of obtaining a result by chance alone.
What makes a research finding statistically significant quizlet?
Scientists have decided that
5%
is the cutoff for statistically significant results. This means that in an experiment design, there must be less than a 5% chance that the results occurred by chance. … -is the probability that the study will produce a statistically significant result if the research hypothesis is true.
How do you explain significant difference?
A Significant Difference between two groups or two points in time means that
there is a measurable difference between the groups and that
, statistically, the probability of obtaining that difference by chance is very small (usually less than 5%).
What is an example of statistical significance in psychology?
Such results are informally referred to as ‘statistically significant’. For example, if someone argues that
“there’s only one chance in a thousand this could have happened by coincidence
,” a 0.1% level of statistical significance is being implied. The lower the significance level, the stronger the evidence.
What does p-value signify?
In statistics, the p-value is
the probability of obtaining results at least as extreme as the observed results of a statistical hypothesis test
, assuming that the null hypothesis is correct. … A smaller p-value means that there is stronger evidence in favor of the alternative hypothesis.
How do you know if P-value is significant?
The p-value can be perceived as an oracle that judges our results. If the p-value
is 0.05 or lower, the result is trumpeted as significant
, but if it is higher than 0.05, the result is non-significant and tends to be passed over in silence.
What does significant difference mean in statistics?
A statistically significant difference is simply one where the measurement system
(including sample size, measurement scale, etc.) was capable of detecting a difference
(with a defined level of reliability). Just because a difference is detectable, doesn’t make it important, or unlikely.
How do you test for significant difference?
A t-test
is a type of inferential statistic used to determine if there is a significant difference between the means of two groups, which may be related in certain features. The t-test is one of many tests used for the purpose of hypothesis testing in statistics.
What are three levels of significance?
Popular levels of significance are
10% (0.1), 5% (0.05), 1% (0.01), 0.5% (0.005), and 0.1% (0.001)
. If a test of significance gives a p-value lower than or equal to the significance level, the null hypothesis is rejected at that level.
What does significance level mean in statistics?
The significance level of an event (such as a statistical test) is
the probability that the event could have occurred by chance
. If the level is quite low, that is, the probability of occurring by chance is quite small, we say the event is significant.
What does it mean that the results are not statistically significant for this study?
This means that the results are considered to be „statistically non-significant‟
if the analysis shows that differences as large as (or larger than) the observed difference would be expected to occur by chance more than one out of twenty times (p > 0.05)
.
