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P Values.
The P value, or calculated probability, is the probability of finding the observed, or more extreme, results when the null hypothesis (H 0 ) of a study question is true – the definition of ‘extreme’ depends on how the hypothesis is being tested. P is also described in terms of rejecting H 0 when it is actually true, however, it is not a direct probability of this state.
The null hypothesis is usually an hypothesis of "no difference" e.g. no difference between blood pressures in group A and group B. Define a null hypothesis for each study question clearly before the start of your study.
The only situation in which you should use a one sided P value is when a large change in an unexpected direction would have absolutely no relevance to your study. This situation is unusual; if you are in any doubt then use a two sided P value.
The term significance level (alpha) is used to refer to a pre-chosen probability and the term "P value" is used to indicate a probability that you calculate after a given study.
The alternative hypothesis (H 1 ) is the opposite of the null hypothesis; in plain language terms this is usually the hypothesis you set out to investigate. For example, question is "is there a significant (not due to chance) difference in blood pressures between groups A and B if we give group A the test drug and group B a sugar pill?" and alternative hypothesis is " there is a difference in blood pressures between groups A and B if we give group A the test drug and group B a sugar pill".
If your P value is less than the chosen significance level then you reject the null hypothesis i.e. accept that your sample gives reasonable evidence to support the alternative hypothesis. It does NOT imply a "meaningful" or "important" difference; that is for you to decide when considering the real-world relevance of your result.
The choice of significance level at which you reject H 0 is arbitrary. Conventionally the 5% (less than 1 in 20 chance of being wrong), 1% and 0.1% (P DECISION TRUTH Accept H 0 :
If you are interested in further details of probability and sampling theory at this point then please refer to one of the general texts listed in the reference section.
You must understand confidence intervals if you intend to quote P values in reports and papers. Statistical referees of scientific journals expect authors to quote confidence intervals with greater prominence than P values.
Notes about Type I error :
is the incorrect rejection of the null hypothesis maximum probability is set in advance as alpha is not affected by sample size as it is set in advance increases with the number of tests or end points (i.e. do 20 rejections of H 0 and 1 is likely to be wrongly significant for alpha = 0.05)
Notes about Type II error :
is the incorrect acceptance of the null hypothesis probability is beta beta depends upon sample size and alpha can't be estimated except as a function of the true population effect beta gets smaller as the sample size gets larger beta gets smaller as the number of tests or end points increases.
Copyright Р’В© 2000-2020 StatsDirect Limited, all rights reserved. Download a free trial here .


The correct way to report p values.
In general, p values tell readers only whether any difference between groups, relationship, etc., is likely to be due to chance or to the variable(s) you are studying. According to most statistical guidelines, including those provided by Nature, you need to provide a p value for any change, difference, or relationship called “significant.” Further, because the significance threshold (i.e., the p value that you use as a cutoff for determining significance) can be .05, .001, or .01, it’s advisable to state the significance threshold used in your research in the Methods section of your paper. A sentence like “The significance threshold was set at .05” is all that is required.
However, a p value cannot tell readers the strength or size of an effect, change, or relationship. Therefore, you should avoid reporting nothing else but p values. It’s always a good idea to provide a test statistic ( t, F , U , etc.), correlation or regression coefficient (Pearson’s r, Spearman’s rho, etc.), or measure of effect size (eta-squared, partial-eta-squared, omega-squared, etc.).
Let’s take the example of the sentence “We found a significant relationship between anxiety and job satisfaction ( p.
Here’s another example: “We found a significant difference between pretest and posttest scores.” I would recommend reporting (a) the test statistic so that the reader knows what statistical test you performed to examine this difference and (b) a measure of effect size so that the reader understands how large this difference is. Even the mean pretest and posttest scores could be sufficient for readers to understand the size of the effect you have found.
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In addition, it’s a good idea to report exact p values, since this practice makes for greater scientific integrity. In the above sentence, the p value could be “.048”; this value is technically below “.05” but so close to .05 that it would probably need to be treated like a p value of .51, which is not statistically significant. Typically, if the exact p value is less than .001, you can merely state “p p values, especially for primary outcomes.
Furthermore, here are a couple of basic errors I’ve come across with regard to p values:
1. “ p = .00” or “ p.
Technically, p values cannot equal 0. Some statistical programs do give you p values of .000 in their output, but this is likely due to automatic rounding off or truncation to a preset number of digits after the decimal point. So, consider replacing " p = .000" with " p.
Many journals accept p values that are expressed in relational terms with the alpha value (the statistical significance threshold), that is, “ p ) or less than (
One last tip: Many authorities in scientific, technical, and medical fields recommend that a zero should not be inserted before a decimal fraction when the number cannot be greater than 1 (e.g., correlations, proportions, and levels of statistical significance); that is, “ p.
Do write in a comment with any further questions you may have.




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