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A p value is a probability associated with your critical value. The following figure shows the locations of a test statistic and their corresponding conclusions.

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Hypothesis testing can seem like a plug and chug operation but that can take you only so far.

P values for dummies. Consequently a low p value indicates that you were unlikely to obtain the sample data that was collected if the null is true. A p value of 012 indicates that the difference observed would only be seen about 1 2 of the time if there really is no difference in the entire customer population. Some examples of p values are 012 21 or 0001.

The critical value depends on the probability you are allowing for a type i error. Biostatistics for dummies by john pezzullo the end result of a statistical significance test is a p value which represents the probability that random fluctuations alone could have generated results that differed from the null hypothesis h 0 in the direction of the alternate hypothesis h alt by at least as much as what you observed in your data. It s a probability of obtaining your data assuming the null is true.

By consumer dummies. Calculate p values in the following problems. Remember that a small p value comes from a large test statistic and both mean rejecting h 0.

A small p value typically 0 05 indicates strong evidence against the null hypothesis so you reject the null hypothesis. It measures the chance of getting results at least as strong as yours if the claim h 0 were true. The p value is a number between 0 and 1 and interpreted in the following way.

P values represent the probability of obtaining the effect observed in your sample or more extreme if the null hypothesis is true. All hypothesis tests ultimately use a p value to weigh the strength of the evidence what the data are telling you about the population.