The p value is a statistical measure used to assess the probability of a given hypothesis being true. It is normaly used in hypothesis testing to determine the likelihood that a given result could have occurred by chance. To find the p-value, we need to know the t score, which measures how many standard deviations a given sample falls from the mean of a population. If the t score is negative, it indicates that the sample falls below the population’s mean. In this case, we will need to use a different method to calculate the p-value than when the t-score is positive.
How to find p value from negative t score?
Determine the degrees of freedom (df)
The first step in calculating the p value from a negative t score is determining the degrees of freedom (df). The degrees of freedom measure the number of observations in a sample that are free to vary. It is typically calculated as the number of observations in the sample minus the number of estimated parameters. For example, if we have a sample of 10 observations and we are estimating 2 parameters, the degrees of freedom would be 10-2=8.
Look up the t score in a t table
Once we have determined the degrees of freedom, we can look up the negative t score in a t table. A t table is a statistical tool that lists the critical values of the t distribution for different degrees of freedom. To find the p-value, we need to look up the t score in the t table and find the corresponding p-value.
Calculate the p-value
Once we have found the t score in the t table, we can calculate the p-value. The p-value is calculated by taking the probability of the t score being equal to or less than the observed t score and multiplying it by 2. This is because the t distribution is symmetrical, so the probability of the t score being more significant than the observed t score is equal to the probability of it being less than the observed t score.
For example, if we have a t score of -2.5 and a df of 8, we can look up the t score in the t table and find that the corresponding p-value is 0.02. To calculate the final p-value, we would multiply this value by 2, giving us a final p-value of 0.04.
Interpret the p Value
Once the p-value has been calculated, the final step is interpreting the result Given that the null hypothesis is true, the p-value is a measurement of the likelihood of receiving a result that is equally extreme or more extreme than the one found in the study.
A p-value of 0.05 or less is generally considered statistically significant, meaning there is a low probability of obtaining the observed result by chance alone. A p-value greater than 0.05 is usually considered to be not statistically significant, meaning that the observed result could be due to chance alone.
Calculating the p-value from a negative t score is a simple process that involves determining the degrees of freedom, and looking up the t score in a t table. Then calculating the final p-value by multiplying the probability of the t score being equal to or less than the observed t score by 2. Following these steps, we can quickly determine the probability that a given hypothesis is actual based on the experimental t score.