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  Encyclopedia of Keywords > Information > Evaluation > Analysis > Tests > P-Value   Michael Charnine

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  1. A p-value is defined as the probability of rejecting the null hypothesis {The interaction gene x condition is null.}, if true.
  2. A p-value is a measure of how much evidence you have against the null hypothesis.
  3. The P-value is the probability that a z-score will be less than -2.0.
  4. The p-value is the two-tailed probability computed using a t distribution.
  5. The p-value is based on the assumption that the distribution is normal. (Web site)

Hypothesis Test

  1. Now the p-value is approximately 0.13, so we do not reject the hypothesis. (Web site)
  2. P is the p-value of the test, obtained by linear interpolation in a set of table created by Lilliefors. (Web site)
  3. Another way to report the results of a statistical test is to compute a probability value or p-value. (Web site)
  4. However, the p-value is smaller for the one-sided test. (Web site)
  5. In the end, most folks summarize the result of a hypothesis test into one particular value - the p-value. (Web site)


  1. STAR2 = upper bound on p-value for printing two stars (**), when STARS option is on.
  2. The small p-value of 0.001 indicates the popcorn brand affects the yield of popcorn. (Web site)
  3. The first p-value tests whether the dimension is 0, the next whether the dimension is 1, and so on.
  4. If the p-value is not low, there will be a fair amount of overlap between the two groups. (Web site)
  5. The p-value can then be used to make a statement as to whether or not the two data sets are significantly different.


  1. If a test of significance gives a p-value lower than the ---level, the null hypothesis is rejected. (Web site)
  2. The null hypothesis is that the data set is similar to the normal distribution, therefore a sufficiently small P-value indicates non-normal data. (Web site)
  3. One may combine the p-value with the significance level to make decision on a given test of hypothesis.
  4. The p-value is not the probability of falsely rejecting the null hypothesis.


  1. If alpha is omitted, the test statistic is printed and a range for the p-value of the test is given. (Web site)
  2. As might be expected, the rank sum test leads to the same conclusion but it is less sensitive to the difference between samples (higher p-value).
  3. The sum of these approximates the p-value of the test statistic for the two sided alternative.
  4. If the p-value is large, then this indicates that the test statistic is usual (common)---we take this as a lack of evidence against the null hypothesis. (Web site)
  5. Since we have a one-tailed test, the P-value is the probability that the z-score is greater than 1.91.


  1. The equal variances t-test has a p-value of 0.213. (Web site)
  2. The t-test turns the difference in mean cholesterol into a p-value. (Web site)


  1. We can also draw this conclusion by comparing the p-value for a two-tail test and the alpha value. (Web site)
  2. Or, if the p-value is greater than or equal to alpha, then the difference between the numbers could be due to chance alone. (Web site)


  1. The p-value is determined by the observed value, however, this makes it difficult to even state the inverse of p.
  2. This number is used to compute the approximate finite sample P-value or critical value.
  3. The chi-square value was 583.3 with degrees of freedom 215 (P-value < 0.0001).


  1. The specification by year interaction for the #200 sieve had a p-value = 0.03. (Web site)
  2. All the other sieve sizes, including the #200 sieve, had a p-value greater than 0.05. (Web site)


  1. In one example, with three lags, a value of -3.17 constituted rejection at the p-value of .10. (Web site)
  2. Based on where the rejection region is, you must find out what p-value to use. (Web site)
  3. Use of P-value and a: In this setting, we must also consider the alternative hypothesis in drawing the rejection interval (region) . (Web site)


  1. The P-value indicates how likely it is that we would obtain a t-statistic as large as that observed if the null hypothesis is true. (Web site)
  2. B-statistic, t-statistic and P-value (probability) are generated using the R statistical language with Bioconductor and the LIMMA package. (Web site)


  1. A p-value = 0.51 in the ANOVA table indicated that there was no change in VMA variability. (Web site)
  2. The only statistically significant difference, however, is between 1998 and 2000, which is indicated by a p-value = 0.02. (Web site)

False Discovery Rate

  1. Keywords: Multiple hypothesis testing; adjusted p-value; family-wise Type I error rate; false discovery rate; permutation; DNA microarray. (Web site)
  2. The P-value is obtained from moderated t-statistic and after FDR adjustment which is Benjamini and Hochberg's method to control the false discovery rate. (Web site)


  1. If the p-value is significant, appropriate post-hoc multiple comparisons tests would be performed. (Web site)
  2. Example of filters include: number of missing value, coefficient of variation of expression measures, ANOVA p-value, Cox model p-values.
  3. A working paper that explains the difference between Fisher's evidential p-value and the Neyman-Pearson Type I error rate --.
  4. The next table gives the Mantel r statistic, and the corresponding two-tailed p-value, obtained from the 10000 permutations.
  5. To do this, the treatment means need to be looked at (Oehlert, 2000).Unlike interaction plots, a p-value is associated with a contrast. (Web site)


  1. Information > Evaluation > Analysis > Tests
  2. Information > Science > Mathematics > Statistics
  3. Glossaries > Glossary of Statistics /
  4. Books about "P-Value" in

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  Short phrases about "P-Value"
  Originally created: August 16, 2007.
  Links checked: May 31, 2013.
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