Quick Correlation Coefficients vs Bayesian P

The correlation coefficient (commonly noted by the Greek letter rho, ρ) measures the degree to which two sets of numbers are related. The correlation coefficient can range from -1.000 to +1.000 with a 0 indicating that there is no relation between the two sets. A 'slider' data entry option allows rapid creation of numerical data. Additionally, you may use the 'keypad' data entry option to expand the numerical range beyond plus or minus 1,000. In this application, you may relate two or three sets of numbers and the correlations between the sets are shown as ρ(AB), ρ(AC), and ρ(BC), where the letters A, B, and C represent the columns. There must be at least 3 pairs of numbers in any 2 rows for the correlation coefficient to be computed. Zero is a number but 'n/a' is not. If, for example, Column A has 5 rows of numbers and the 6th row is 'n/a' and Column B has 4 rows of numbers and the 5th row is 'n/a', the correlation coefficient, ρ(AB), will be computed for the first 4 pairs of numbers.

Calculate probability of outcomes of clinical trials, by interpreting reported p-values in the context of scientific expectations, using prior probabilities of outcomes and Bayesian thinking. · p-values are frequently misused and misinterpreted ( see American Statistical Association statement on p-values) · Bayesian inference aids interpretation of p-values with reference to prior knowledge of the probability of the experimental outcome · P-value Interpreter permits realistic interpretation of reported p-values from user entered pre-trial probabilities of clinical trial outcomes and p-values for single and sequential trials · "Learn more" buttons lead to explanations of prior probabilities, p-values and Bayesian probabilities employed in calculating the direct probability of the trial outcomes (e.g. null hypothesis being false), illustrated with examples