The training program is comprehensive training for engineers, supervisors and middle-level managers to clarify statistical concepts and know-how of data analysis tools and techniques using JMP.ĬSense experts have designed this workshop to cover the statistical tools used in different stages of Data Analysis. shows how to use JMP to determine whether the equal-variances or unequal- variances t-test is appropriate, and how to interpret the results. Proceeds to examine more advance methods, from regression and. Example: Leukemia Survival Data (Section 10 p. We calculate our test statistic as: t Difference Standard Error 1.40 0.456 3.07 t Difference Standard Error 1.40 0.456 3. Most regression products dont do lack-of-fit tests. Step 5 - Find the degree of freedom (df) using Eq-2. We now have the pieces for our test statistic. For example, JMP treats lack-of-fit in regression the same as it does goodness-of-fit in categorical models. (D)2 Step 4 - Put the values found from Steps 1-3 in Eq-4 and find the t-value. (D2) Step 3 - Find the square of summation of D. D (A-B) Step 2 - Find the sum of square of each D found in Step 1. Data Analysis or is a statistics-based family of tools that we use to monitor, control, and improve processes, based on the either Six Sigma DMAIC or SPC framework.Ĭonceptually, it is applying the statistical technique to achieve control over the processes to improve their reliability and predictability. models covered by R, beginning with simple classical tests such as chi-square and t-test. The regression coecient in the population model is the log(OR), hence the OR is obtained by exponentiating, e elog(OR) OR Remark: If we t this simple logistic model to a 2 X 2 table, the estimated unadjusted OR (above) and the regression coecient for x have the same relationship. Step 1 - Find the sum of difference of each two samples in data.
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