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- How to pull up xlminer analysis toolpak excel software#
- How to pull up xlminer analysis toolpak excel free#
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Another way to run the hypothesis test, it is to look at P(T<=t) two-tail, also known as P-value, which represents the probability that t Critical two-tail exceeds the experimental value of t Stat.Īt the beginning of the test, the level of significance was set at α = 0.05 (= 5%). P(T t Critical two-tail (2,306004133), the difference between the two results given by the analysis of the concentrations of solution A and B is significant at the 5% level- H 0, the Null hypothesis, is qualified to be rejected. As indicated in Table 3, there are different parameters but those to consider are highlighted in green and yellow. You can get it from the Add-ons from the Google Sheets page upper menu: Add-ons> Get Add-ons> Search Add-ons and type XLMiner ToolPak.) The test was run by XLMiner ToolPak-Excel Analysis Pak. Table 3 below shows the results for the comparison between the absorbance values of solution A and solution B.
How to pull up xlminer analysis toolpak excel software#
The Critical value can be found in specific tables ( t-distribution critical value tables) or is given by the software test output. If the absolute value or modulus of t is greater than the Critical value, the Null hypothesis can be rejected. Most of the time α is set at 0.05 (or 5%). By using this level of significance, it means that there is a 1 in 20 chance that the Null Hypothesis is rejected when it is true. Before doing a t-test, the level of significance, also known as α, needs to be chosen.
How to pull up xlminer analysis toolpak excel free#
This number indicates the number of values that are free to vary. An important factor that needs to be considered is the number of d egrees of freedom ( df) in case of the t-distribution, df is (n 1+n 2) - 2. In the denominator, s is a pooled estimate of the standard deviation whereas n 1 and n 2 are the sample sizes. In the numerator is the difference between the calculated means. Source: Statistics and Chemometrics for Analytical Chemistry by James N.
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Of course, this is a simulation (solutions were prepared on purpose) but in an actual lab situation details like these can be of value and importance. In fact, although the solutions look to have the same intensity of blue, there could be a chemical difference. But the difference exists and perhaps it is significant enough such that the two solutions are indeed different enough to not be identical. See figure 4 below. Based on sight, it could be that the two aqueous solutions are identical in concentration. The differences among the absorbance and concentration data are small and based on this we could conclude that there is no meaningful difference between the two aqueous solutions.
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Visual observation of the two colored aqueous solutions indicate no perceptible difference between the two solutions. As indicated by the absorbance data, there is a small difference (0,010) between the average absorbance value of the two aqueous solutions and a more numerically sizable difference (0,108μM) between the calculated concentrations of the two aqueous solutions.