#HOW TO OPEN XLMINER ANALYSIS TOOLPAK SOFTWARE#
#HOW TO OPEN XLMINER ANALYSIS TOOLPAK FREE#

We can concludeВ that solution A and solution BВ are different. So, for the following t-test, the option вЂњ t-test: two sample assuming equal variancesвЂќ is chosen.В Conversely, if the Null hypothesis was rejected, then the option вЂњ t-test: two sample assuming unequal variances' would have been chosen. The level of significance, О±, for the test is 0.05 whereas the probability that the F value is smaller than the F Critical one-tail is 0.446519679, which is much larger thanВ О± = 0.05 used in the test.

The same conclusion is reached by looking at the P-value.

Since F is smaller the F Critical value, the Null hypothesis is not qualified to be rejected and hence theВ variances in the two data sets are equal. See equation below.В Keep in mind that F must be greater than or equal to 1 therefore s 1 2В в‰Ґ s 2 2. Comparing variancesВ is done usingВ a F-test. In general, it is a good idea to compare the variances before running the t-test even though most of the time variances are assumed to be equal. In a more intuitive way, varianceВ says something aboutВ the spread of values in a data set. Mathematically speaking, variance is the square of the standard deviation. In the header of Table 3, note that the t-test was conducted by assuming equal variances. Although both blue solutions look the same and have very similar absorbances and concentrations, they nevertheless are different enough from each other to not be identical. Conclusion:В There is a significant difference between the average absorbance value (and hence calculated concentrations) of solution A and solution B. Since the P-value two-tail is considerably smaller than that (0,0000006954 versus 0,05), the Null hypothesis, H 0,В qualifies to be rejected. Another way to run the hypothesis test, it is to look at P(T<=t) two-tail,В also known as P-value, which represents the probability that t Critical two-tail exceeds the experimental value of t Stat.ДЄt the beginning of the test, the level of significance was set at О± =В 0.05 (=В 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,В 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:В Add-ons> Get Add-ons> Search Add-ons and type XLMiner ToolPak.) TheВ test was run by XLMiner ToolPak-Excel Analysis Pak. Table 3В below shows the results for the comparison between the absorbance values of solution A and solution B.

#HOW TO OPEN XLMINER ANALYSIS TOOLPAK 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 О±В is set at 0.05 (or 5%).В 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 О±,В needs to be chosen.

#HOW TO OPEN XLMINER ANALYSIS TOOLPAK 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. 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.В Based on sight, it could be that theВ two aqueous solutions are identical in concentration.В The differencesВ among the absorbance and concentration data are small and based on this we could concludeВ that there is no meaningful difference between the two aqueous solutions. 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 sizableВ difference (0,108ОјM) between the calculated concentrations of the two aqueous solutions.

How to open xlminer analysis toolpak