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- https://chem.libretexts.org/Bookshelves/Analytical_Chemistry/Analytical_Chemistry_2.1_(Harvey)/14%3A_Developing_a_Standard_Method/14.04%3A_Using_Excel_and_R_for_an_Analysis_of_VarianceThis page provides guidance on conducting an analysis of variance (ANOVA) using both Excel and R. Excel's Analysis ToolPak simplifies ANOVA, allowing users to input data and parameters to obtain resul...This page provides guidance on conducting an analysis of variance (ANOVA) using both Excel and R. Excel's Analysis ToolPak simplifies ANOVA, allowing users to input data and parameters to obtain results, including statistical measures like mean, variance, F-value, and p-values. R, on the other hand, requires coding but offers additional features like Tukey's honest significant difference test to identify sources of significant differences.
- https://chem.libretexts.org/Bookshelves/Analytical_Chemistry/Analytical_Chemistry_2.1_(Harvey)/04%3A_Evaluating_Analytical_Data/4.06%3A_Statistical_Methods_for_Normal_DistributionsThis page discusses the use of statistical tests to compare means and variances in analytical chemistry. Key methods include the t-test for comparing sample means, the F-test for variances, and signif...This page discusses the use of statistical tests to compare means and variances in analytical chemistry. Key methods include the t-test for comparing sample means, the F-test for variances, and significance tests for outliers like Dixon's Q-test, Grubb's test, and Chauvenet's criterion. The tests help determine if observed differences are significant or due to chance, aiding in validating analytical methods or identifying errors in analyses.
- https://chem.libretexts.org/Courses/Los_Angeles_Trade_Technical_College/Analytical_Chemistry/2%3A_Analytical_Chemistry_2.0_(Harvey)/05%3A_Evaluating_Analytical_Data/5.05%3A_Statistical_Analysis_of_DataA confidence interval is a useful way to report the result of an analysis because it sets limits on the expected result. In the absence of determinate error, a confidence interval indicates the range ...A confidence interval is a useful way to report the result of an analysis because it sets limits on the expected result. In the absence of determinate error, a confidence interval indicates the range of values in which we expect to find the population’s expected mean. When we report a 95% confidence interval for the mass of a penny as 3.117 g ± 0.047 g, for example, we are claiming that there is only a 5% probability that the expected mass of penny is less than 3.070 g or more than 3.164 g.
- https://chem.libretexts.org/Courses/Lakehead_University/Analytical_I/4%3A_Evaluating_Analytical_Data/4.05%3A_Statistical_Analysis_of_DataA confidence interval is a useful way to report the result of an analysis because it sets limits on the expected result. In the absence of determinate error, a confidence interval indicates the range ...A confidence interval is a useful way to report the result of an analysis because it sets limits on the expected result. In the absence of determinate error, a confidence interval indicates the range of values in which we expect to find the population’s expected mean. When we report a 95% confidence interval for the mass of a penny as 3.117 g ± 0.047 g, for example, we are claiming that there is only a 5% probability that the expected mass of penny is less than 3.070 g or more than 3.164 g.
- https://chem.libretexts.org/Bookshelves/Analytical_Chemistry/Analytical_Chemistry_2.1_(Harvey)/04%3A_Evaluating_Analytical_Data/4.11%3A_Chapter_Summary_and_Key_TermsThe page discusses the characterization of data by central tendency and spread, involving measures like mean, median, range, and standard deviation. Errors affecting accuracy and precision are address...The page discusses the characterization of data by central tendency and spread, involving measures like mean, median, range, and standard deviation. Errors affecting accuracy and precision are addressed through propagation of uncertainty. The page covers probability distributions, normal distribution confidence intervals, and statistical analysis techniques such as t-tests and F-tests for comparing data sets.
