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- https://chem.libretexts.org/Courses/Lakehead_University/Analytical_I/4%3A_Evaluating_Analytical_Data/4.01%3A_Characterizing_Measurements_and_ResultsOne way to characterize data from multiple measurements/runs is to assume that the measurements are randomly scattered around a central value that provides the best estimate of expected, or “true” va...One way to characterize data from multiple measurements/runs is to assume that the measurements are randomly scattered around a central value that provides the best estimate of expected, or “true” value. There are two common ways to estimate central tendency: the mean and the median.
- https://chem.libretexts.org/Bookshelves/Analytical_Chemistry/Analytical_Chemistry_2.1_(Harvey)/04%3A_Evaluating_Analytical_Data/4.08%3A_Using_Excel_and_R_to_Analyze_DataThis chapter discusses using Excel and R for statistical calculations. Both tools offer functions for descriptive statistics, probability distributions, and significance tests. Excel provides built-in...This chapter discusses using Excel and R for statistical calculations. Both tools offer functions for descriptive statistics, probability distributions, and significance tests. Excel provides built-in functions for calculating means, variances, and t-tests. R, a programming environment, offers similar capabilities and additional functions for detecting outliers using Dixon's Q-test and Grubb's test.
- https://chem.libretexts.org/Courses/Los_Angeles_Trade_Technical_College/Analytical_Chemistry/2%3A_Analytical_Chemistry_2.0_(Harvey)/05%3A_Evaluating_Analytical_Data/5.01%3A_Characterizing_Measurements_and_ResultsOne way to characterize data from multiple measurements/runs is to assume that the measurements are randomly scattered around a central value that provides the best estimate of expected, or “true” va...One way to characterize data from multiple measurements/runs is to assume that the measurements are randomly scattered around a central value that provides the best estimate of expected, or “true” value. There are two common ways to estimate central tendency: the mean and the median.
- 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.
- https://chem.libretexts.org/Bookshelves/Analytical_Chemistry/Analytical_Chemistry_2.1_(Harvey)/04%3A_Evaluating_Analytical_Data/4.01%3A_Characterizing_Measurements_and_ResultsThis page focuses on determining the mass of a circulating United States penny and explores methods for analyzing data related to this measurement. It discusses the importance of defining the problem ...This page focuses on determining the mass of a circulating United States penny and explores methods for analyzing data related to this measurement. It discusses the importance of defining the problem precisely and collects preliminary data from seven pennies to illustrate concepts. Measures of central tendency, including the mean and the median, are introduced as ways to summarize data, with the mean being more sensitive to extreme values than the median.
