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- https://chem.libretexts.org/Courses/Los_Angeles_Trade_Technical_College/Analytical_Chemistry/2%3A_Analytical_Chemistry_2.0_(Harvey)/05%3A_Evaluating_Analytical_Data/5.06%3A_Statistical_Methods_for_Normal_DistributionsThe normal distribution is the most common distribution used for experimental results. Because the area between any two limits of a normal distribution is well defined, constructing and evaluating sig...The normal distribution is the most common distribution used for experimental results. Because the area between any two limits of a normal distribution is well defined, constructing and evaluating significance tests is straightforward.
- https://chem.libretexts.org/Courses/University_of_San_Diego/Fall_2024_Chem_220_Analytical_Chemistry_David_De_Haan/02%3A_Descriptive_Statistics/2.01%3A_Measures_of_CenterBoth graphical and numerical methods of summarizing data make up the branch of statistics known as descriptive statistics. Later, descriptive statistics will be used to estimate and make inferences ab...Both graphical and numerical methods of summarizing data make up the branch of statistics known as descriptive statistics. Later, descriptive statistics will be used to estimate and make inferences about population parameters using methods that are part of the branch called inferential statistics. This section introduces numerical measurements to describe sample data.
- https://chem.libretexts.org/Courses/University_of_San_Diego/USD_CHEM_220%3A_Fall_2022_(Gillette)/02%3A_Descriptive_Statistics/2.01%3A_Measures_of_CenterBoth graphical and numerical methods of summarizing data make up the branch of statistics known as descriptive statistics. Later, descriptive statistics will be used to estimate and make inferences ab...Both graphical and numerical methods of summarizing data make up the branch of statistics known as descriptive statistics. Later, descriptive statistics will be used to estimate and make inferences about population parameters using methods that are part of the branch called inferential statistics. This section introduces numerical measurements to describe sample data.
- https://chem.libretexts.org/Bookshelves/Analytical_Chemistry/Instrumental_Analysis_(LibreTexts)/35%3A_Appendicies/35.02%3A_Single-Sided_Normal_DistributionFor example, the proportion of the area under a normal distribution to the right of a deviation of 0.04 is 0.4840 (see entry in red in the table), or 48.40% of the total area (see the area shaded blue...For example, the proportion of the area under a normal distribution to the right of a deviation of 0.04 is 0.4840 (see entry in red in the table), or 48.40% of the total area (see the area shaded blue in Figure \PageIndex1). This divides the normal distribution curve into three regions: the area that corresponds to our answer (shown in blue), the area to the right of this, and the area to the left of this.
- https://chem.libretexts.org/Courses/Lakehead_University/Analytical_I/4%3A_Evaluating_Analytical_Data/4.06%3A_Statistical_Methods_for_Normal_DistributionsThe normal distribution is the most common distribution used for experimental results. Because the area between any two limits of a normal distribution is well defined, constructing and evaluating sig...The normal distribution is the most common distribution used for experimental results. Because the area between any two limits of a normal distribution is well defined, constructing and evaluating significance tests is straightforward.
- https://chem.libretexts.org/Bookshelves/Physical_and_Theoretical_Chemistry_Textbook_Maps/Thermodynamics_and_Chemical_Equilibrium_(Ellgen)/03%3A_Distributions_Probability_and_Expected_Values/3.10%3A_Statistics_-_the_Mean_and_the_Variance_of_a_DistributionThere are two important statistics associated with any probability distribution, the mean of a distribution and the variance of a distribution.
- 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/Courses/Los_Angeles_Trade_Technical_College/Analytical_Chemistry/2%3A_Analytical_Chemistry_2.0_(Harvey)/15%3A_Developing_a_Standard_Method/15.3%3A_Validating_the_Method_as_a_Standard_MethodFor an analytical method to be useful, an analyst must be able to achieve results of acceptable accuracy and precision. Verifying a method, as described in the previous section, establishes this goal ...For an analytical method to be useful, an analyst must be able to achieve results of acceptable accuracy and precision. Verifying a method, as described in the previous section, establishes this goal for a single analyst. Another requirement for a useful analytical method is that an analyst should obtain the same result from day to day, and different labs should obtain the same result when analyzing the same sample. The process by which we approve method for general use is known as validation.
- 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.
