**List of Articles**These concepts have articles devoted to them. The list that follows shows other concepts that are covered in these articles.

- Alpha, α
- Alpha and Beta Errors
- Alpha, p-value, Critical Value and Test Statistic – How They Work Together
- Alternative Hypothesis
- ANOM
- ANOVA – Part 1: What it Does
- ANOVA – Part 2: How it Does It
- ANOVA -- Part 3: One-Way (aka single factor)
- ANOVA -- Part 4: Two-Way (aka two-factor)
- ANOVA vs. Regression
- Binomial Distribution
- Charts/ Graphs/ Plots – Which to Use When
- Chi-Square – the Test Statistic and its Distributions
- Chi-Square Test for Goodness of Fit
- Chi-Square Test for Independence
- Chi-Square Test for the Variance
- Confidence Intervals – Part 1: General Concepts
- Confidence Intervals – Part 2: Some Specifics
- Control Charts – Part 1: General Concepts and Principles
- Control Charts – Part 2: Which to Use When
- Correlation -- Part 1
- Correlation -- Part 2
- Critical Value
- Degrees of Freedom
- Design of Experiments (DOE) -- Part 1
- Design of Experiments (DOE) -- Part 2
- Design of Experiments (DOE) -- Part 3
- Distributions -- Part 1: What They Are
- Distributions -- Part 2: How They Are Used
- Distributions -- Part 3: Which to Use When
- Errors – Types, Uses, and Interrelationships
- Exponential Distribution
- F
- Fail to Reject the Null Hypothesis
- Hypergeometric Distribution
- Hypothesis Testing – Part 1: Overview
- Hypothesis Testing – Part 2: How To
- Inferential Statistics
- Margin of Error
- Nonparametric
- Normal Distribution
- Null Hypothesis
- p, p-value
- p, t, and F: "<" or ">"?
- Poisson Distribution
- Power
- Process Capability Analysis (PCA)
- Proportion
- r, Multiple R, r2, R2, R Square, R2 Adjusted
- Regression – Part 1: Sums of Squares
- Regression – Part 2: Simple Linear
- Regression – Part 3: Analysis Basics
- Regression – Part 4: Multiple Linear
- Regression -- Part 5: Simple Nonlinear
- Reject the Null Hypothesis
- Residuals
- Sample, Sampling
- Sample Size – Part 1: Proportions for Count Data
- Sample Size – Part 2: for Continuous/ Measurement Data
- Sampling Distribution
- Sigma, σ
- Skew, Skewness
- Standard Deviation
- Standard Error
- Statistically Significant
- Sum of Squares
- t, The Test Statistic and Its Distributions
- t-tests -- Part 1: Overview
- t-tests -- Part 2: Calculations and Analysis
- Test Statistic
- Variables
- Variance
- Variation/ Variability/ Dispersion/ Spread
- Which Statistical Tool to Use to Solve Some Common Problems
- z

__Other Concepts --and the article(s) in which they are covered____1-Sided__or__1-Tailed__: see the articles*Alternative Hypothesis*and*Alpha, α*.__1-Way__: an analysis that has 1 Independent (x) Variable. E.g. 1-way ANOVA__2-Sided__or__2-Tailed__: see the articles*Alternative Hypothesis*and*Alpha, α*.__2-Way__: an analysis that has 2 Independent (x) Variables. E.g. 2-way ANOVA__68-95-99.7 Rule__: same as the Empirical Rule. See the article*Normal Distribution*.- Acceptance Region: see the article
*Alpha, α*. __Adjusted R2__: see the article*r, Multiple R, r2, R2, R Square, R2 Adjusted, Adjusted R2*.__aka__: also known as__Alias:__see the article*Design of Experiments (DOE) – Part 2*.__Associated__,__Association__: see the article*Chi-Square Test for Independence*.__Assumptions__: requirements for being able to use a particular test or analysis. For example, ANOM and ANOVA require approximately Normal data.__Attributes data__,__Attributes Variable__: same as Categorical or Nominal data or Variable. See the articles*Variables*and*Chi-Square Test for Independence*.__Autocorrelation__: see the article*Residuals*.__Average Absolute Deviation__: see the article*Variance*.__Average__: same as the Mean -- the sum of a set of numerical values divided by the Count of values in the set.__Bernoulli Trial__: see the article*Binomial Distribution*.__Beta__: The probability of a Beta Error. See the article*Alpha and Beta Errors*.__Beta Error__: featured in the article*Alpha and Beta Errors*.__Bias__: see the article*Sample, Sampling*.- B
__in__,__Binning__: see the articles*Chi-Square Test for Goodness of Fit*, and*Charts/ Plots/ Graphs – Which to Use When*. __Block__,__Blocking__see the article D*esign of Experiments (DOE) – Part 3*.__Box Plot__,__Box and Whiskers Plot__: see the article*Charts/ Graphs/ Plots – Which to Use When*.__Cm__,__Cp__,__Cr__, or__CPK__see the article*Process Capability Analysis (PCA)*.__Capability__,__Capability Index__: see the article*Process Capability Analysis (PCA)*.__Categorical data__,__Categorical Variable__: same as Attribute or Nominal data/Variable. See the articles*Variables*and*Chi-Square Test for Independence*.__CDF__: see Cumulative Density Function below.__Central Limit Theorem__: see the article*Normal Distribution*.__Central Location__: same as Central Tendency. See the article*Distributions – Part 1: What they Are*.__Central Tendency__: same as Central Location. See the article*Distributions – Part 1: What they Are*. Chebyshev's Theorem: see the article Standard Deviation.__Confidence Coefficient__same as Confidence Level. See the article*Alpha, α*.__Confidence Level__: (aka Level of Confidence aka Confidence Coefficient) equals 1–Alpha. See the article*Alpha, α*.__Confounding__: see the article*Design of Experiments (DOE), Part 3*.__Contingency Table__: see the article*Chi-Square Test for Independence*.__Continuous data or Variables__: see the articles*Variables*and*Distributions – Part 3: Which to Use When*.__Control__, "in…" or "out of…": see the article*Control Charts – Part 1: General Concepts and Principles*.__Control Limits, Upper and Lower__: see the article*Control Charts – Part 1: General Concepts and Principles*.__Count data__,__Count Variables__: aka Discrete data or Discrete Variables. See the article*Variables*.__Covariance__: see the article*Correlation – Part 1*.__Criterion Variable__: see the article*Variables*.__Critical Region__: same as Rejection Region. See the article*Alpha, α*.__Cumulative Density Function (CDF)__: the formula for calculating the Cumulative Probability of a Range of values of a Continuous random Variable, e.g. the Cumulative Probability that x ≤ 0.5.__Cumulative Probability__: see the article*Distributions – Part 2: How They Are Used*.__Curve Fitting__: see the article*Regression -- Part 5: Simple Nonlinear*.__Dependent Variable__: see the article*Variables*.__Descriptive Statistics__: See the article*Inferential Statistics*.__Dot Plot__: see the article*Charts/ Graphs/ Plots – Which to Use When*.__Deviation__: The difference between a data value and a specified value (usually the Mean). See the article*Regression – Part 1: Sums of Squares*. See also the article*Standard Deviation*.__Discrete data or Variables__: see the articles*Variables*and*Distributions – Part 3: Which to Use When*.__Dispersion__: see the article*Variation/ Variability/ Dispersion/ Spread*(they all mean the same thing).__Effect Size__: see the article*Power*.__Empirical Rule__– same as the 68-95-99.7 Rule. See the article*Normal Distribution*.__Expected Frequency__: see the articles*Chi-Square Test for Goodness of Fit*and*Chi-Square Test for Independence.*__Expected Value__: see the articles Chi-Square Test for Goodness of Fit and*Chi-Square Test for Independence*.__Exponential__: see the article*Exponential Distribution*.__Exponential Curve__: see the article*Regression – Part 5: Simple Nonlinear*.__Exponential Transformation__: see the article Regression --*Part 5: Simple Nonlinear*.__Extremes__: see the article*Variation/ Variability/ Dispersion/ Spread*.__F-test__: see the article*F*.__Factor__: see the articles ANOVA – Parts 3 and 4 and*Design of Experiments – Part 1*.__False Positive__: an Alpha or Type I Error; featured in the article*Alpha and Beta Errors*.__False Negative__: a Beta or Type II Error; featured in the article*Alpha and Beta Errors*.__Frequency__: a Count-like Statistic which can be non-integer. See the articles*Chi-Square Test for Goodness of Fit*and*Chi-Square Test for Independence.*__Friedman Test__: see the article*Nonparametric*.__Generator__: see the article*Design of Experiments – Part 3*.__Goodness of Fit__: see the articles*Regression – Part 1 of 5: Sums of Squares*and*Chi-Square Test for Goodness of Fit*.__Histogram__: see the article*Charts, Plots, Graphs – Which to Use When*.- Independence: see the article, Chi-Square Test for Independence.
__Independent Variable__: see the article*Variables*.- I
__nteraction__: see the articles*ANOM*;*ANOVA – Part 4: 2-Way*; Design of Experiments, Parts 1, 2, and 3;*Regression – Part 4: Multiple Linear*. __Intercept__: see the article*Regression -- Part 2: Simple Linear*.__Interquartile Range (IQR)__: see the article*Variation/ Variability/ Dispersion/ Spread*.__Kruskal-Wallis Test__: see the article*Nonparametric*.__Kurtosis__: a measure of the Shape of a Distribution. See the article*Normal Distributions – Part 1*.__Least Squares__(same as Least Sum of Squares or Ordinary Least Sum of Squares) see the articles*Regression – Part 1: Sums of Squares*and*Regression – Part 2: Simple Linear*.__Least Sum of Squares__: same as*Least Squares*(above).__Level of Confidence__: same as Confidence Level; equal to 1 – α. See the article*Alpha, α*.__Level of Significance__: same as Significance Level, Alpha (α). See the articles*Alpha, α*and*Statistically Significant.*__Line Chart__: see the article*Charts/ Graphs/ Plots – Which to Use When*.- L
__ogarithmic Curve__,__Logarithmic Transformation__: see the article*Regression – Part 5: Simple Nonlinear*. __Main Effect__a Factor which is not an Interaction. See the articles ANOVA – Part 4: 2-Way and*Design of Experiments, Part 2.*__Mann-Whitney Test__: see the article*Nonparametric*.__Mean__: the average. Along with Mean and Median, it is a measure of Central Tendency.__Mean Absolute Deviation (MAD)__: see the article*Variation/ Variability/ Dispersion/ Spread*.__Mean Sum of Squares__: see the articles*ANOVA – Part 2: MSB, MSW*, and*F*.__Measurement data__: same as Continuous data above.__Median__: the middle of a range of values. Along with Mean and Mode, it is a measure of Central Tendency. It is used instead of the Mean in Nonparametric Analysis. See the article*Nonparametric*.__Mode__: the most common value within a group (e.g. a Sample or Population or Process). There can be more than one Mode. Along with Mean and Median, Mode is a measure of Central Tendency.__MSB__and__MSW__: see the articles*ANOVA – Part 2: MSB, MSW*, and*F*.__Multiple R__: see the article*r, Multiple R, r2, R2, R Square, R2 Adjusted*.__Multiplicative Law of Probability__: see the article*Chi-Square Test for Independence*.__Nominal data, Nominal Variable__: Same as Categorical or Attributes data or Variable. See the article*Variables*.*One-sided, One-tailed*: see the articles Alternative Hypothesis and*Alpha, α*.- One-way: same as 1-way; an analysis that has 1 Independent (x) Variable. E.g. 1-way ANOVA.
__Outlier__: See the article*Variation/ Variability/ Dispersion/ Spread*.__Parameter__: a measure of a property of a Population or Process, e.g. the Mean or Standard Deviation. The counterpart for a Sample is called a "Statistic". Parameters are usually denoted by characters in the Greek Alphabet, such as μ or σ.__Parametric__: see the article*Nonparametric*.__Pareto Chart__: see the article*Charts/ Graphs/ Plots – Which to Use When*.__PCA__: see the article*Process Capability Analysis (PCA)*.__PDF__: see__Probability Density Function__below.__Pearson's Coefficient__:,__Pearson's r__: the correlation Coefficient, r. See the article*Correlation – Part 2*.__Performance Index__: see the article*Process Capability Analysis (PCA)*.__PMF__: see Probability Mass Function below__Polynomial Curve__: see the article*Regression -- Part 5: Simple Nonlinear*.- "
__Population or Process__": Where most texts say "Population", this book says adds "or Process". Ongoing Processes are handled the same as Populations, because new data values continue to be created. Thus, like Populations, we usually don't have complete data for Processes. __Power Transformation__: see the article*Regression -- Part 5: Simple Nonlinear*.__Probability Density Function (PDF)__the formula for calculating the Probability of a single value of a Continuous random Variable of, e.g. the Probability that x = 5. (For Discrete random Variables, the corresponding term is Probability Mass Function, PMF.) See also Cumulative Density Function.__Probability Distribution__: see the article*Distributions – Part 1: What They Are*.__Probability Mass Function (PMF)__the formula for calculating the Probability of a single value of a Discrete random Variable of, e.g. the Probability that x = 5.__Qualitative Variable, Qualitative data__: same as Categorical Variable, Categorical data above. See the article*Variables and Chi-Square Test for Independence*.__Outlier__See the article*Variation/ Variability/ Dispersion/ Spread*.__Random Sample__: see the article*Sample, Sampling*.__Random Variable__: see the article*Variables*.__Range:__see the article*Variation/ Variability/ Dispersion/ Spread*.__Rejection Region__: same as Critical Region. See the article*Alpha, α*.__Replacement, Sampling With__or__Without__: see the article*Binomial Distribution*.__Resolution__: see the article*Design of Experiments (DOE) -- Part 3*.__Response Variable__: see the articles*Variables*and*Design of Experiments (DOE) – Part 2*.__Run Rules__: see the article*Control Charts – Part 1.*__Scatterplot__: see the article*Charts/ Graphs/ Plots – Which to Use When*.__Shape__: see the article*Distributions – Part 1: What They Are*.__Significance Level__: see the article*Alpha, α*.__Significant__: see the article*Statistically Significant*.__Slope__: see the article*Regression -- Part 2: Simple Linear*.__Spread__: see the article*Variation/ Variability/ Dispersion/ Spread*.__Standard Normal Distribution__: see the articles*Normal Distribution*and*z*.__Statistic__: a measure of a property of a Sample, e.g. the Mean or Standard Deviation. The counterpart for a Population or Process is called a "Parameter". Statistics are usually denoted by characters based on the Roman Alphabet, such as x̅ or s.__Statistical Inference__(same as*Inferential Statistics*; see the article by that name.)__Statistical Process Control__: see the article*Control Charts – Part 1: General Concepts and Principles*.__Student's t__: see the article*t – The Test Statistic and Its Distributions*.__Tail__: see the articles*Alpha, α*and*Alternative Hypothesis*.__Three Sigma Rule__: same as Empirical Rule and the 68-95-99.7 Rule. See the article*Normal Distribution*.__Transformation__: see the article Regression -- Part 5: Simple Nonlinear.__Two-sided__,__Two-tailed__: same as 2-sided, 2-tailed. See the articles Alpha, α and*Alternative Hypothesis*.__Two-wa__y: same as 2-way; an analysis that has 2 Independent (x) Variables. E.g. 2-way ANOVA.__Type I and Type II Errors__: same as*Alpha and Beta Errors*, respectively. See the article by that name.__Variables data__same as Continuous data. See the articles*Variables*and Distributions – Part 3: Which to Use When.__Variability__: see the article*Variation/ Variability/ Dispersion/ Spread*.__Wilcoxon Test__: see the article*Nonparametric*.