A series of links below are listed to teach basic statistics used in Six Sigma projects. A Green Belt, Black Belt, or Master Black Belt should at a minimum be comfortable with these basic statistics. There are primarily two branches in which statistics are studied:
Descriptive Statistics
Applied to describe the data using numbers, charts, and graphs. Terms such as mean, median, mode, variance, standard deviation are values that summarize data. Descriptive statistics describe the entire group for which the numbers were obtained. These are the actual values for the entire group.
Inferential Statistics
Uses sample statistics to infer relationships of the population parameters.This is most often done in the Analyze and Improve phases using hypothesis testing, correlation analysis, regression analysis, and design of experiments (DOE). Rarely is it possible to be able to analyze the population (such as the average weight of all sharks in the ocean) so a sampling strategy is employed. The analysis of the sample is used to apply inferences to the entire population. The values may or may not be the same values for the entire population, but they are often used with a confidence interval applied.

A comparison (of means, variance, proportions) is initiated with a hypothesis statement about a population or populations. The sample statistic(s) are studied and analyzed to determine with a certain level of confidence and power that the hypothesis (null hypothesis) is to be proven false or not false (but not necessarily true), see Hypothesis Testing for more information.
Histograms
Box Plots
Comparing Samples vs. Population
Data Classification
P-Value
Confidence Intervals
Correlation
Measures of Central Tendency: Mean, Median, Mode
Measures of Dispersion: Range, Standard Deviation, Variance
Alpha and Beta Risks (Type I Error and Type II Error)
Hypothesis Testing
Analysis of Variance (ANOVA)
DPU - Defects Per Unit
DPO - Defects Per Opportunity
DPMO - Defects Per Million Opportunities
Process Yield Metrics
FY - Final Yield
TPY - Throughput Yield
RTY - Rolled Throughput Yield
NY - Normalized Yield
The meaning and formula around sigma scores
Z-score
Yield to Sigma Relationships
Process Capability Indices
Pp
Ppk
Cp
Cpk
Cpm
DISCRETE DISTRIBUTIONS:
1) Binomial Distribution
2) Poisson Distribution
3) Hypergeometric Distribution
CONTINUOUS DISTRIBUTIONS:
1) Uniform Distribution
2) Normal Distribution
3) Exponential Distribution
4) t Distribution
5) Chi-square Distribution
6) F Distribution
Return to the MEASURE Phase
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