Six Sigma Green Belt Training

Directions: There are 34 questions in this self-assessment. Indicate your response by clicking on the correct answer. In order to receive the correct answers to the assessment, you must answer all questions.

1. A bar chart that depicts the frequencies of numerical or measurement data.
   a. Sample
   b. Histogram
   c. Check Sheet
   d. Process Map
   
   
2. A systematic group of activities intended to recognize and evaluate the potential failure of a product/process and the effects of that failure.
   a. Six Sigma
   b. Design of Experiments
   c. Benchmarking
   d. Failure Mode and Effects Analysis
   
   
3. Inputs to a process that can be manipulated during experimentation.
   a. Factors
   b. Hypothesis Testing
   c. Control Plan
   d. Population
   
   
4. The probability of accepting the alternative hypothesis (H1) when the null hypothesis (Ho) is true.
   a. Beta Risk
   b. Alpha Risk
   c. Attribute Data
   d. Random Experiment
   
   
5. An advanced flowcharting method, identifying the process input variables "x" and the relationship to the process output variables "y".
   a. Statistical Process Control
   b. Pareto Chart
   c. Scatter Diagram
   d. Process Map
   
   
6. An improvement process in which a company measures its performance against that of best-in-class companies, determines how those companies achieved their performance levels, and uses the information to improve its own performance.
   a. Control Chart
   b. Six Sigma
   c. Benchmarking
   d. Cause and Effect Diagram
   
   
7. A procedure whereby one or two mutually exclusive and exhaustive statements about a population is concluded. Information from a sample is used to infer something about a population from which the sample was drawn.
   a. Hypothesis Testing
   b. Design of Experiment
   c. Beta Risk
   d. Benchmarking
   
   
8. A graphical tool for ranking causes from most significant to least significant.
   a. Check Sheet
   b. Cause and Effect Diagram
   c. Scatter Diagram
   d. Pareto Chart
   
   
9. The probability of accepting the null hypothesis (Ho) when the alternative (H1) is true.
   a. Elementary Outcomes
   b. Beta Risk
   c. Attribute Data
   d. Alpha Risk
   
   
10. For a set of data, the average squared deviation from the mean, with a denominator of n-1.
    a. Sample Variance
    b. Normal Distribution
    c. Sample
    d. Population
    
    
11. Provides relationship between two variables, and provides a visual correlation coefficient.
    a. Control Chart
    b. Pareto Chart
    c. Scatter Diagram
    d. Statistical Process Control
    
    
12. A definition of the possible outcomes of interest from a given experiment.
    a. Hypothesis Testing
    b. Normal Distribution
    c. Elementary Outcomes
    d. Random Variable
    
    
13. The number of units in a sample.
    a. Population
    b. Mode
    c. Mean
    d. Sample Size
    
    
14. A document that describes the required characteristics for the quality of a product or service, including measures and control methods.
    a. Statistical Control Process
    b. Control Plan
    c. Six Sigma
    d. Confidence Interval
    
    
15. The charting of a data set in which most of the data points are concentrated around the average (mean), thus forming a bell-shaped curve.
    a. Pareto Chart
    b. Normal Distribution
    c. Standard Deviation
    d. Scatter Diagram
    
    
16. A methodology that provides businesses with the tools to improve the capability of their business processes.
    a. Design of Experiments
    b. Benchmarking
    c. Six Sigma
    d. Failure Mode and Effects Analysis
    
    
17. A branch of applied statistics dealing with planning, conducting, analyzing, and interpreting controlled tests to evaluate the factors that control the value of a parameter or group of parameters.
    a. Random Experiment
    b. Probability
    c. Six Sigma
    d. Design of Experiments
    
    
18. Range which a parameter that a population may be expected to fall, on the basis of measurement, with some specific confidence level or confidence coefficient.
    a. Confidence Interval
    b. Factors
    c. Control Plan
    d. Normal Distribution
    
    
19. Possible results of a random experiment.
    a. Standard Deviation
    b. Elementary Outcomes
    c. Discrete Data
    d. Sample Size
    
    
20. The measure of the likelihood of a given event occurring.
    a. Risk
    b. Hypothesis Test
    c. Cause and Effect Diagram
    d. Probability
    
    
21. A set or collection of objects or individuals. It can be the corresponding set of values that measure a certain characteristic of a set of objects or individuals.
    a. Factors
    b. Alpha Risk
    c. Median
    d. Population
    
    
22. A simple data recording device, custom designed by the user, which allows them to interpret the results.
    a. Histogram
    b. Scatter Diagram
    c. Check Sheet
    d. Pareto Chart
    
    
23. Basic tool of statistical process control. It consists of a run chart, together with statistically determined upper and lower control limits and a centerline.
    a. Control Chart
    b. Confidence Interval
    c. Statistical Control Process
    d. Control Plan
    
    
24. A pictorial diagram showing possible causes (process inputs) for a given effect (process outputs). It is also referred to as the "Ishikawa diagram" or "fishbone diagram."
    a. Standard Deviation
    b. Cause and Effect Diagram
    c. Random Experiment
    d. Scatter Diagram
    
    
25. The chance of making a right or wrong conclusion.
    a. Risk
    b. Beta Risk
    c. Alpha Risk
    d. Mode
    
    
26. Arithmetic average of a set of values.
    a. Median
    b. Sample
    c. Mode
    d. Mean
    
    
27. A set of values or items selected from some population.
    a. Factors
    b. Alpha Risk
    c. Sample
    d. Sample Size
    
    
28. The middle value of a data set when the values are arranged in either ascending or descending order.
    a. Median
    b. Mode
    c. Mean
    d. Discrete Data
    
    
29. The use of basic graphical and statistical methods for analyzing and controlling the variation of a process, and thus continuously improving the process.
    a. Confidence Interval
    b. Statistical Process Control
    c. Design of Experiments
    d. Control Plan
    
    
30. Countable observations, for example, number of defects.
    a. Sample Size
    b. Attribute Data
    c. Discrete Data
    d. Variable Data
    
    
31. The value occurring most frequently in a data set.
    a. Mean
    b. Mode
    c. Variable Data
    d. Risk
    
    
32. One of the most common measures of variability in a data set or population.
    a. Normal Distribution
    b. Alpha Risk
    c. Mean
    d. Standard Deviation
    
    
33. Data coming basically from GO/NO-GO, pass/fail determinations of whether units conform to standards.
    a. Attribute Data
    b. Discrete Data
    c. Variable Data
    d. Sample Size
    
    
34. Concerning the values of a variable, as opposed to attribute data. A dimensional value can be recorded and is only limited in value by the resolution of the measurement system.
    a. Factors
    b. Elementary Outcomes
    c. Variable Data
    d. Normal Distribution