# Six Sigma Yellow Belt Trivia Quiz!

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Six Sigma is a way in which most corporate use to improve some of their processes. What levels are you when it comes to six sigma? Are you working up for the black belt? The quiz below is perfect for a yellow belt part I, II and III. Give it a try and get to review your understanding as you wait for the next batch of questions.

• 1.

### __________________can be measured against a benchmark in a process.

• A.

Performance

• B.

Outcome of the process (Y)

• C.

Operational Efficiency

• D.

All of the above

D. All of the above
Explanation
All of the options listed - performance, outcome of the process, and operational efficiency - can be measured against a benchmark in a process. Performance refers to how well a task or activity is executed, while the outcome of the process assesses the end result or achievement. Operational efficiency evaluates the effectiveness and productivity of the process. Therefore, all three options can be used as criteria to measure against a benchmark in order to evaluate and improve the performance of a process.

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• 2.

### “If P value is >=0.5, then the process is said to be Normal” – Indicate what type of statistics is being used?

• A.

Descriptive

• B.

Inferential

• C.

Expression

• D.

None of the above

B. Inferential
Explanation
The statement "If P value is >=0.5, then the process is said to be Normal" suggests that the statistics being used in this context is inferential. Inferential statistics involves making inferences or drawing conclusions about a population based on a sample. In this case, the P value is likely being used to make an inference about the normality of a process based on the observed data.

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• 3.

### Ratio and Interval Scale of measurements are based on ______________type of data

• A.

Discrete & Attribute

• B.

Discrete & Continuous

• C.

Variable & Continuous

• D.

Continuous & Attribute

C. Variable & Continuous
Explanation
Ratio and Interval Scale of measurements are based on variable and continuous type of data. In these scales, the data consists of numerical values that can take on any value within a certain range, and the intervals between the values are equal. This means that the data can be measured and compared using mathematical operations such as addition, subtraction, multiplication, and division. Additionally, the data in these scales can have a true zero point, which allows for the calculation of ratios between values. Therefore, variable and continuous data are the basis for ratio and interval scales of measurements.

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• 4.

### The Pareto Graph is used to represent ____________ scale of measurement.

• A.

Nominal

• B.

Ordinal

• C.

Ratio

• D.

Interval

A. Nominal
Explanation
The Pareto Graph is used to represent data on a nominal scale of measurement. Nominal scale is the lowest level of measurement where data is categorized into distinct categories or labels without any specific order or ranking. In a Pareto Graph, the categories are represented by bars or columns, with the height of each bar indicating the frequency or count of each category. This type of graph is commonly used to show the relative importance or frequency of different categories in a dataset.

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• 5.

### --------------------- helps to understand Process behavior for parametric distribution.

• A.

Median

• B.

Range

• C.

Mean

• D.

Variance

C. Mean
Explanation
The mean helps to understand process behavior for parametric distribution because it provides a measure of central tendency. It represents the average value of a set of data, indicating the typical value around which the data points are clustered. By calculating the mean, we can determine the average behavior of the process and identify any deviations or trends. This information is useful in analyzing and predicting the behavior of the process in relation to the parametric distribution.

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• 6.

### Which of the following is not a Measure of Central Tendency

• A.

Geometric Mean

• B.

Median

• C.

Mode

• D.

Arithmetic Mean

A. Geometric Mean
Explanation
The geometric mean is not a measure of central tendency because it is used to calculate the average of a set of numbers that are multiplied together, rather than added together like in the case of the arithmetic mean, median, and mode. The geometric mean is commonly used in situations where the values being averaged are proportional or have a multiplicative relationship, such as calculating average growth rates or average rates of return.

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• 7.

### Which of the following is NOT an advantage of using a median?

• A.

Extreme values do not affect the median as strongly as they affect Mean

• B.

A median can be calculated for qualitative descriptions

• C.

Median is easy to understand

• D.

Median can be calculated even for open-ended classes

D. Median can be calculated even for open-ended classes
Explanation
The median cannot be calculated for open-ended classes because it requires the data to be arranged in order. Open-ended classes do not have specific values, so it is not possible to determine the exact position of the median.

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• 8.

### The measure which helps to understand the spread of variation is called as __________

• A.

Quartile 1

• B.

Cpk

• C.

Mode

• D.

Variance

D. Variance
Explanation
Variance is a statistical measure that helps to understand the spread of variation in a dataset. It calculates the average of the squared differences between each data point and the mean. A higher variance indicates a wider spread of data points, while a lower variance indicates a narrower spread. Therefore, variance is a useful measure for understanding the extent to which data points deviate from the mean and provides insights into the overall variability of the dataset.

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• 9.

### The distance between Quartile1 (Q1) and Quartile3 (Q3) is called as __________ and it helps to understand ___________ of process variation.

• A.

Inter Quartile Range and Width

• B.

Quartile Range and Height

• C.

Quartile 2 and Width

• D.

Median and Width

A. Inter Quartile Range and Width
Explanation
The distance between Quartile1 (Q1) and Quartile3 (Q3) is called the Inter Quartile Range (IQR) and it helps to understand the spread of process variation. The IQR represents the range of values that the middle 50% of the data falls within, excluding outliers. It is a measure of dispersion that is not affected by extreme values, making it useful in identifying the variability within the central portion of the data. The width of the IQR represents the extent of this spread, providing insight into the overall range of values within which the majority of the data falls.

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• 10.

### Box Plot Graph is used to_______________________ . The choice of answer could be more than one.  [multiple choice]

• A.

Identify outliers

• B.

Differentiate before and after Improvements.

• C.

It is suited for time ordered data and parametric distribution.

• D.

B and C only

A. Identify outliers
B. Differentiate before and after Improvements.
Explanation
The Box Plot Graph is a useful tool for identifying outliers in a dataset and differentiating before and after improvements. It allows us to visually analyze the distribution of data, identify any extreme values or outliers that may exist, and compare the distribution before and after certain improvements or interventions have been made. It is particularly suited for time-ordered data and parametric distribution, making it a valuable tool in data analysis and decision-making processes.

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• 11.

### The Graph which helps to identify and prioritize problems to be solved

• A.

Control Chart

• B.

Histogram Chart

• C.

Fish Bone Graph

• D.

Pareto Chart

D. Pareto Chart
Explanation
A Pareto Chart is a graph that helps to identify and prioritize problems to be solved. It is based on the Pareto principle, which states that a small number of causes are responsible for a large percentage of the problems or issues. The chart displays the frequency or count of each problem or issue in descending order, along with a cumulative percentage line. This allows the user to easily identify the most significant problems that should be addressed first. The Pareto Chart is a useful tool in problem-solving and decision-making processes.

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• 12.

### The Control Chart would help us to determine whether the process is

• A.

Stable

• B.

Capable

• C.

Correlation

• D.

Prediction

A. Stable
Explanation
A control chart is a statistical tool used to monitor and control a process over time. It helps in determining whether the process is stable or not. A stable process is one that is consistent and predictable, with variation that is within acceptable limits. By analyzing the data plotted on a control chart, we can identify any patterns or trends that may indicate instability in the process. Therefore, the control chart would help us determine whether the process is stable or not.

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• 13.

### What kind of Graph would help us to analyze stability of non parametric distribution of data points

• A.

P Chart

• B.

I-mR Chart

• C.

C Chart

• D.

Box Plot

D. Box Plot
Explanation
A box plot is a type of graph that provides a visual representation of the distribution of data points in a dataset. It consists of a box that represents the interquartile range (IQR) of the data, with a line inside the box indicating the median. The "whiskers" extend from the box to show the range of the data, excluding outliers. By analyzing the box plot, we can easily identify the spread, skewness, and presence of outliers in the non-parametric distribution of data points. Therefore, a box plot is the most suitable graph for analyzing the stability of a non-parametric distribution.

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• 14.

### If the sample value of sub group size is n=1, choose the appropriate type of control chart for outlier analysis.

• A.

P Chart

• B.

I-mR Chart

• C.

C Chart

• D.

NP Chart

B. I-mR Chart
Explanation
The I-mR Chart, also known as the Individuals and Moving Range Chart, is the appropriate type of control chart for outlier analysis when the sample value of subgroup size is n=1. This chart is used to monitor continuous data and is particularly useful when the subgroup size is small or variable. It helps identify any individual data points that fall outside of the expected range, indicating potential outliers in the process. The chart consists of individual data points plotted over time, along with the moving range between consecutive data points, allowing for the detection of both systematic and random variation in the process.

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• 15.

### If special causes assigned in the process variations, then the UCL and LCL would be recomputed without removing those outliers. (True/False)

• A.

True

• B.

False

B. False
Explanation
The correct answer is False. If special causes are assigned in the process variations, the UCL and LCL would not be recomputed without removing those outliers. In statistical process control, special causes are considered to be non-random and indicate that the process is out of control. In such cases, it is important to identify and remove these special causes before recalculating the control limits. This ensures that the control limits accurately represent the variation caused by common causes and help in detecting any further deviations from the desired process performance.

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• 16.

### All the data points lie within UCL & LCL and 10 out of 11 data points on one side of mean value(central limit), indicate whether the process is having____________

• A.

Special causes

• B.

Common causes

• C.

Assignable causes

• D.

Outliers

B. Common causes
Explanation
The given information suggests that the data points are within the control limits (UCL & LCL), indicating that the process is stable and under statistical control. Additionally, the fact that 10 out of 11 data points are on one side of the mean value suggests that the process is exhibiting a common cause variation. Common causes refer to the inherent variability within a process that is expected and can be attributed to the system itself. Therefore, the process is likely experiencing common causes rather than special causes, assignable causes, or outliers.

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• 17.

### In Control chart interpretations, how many business rules (Shewart Rule’s) will be used to interpret for stable process.

• A.

5 Rules

• B.

7 Rules

• C.

6 Rules

• D.

8 Rules

B. 7 Rules
Explanation
In Control chart interpretations, 7 Shewart Rules are used to interpret for a stable process. These rules help in identifying any patterns or trends that may indicate that the process is out of control. By applying these rules, any deviations from the expected pattern can be detected and appropriate actions can be taken to bring the process back to stability. These rules are an essential tool in quality control and process improvement.

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• 18.

### Which of the following tools indicates a relationship between X and Y variables, and provides a visual correlation coefficient.

• A.

Cause (X) and Effect (Y) Diagram

• B.

Pareto Chart

• C.

Scatter Diagram

• D.

Control Chart

C. Scatter Diagram
Explanation
A scatter diagram is a tool that indicates a relationship between X and Y variables by plotting data points on a graph. It provides a visual representation of the correlation between the variables, allowing for the identification of patterns or trends. The scatter diagram also calculates a correlation coefficient, which quantifies the strength and direction of the relationship between the variables. Therefore, a scatter diagram is the correct answer as it fulfills both criteria mentioned in the question.

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• 19.

### The data set is having 100 values of effort variance in % for different project releases, indicate what type of distributions would be suited for understanding the process behavior

• A.

Poison

• B.

Binomial

• C.

Normal

• D.

Exponential

C. Normal
Explanation
The normal distribution would be suited for understanding the process behavior in this data set because it is commonly used to model continuous data and is characterized by a bell-shaped curve. Since the data represents effort variance in % for different project releases, which is a continuous variable, the normal distribution would provide a good fit for analyzing the variability of the data and identifying any patterns or trends.

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• 20.

### The area under the curve value is 1, then the mean, median and mode values would be same (True/False)

• A.

True

• B.

False

A. True
Explanation
If the area under the curve is 1, it means that the entire distribution is accounted for and there are no gaps or missing values. In such a case, the mean, median, and mode values would be the same. The mean represents the average value of the distribution, the median represents the middle value, and the mode represents the most frequently occurring value. When the area under the curve is 1, it indicates a symmetrical distribution, where the mean, median, and mode all coincide at the center of the distribution. Therefore, the statement "The mean, median, and mode values would be same" is true.

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• 21.

### The Organization Specification limits are + 5 or – 5 % where as Control Limits are + 6 % &  -2% , justify whether the Process is

• A.

Stable

• B.

Capable

• C.

Within control

• D.

None of the above

D. None of the above
Explanation
The process is none of the above because the organization specification limits and control limits are not within the same range. The organization specification limits are +5% or -5%, while the control limits are +6% and -2%. This means that the process is not stable, capable, or within control according to both sets of limits.

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• 22.

### A process has its CPk value less than 1. The process is __________ .

• A.

Stable

• B.

Capable

• C.

Not Capable

• D.

None of the above

C. Not Capable
Explanation
If a process has a CPk value less than 1, it indicates that the process is not capable. CPk is a measure of process capability, specifically the ability of a process to consistently produce output within specified limits. A CPk value less than 1 suggests that the process is not able to meet the required specifications consistently, indicating that it is not capable. Therefore, the correct answer is "Not Capable".

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• 23.

### The design and code review effort is high (process is effective) in a project, and it results in less number of defects injected in UAT phase. Identify the appropriate type of correlation between review effort and number of defects. (Assume that “r” value is good).

• A.

Positive Correlation

• B.

Strong Negative Correlation

• C.

Non linear Correlation

• D.

Strong Positive Correlation

B. Strong Negative Correlation
Explanation
A strong negative correlation means that as one variable increases, the other variable decreases. In this case, the design and code review effort is high, which means that more effort is being put into reviewing the design and code. As a result, there are less number of defects injected in the UAT phase. This indicates that the more effort put into the review, the fewer defects are found, showing a strong negative correlation between review effort and number of defects.

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• 24.

### In a project, defect density increases and Productivity decreases in subsequent releases. Indicate what kind of relationship that you can interpret in this pair (x, y)?

• A.

Weak Positive Correlation

• B.

Strong Negative Correlation

• C.

No relation

• D.

Strong Positive Correlation

B. Strong Negative Correlation
Explanation
The given answer suggests that there is a strong negative correlation between defect density and productivity in subsequent releases of the project. This means that as the defect density increases, the productivity decreases. The strong negative correlation implies that there is a clear and consistent inverse relationship between these two variables, indicating that as one variable increases, the other consistently decreases.

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• 25.

### ___________________determines the nature of relationship which would help us to make predictions.

• A.

Correlation Analysis

• B.

Regression Analysis

• C.

Stability Analysis

• D.

Capability Analysis

B. Regression Analysis
Explanation
Regression analysis is a statistical technique used to determine the nature of the relationship between variables. It helps us make predictions by identifying the strength and direction of the relationship between a dependent variable and one or more independent variables. By analyzing the data and calculating the regression equation, we can estimate the value of the dependent variable based on the values of the independent variables. Therefore, regression analysis is a suitable method for determining the nature of the relationship and making predictions.

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• 26.

### A software development process has UAT Defect density as Y, percent review effectiveness as X1 and percent design phase effort as X2. Indicate the type of  regression model Y= -0.1320 X1 + 0.16 X2 + 23.200

• A.

Single Linear Regression

• B.

Dummy Variable Regression

• C.

Multi Linear Regression

• D.

Logistic Regression

C. Multi Linear Regression
Explanation
The given regression model includes two independent variables, X1 and X2, which indicates that it is a multi linear regression model. In multi linear regression, the dependent variable is predicted based on multiple independent variables. Therefore, the given equation Y= -0.1320 X1 + 0.16 X2 + 23.200 represents a multi linear regression model.

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• 27.

### What is the Probability value of the area under the curve between +1.0 and +2.0 Standard deviation units in Normal Distribution?

• A.

0.3413

• B.

0.4772

• C.

0.1359

• D.

0.8185

B. 0.4772
Explanation
The probability value of the area under the curve between +1.0 and +2.0 standard deviation units in a normal distribution is 0.4772. This means that there is a 47.72% chance that a randomly selected value from the distribution falls within this range.

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• 28.

### Three Standard Deviations on left and right side of the mean would include what % of the total data points in Normal Distribution?

• A.

68 %

• B.

97 %

• C.

99 %

• D.

95 %

C. 99 %
Explanation
In a normal distribution, approximately 99% of the data points fall within three standard deviations on both the left and right sides of the mean. This means that the remaining 1% of the data points are outliers that fall outside this range. This is a commonly used rule in statistics known as the 68-95-99.7 rule, which states that approximately 68% of the data falls within one standard deviation, 95% falls within two standard deviations, and 99.7% falls within three standard deviations of the mean.

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• 29.

### What percentage of data is included in +/- 1.5 Sigma

• A.

43.32 %

• B.

68.27 %

• C.

86.64 %

• D.

0%

B. 68.27 %
Explanation
In a normal distribution (a bell-shaped curve), approximately 68.27% of the data falls within one standard deviation (σ) of the mean in both directions. This means that within +/- 1σ from the mean, you would find about 68.27% of the data.

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• 30.

### What is the percentage of perfection in a process operating at +/- 3 Sigma level

• A.

99.999660 %

• B.

99.999999. %

• C.

99.976700 %

• D.

3.4 DPMO

C. 99.976700 %
Explanation
The correct answer is 99.976700%. In statistical terms, a process operating at +/- 3 Sigma level means that it has a defect rate of 0.27%. To calculate the percentage of perfection, we subtract the defect rate from 100%. Therefore, the percentage of perfection in this case is 100% - 0.27% = 99.976700%.

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• 31.

### One of the most popular measures of variability in a data set or population is ______________.

• A.

Dispersion

• B.

Variation

• C.

Mean

• D.

Standard Deviation

D. Standard Deviation
Explanation
Standard deviation is a widely used measure of variability in a data set or population. It provides information about how spread out the values are from the mean. A higher standard deviation indicates a greater dispersion of data points, while a lower standard deviation suggests that the data points are closer to the mean. Therefore, standard deviation is a reliable measure to assess the variability or dispersion of a dataset.

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• 32.

### Which of the below statistical tests helps in decision making based on data inferences?

• A.

Mode

• B.

Hypothesis Test

• C.

Skewness

• D.

Stability Test

B. Hypothesis Test
Explanation
Hypothesis tests are statistical tests that assist in decision making based on data inferences. These tests involve formulating a null hypothesis and an alternative hypothesis, collecting data, and then using statistical methods to determine whether there is enough evidence to reject the null hypothesis in favor of the alternative hypothesis. This helps in making decisions about the population parameter being tested, such as determining if a new treatment is effective or if there is a significant difference between two groups.

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• 33.

### If you are a Team Lead encountering a positively skewed normal distribution curve for Defect Leakage Rate, then what will you conclude from the following?

• A.

Process is stable

• B.

Process is within limits

• C.

Process needs Corrective action over Defects

• D.

Process is influenced by special cause variation

C. Process needs Corrective action over Defects
Explanation
If a Team Lead encounters a positively skewed normal distribution curve for Defect Leakage Rate, it means that the process is not stable. A positively skewed distribution indicates that there are more defects occurring at higher values, which suggests that there may be underlying issues or factors causing the defects. Therefore, the correct conclusion from the given options is that the process needs corrective action over defects to address and improve the high defect rate.

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• 34.

### In which condition of the following, a data set is a said to be a normal distribution?

• A.

If Cpk Value is > 1

• B.

If R Value between -1 to +1

• C.

If P value < 0.05

• D.

If P value > = 0.05

D. If P value > = 0.05
Explanation
A data set is said to have a normal distribution if the p-value is greater than or equal to 0.05. This means that there is not enough evidence to reject the null hypothesis that the data follows a normal distribution. In other words, the data is likely to be normally distributed if the p-value is greater than or equal to 0.05.

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• 35.

### You are a Project Manager wanting to compare on time delivery (%) of Team Leads across 4 teams, your choice of technique would be?

• A.

Hypothesis Testing

• B.

Histograms

• C.

Pareto chart

• D.

Box Plots

D. Box Plots
Explanation
Box plots would be the most suitable technique for comparing the on-time delivery (%) of Team Leads across 4 teams. Box plots provide a visual representation of the distribution of data, including the median, quartiles, and any outliers. By using box plots, the Project Manager can easily compare the on-time delivery performance of each Team Lead and identify any variations or outliers among the teams. This technique allows for a quick and effective comparison of the data, helping the Project Manager make informed decisions and take appropriate actions to improve on-time delivery across the teams.

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• 36.

### Post delivery defects are aimed to be < 4. What will be your action, if your Project delivers 10 defects on an average?

• A.

You will Change your Specification limits

• B.

Shift your specification limits to target

• C.

Shift your mean performance within specification limits

• D.

No action required

C. Shift your mean performance within specification limits
Explanation
If the project is delivering 10 defects on average, it means that the current mean performance is outside of the specified limits. Therefore, the appropriate action would be to shift the mean performance within the specification limits. This can be achieved by identifying and addressing the root causes of the defects, making necessary improvements, and ensuring that the project meets the target of less than 4 defects. Changing the specification limits or shifting the limits to target may not address the underlying issues causing the defects, so shifting the mean performance is the most suitable action in this scenario.

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• 37.

### An observation above upper Control limit is concluded as?

• A.

Process special cause variation

• B.

Process common cause variation

• C.

Process performance

• D.

No variation

A. Process special cause variation
Explanation
When an observation is above the upper control limit, it indicates that the process has experienced a special cause variation. Special cause variations are sporadic and unpredictable events that occur outside the normal range of process variation. They are often caused by factors that are not inherent to the process and can be identified and eliminated. This observation suggests that there is a specific reason or event that caused the process to deviate from its usual performance, and it needs to be investigated and addressed to bring the process back under control.

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• 38.

### In your project, Review effort (hrs, X) and defect rate (no. of defects per hour, Y) show a negative correlation. It means :

• A.

As Defect rate increases, Review effort also increases

• B.

Negative correlation does not infer any relationship between Review effort and defect Factors

• C.

As Defect Rate decreases, Review effort also decreases

• D.

As Defect Rate increases, Review Effort Hrs decreases

D. As Defect Rate increases, Review Effort Hrs decreases
Explanation
As the given statement states that there is a negative correlation between review effort (hrs) and defect rate (no. of defects per hour), it means that as the defect rate increases, the review effort hours decrease. This implies that when there are more defects per hour, less time is required for reviewing and addressing them. Therefore, the correct answer is "As Defect Rate increases, Review Effort Hrs decreases."

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• 39.

### What is the outocme of Hypothesis Testing, where P Value > = 0.05 ?

• A.

Accept Alternate Hypothesis

• B.

Reject Null

• C.

Accept Null Hypothesis

• D.

Data is normal

C. Accept Null Hypothesis
Explanation
When the P-value is greater than or equal to 0.05, it means that the observed data is not statistically significant enough to reject the null hypothesis. Therefore, the correct outcome of hypothesis testing in this case would be to accept the null hypothesis. This implies that there is not enough evidence to support the alternative hypothesis and any observed differences or relationships in the data can be attributed to chance or random variation.

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• 40.

### If the effort variance of your project shows a negatively skewed normal distribution curve, what will you infer from the following?

• A.

This means that the project is proactively finishing ahead of time

• B.

Project is in control

• C.

Project is influenced by lot of special causes

• D.

None of the above

A. This means that the project is proactively finishing ahead of time
Explanation
A negatively skewed normal distribution curve indicates that the majority of the data points are concentrated towards the right side of the curve, with a few extreme values towards the left side. In the context of project management, if the effort variance of a project shows a negatively skewed normal distribution curve, it means that most of the actual effort expended on the project is less than the expected effort. This suggests that the project is proactively finishing ahead of time, as the actual effort is less than anticipated.

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• 41.

### Kano Model depicts the following from the customer, EXCEPT

• A.

Delighters

• B.

Satisfiers

• C.

Must-Be

• D.

Objections

D. Objections
Explanation
The Kano Model is a tool used to analyze customer preferences and prioritize product features. It categorizes customer requirements into four categories: Delighters, Satisfiers, Must-Be, and Indifferent. Delighters are unexpected features that exceed customer expectations, Satisfiers are features that meet customer expectations, and Must-Be are basic requirements that must be fulfilled. The model does not depict objections, which are concerns or issues raised by customers regarding a product or service.

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• 42.

### Critical to Quality parameters are derived from

• A.

Voice of Customer

• B.

Measure of central tendency

• C.

Data dispersion diagrams

• D.

Regression analysis

A. Voice of Customer
Explanation
Critical to Quality parameters are derived from the Voice of Customer. The Voice of Customer refers to the feedback, needs, and expectations of the customers. By understanding and analyzing the Voice of Customer, organizations can identify the key quality parameters that are most important to their customers. This information helps in setting quality targets, designing products or services, and making improvements to meet customer expectations and enhance customer satisfaction.

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• 43.

### Voice of Customer is

• A.

A table to collect raw voices of Customers

• B.

A software tool to automatically update customer feedbacks

• C.

First used in Measure phase

• D.

All of the above

A. A table to collect raw voices of Customers
Explanation
The correct answer is "A table to collect raw voices of Customers." This means that Voice of Customer is a method or system used to gather and document the feedback, opinions, and preferences of customers. It involves creating a table or database where customer feedback can be collected in its raw form, without any interpretation or analysis. This information can then be used to understand customer needs and expectations, and make improvements to products or services.

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• 44.

### Cost of quality includes the following except:

• A.

Cost of Appraisal

• B.

Cost of Prevention

• C.

Cost of Change management and external consultancy

• D.

Cost of failures

C. Cost of Change management and external consultancy
Explanation
The cost of change management and external consultancy is not included in the cost of quality. The cost of quality refers to the expenses incurred in order to prevent defects and failures, as well as the costs associated with appraising and evaluating the quality of products or services. Change management and external consultancy, although important aspects of business operations, are not directly related to the cost of quality.

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• 45.

### Following have been exponents of Quality evolution except:

• A.

Juran

• B.

Philip Crossby

• C.

Wockhardt

• D.

Deming

C. Wockhardt
Explanation
Wockhardt is not an exponent of Quality evolution. Juran, Philip Crossby, and Deming are well-known figures in the field of quality management and have made significant contributions to the evolution of quality practices. However, Wockhardt is a pharmaceutical company and not an individual or organization associated with quality management. Therefore, it can be concluded that Wockhardt is not an exponent of Quality evolution.

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• 46.

### Which one of the following is not a Process Improvement Methodology

• A.

Lean

• B.

Six Sigma

• C.

Theory of Constraints

• D.

Kano Model

D. Kano Model
Explanation
The Kano Model is not a Process Improvement Methodology. It is a customer satisfaction model developed by Noriaki Kano in the 1980s. The Kano Model helps in understanding and categorizing customer preferences and requirements. It classifies customer needs into five categories: must-be, one-dimensional, attractive, indifferent, and reverse. This model is used to prioritize and improve product features based on customer satisfaction. While Lean, Six Sigma, and Theory of Constraints are all process improvement methodologies that focus on eliminating waste, reducing variation, and optimizing processes, the Kano Model is not directly related to process improvement.

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• 47.

### Six Sigma is a term used to indicate that there are 6 Standard Deviations below and above the process Mean and within upper and lower specification limits.

• A.

True

• B.

False

A. True
Explanation
The statement is true because Six Sigma is a statistical measure used to indicate the level of quality in a process. It represents that there are six standard deviations between the process mean and the nearest specification limit, with three standard deviations below the mean and three above it. This means that the process is highly capable and has very low variation, leading to a high level of quality and customer satisfaction.

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• 48.

### Quality and the Critical-to-Quality (CTQ’s) are both subjective terms that are defined by the _______________.

• A.

Management team

• B.

Line Supervisor

• C.

Customer

• D.

Design team

C. Customer
Explanation
Quality and Critical-to-Quality (CTQ's) are subjective terms that are defined by the customer. The customer is the ultimate judge of whether a product or service meets their expectations and requirements. Their feedback and satisfaction are crucial in determining the quality of a product or service. The management team, line supervisor, and design team may have their own perspectives and criteria for quality, but ultimately it is the customer's perception that matters the most.

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• 49.

### Which of the following are characteristics of the inputs to a process? [Multiple choice]

• A.

These are referred to as the x variables

• B.

These are the "causes" that create the effect

• C.

A process output is a function of its inputs

• D.

None of the above

A. These are referred to as the x variables
B. These are the "causes" that create the effect
C. A process output is a function of its inputs
Explanation
The inputs to a process are referred to as the x variables because they are the independent variables that can be manipulated or controlled. These inputs are also considered the "causes" that create the effect or the outcome of the process. The process output is a function of its inputs, meaning that the result or output of the process is determined by the values or characteristics of the inputs.

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• 50.

### Which of the following Six Sigma tool qualifies Voice of Customer:

• A.

Kano Model

• B.

Control charts

• C.

Regression analysis

• D.

Value stream mapping

A. Kano Model
Explanation
The Kano Model is a Six Sigma tool that qualifies the Voice of Customer. It is used to categorize customer requirements into different categories based on their impact on customer satisfaction. The model helps in understanding customer needs and preferences, allowing organizations to prioritize and focus on the most critical requirements. It helps in identifying the features that delight customers and those that are basic expectations. By using the Kano Model, organizations can align their products and services with customer expectations, leading to improved customer satisfaction and loyalty.

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• Current Version
• Nov 09, 2023
Quiz Edited by
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• Nov 02, 2011
Quiz Created by
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