Random Sample
A simple random sample is a subset of a statistical population in which each member of the subset has an equal probability of being chosen. An example of a simple random sample would be the names of 25 employees being chosen out of a hat from a company of 250 employees.
Root Cause Analysis
Root Cause Analysis is a process or procedure that helps guide people to discover and understand the initiating causes of a problem, with the goal of determining missing or inadequately applied controls that will prevent recurrence.
Reliability
The ability of an apparatus, machine, or system to consistently perform its intended or required function or mission, on demand and without degradation or failure.
Sampling
Sampling is a process used in statistical analysis in which a predetermined number of observations are taken from a larger population. The methodology used to sample from a larger population depends on the type of analysis being performed but may include simple random sampling or systematic sampling.
Scorecard
A scorecard is an evaluation device, usually in the form of a questionnaire, which specifies the criteria your customers will use to rate your business’s performance in satisfying their requirements.
Segmentation
Segmentation means to divide the marketplace into parts, or segments, which are definable, accessible, actionable, and profitable and have a growth potential. In other words, a company would find it impossible to target the entire market, because of time, cost and effort restrictions. It needs to have a 'definable' segment - a mass of people who can be identified and targeted with reasonable effort, cost and time.
Sigma Level
Determining sigma levels of processes (one sigma, six sigma, etc.) allows process performance to be compared throughout an entire organization because it is independent of the process. It is merely a determination of opportunities and defects. However, the terms are appropriately defined for that specific process.
Sigma is a statistical term that measures how much a process varies from perfection, based on the number of defects per million units.
- One Sigma = 690,000 per million units
- Two Sigma = 308,000 per million units
- Three Sigma = 66,800 per million units
- Four Sigma = 6,210 per million units
- Five Sigma = 230 per million units
- Six Sigma = 3.4 per million units
SIPOC Diagram
SIPOC diagrams are useful for focusing a discussion and helping team members agree upon a common language and understanding of a process for continuous improvement. In Six Sigma, SIPOC is often used during the “define” phase of the DMAIC improvement steps.
Six Sigma
Six Sigma is a method that provides organizations tools to improve the capability of their business processes. This increase in performance and decrease in process variation lead to defect reduction and improvement in profits, employee morale, and quality of products or services.
Six Sigma Strategy
The Six Sigma strategy was initially developed in 1986 by officials with Motorola, U. S. A. By 2010; it had become a dominant factor in the management of businesses across many industries. Its fundamental goal is to enhance the quality of processes and outputs through the identification and removal of defects. To this end, it also minimizes the variability of business and manufacturing procedures.
SWOT Analysis
SWOT Analysis is a useful technique for understanding your Strengths and Weaknesses, and for identifying both the Opportunities open to you and the Threats you face. Used in a business context, it helps you carve a sustainable niche in your market. Employed in a personal context Add to My Personal Learning Plan, it helps you develop your career in a way that takes the best advantage of your talents, abilities, and opportunities.
T-test
T-tests are called t-tests because the test results are all based on t-values. T-values are an example of what statisticians call test statistics. A test statistic is a standardized value that is calculated from sample data during a hypothesis test. The procedure that calculates the test statistic compares your data to what is expected under the null hypothesis.
Each type of t-test uses a specific procedure to boil all of your sample data down to one value, the t-value. The calculations behind t-values compare your sample mean(s) to the null hypothesis and incorporate both the sample size and the variability in the data. A t-value of 0 indicates that the sample results exactly equal the null hypothesis. As the difference between the sample data and the null hypothesis increases, the absolute value of the t-value increases.
Assume that we perform a t-test and it calculates a t-value of 2 for our sample data. What does that even mean? I might as well have told you that our data equal two fit bins! We don’t know if that’s common or rare when the null hypothesis is true.
TQM
Total Quality Management is defined as a continuous effort by the management as well as employees of a particular organization to ensure long-term customer loyalty and customer satisfaction. Remember, one happy, and the satisfied customer brings ten new customers along with him whereas one disappointed individual will spread bad word of mouth and spoil several of your existing as well as potential customers.
Tree Diagram
Breaks down or stratifies ideas in progressively greater detail. The objective is to partition a big idea or problem into its smaller components, making the idea easier to understand, or the problem easier to solve.
Type I Error
In hypothesis testing, rejecting the null hypothesis (no difference) when it is, in fact, true (e.g. convicting an innocent person.)
TYPE 1 errors are those where scientists assumed a relationship where none existed. The Producers risk: Rejecting a good part.
When a point falls out of the boundary limit and the SPC system gives signal that the process is out of control or produced product is bad in Quality but nothing have gone wrong (i.e., the process is in control)
Type II Error
In hypothesis testing: failing to reject a false null hypothesis (e.g., failing to convict a guilty person).TYPE 2 errors are those where scientists assumed no relationship exists when in fact it does.Consumers Risk – Accepting and shipping bad parts.
Trend Analysis
A trend analysis is a method of analysis that allows traders to predict what will happen with stock in the future. Trend analysis is based on historical data about the stock's performance given the overall trends of the market and appropriate indicators within the market.
Trend analysis takes into account historical data points for a stock and, controlling for other factors like the general changes in the sector, market conditions, competition for similar stocks, it allows traders to forecast short, intermediate, and long-term possibilities for the stock.