Type I and II errors Mistakenly rejecting the null hypothesis is a type 1 error. These errors are not avoidable and are part of statistical testing‚ but we can lessen the occurrence by setting the significance at a lower level. However‚ by setting the significance level lower; let us say .001‚ we then increase the chance of type 2 errors. Failing to correctly reject the null hypothesis creates a type 2 error‚ this is because; according to Aron (2009) “with an extreme significance level like
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Control Charts Control charts‚ also known as Shewhart charts are tools used to determine if a manufacturing or business process is in a state of statistical control. The control chart was invented by Walter A. Shewhart‚ (also known as the father of statistical quality control) while working for Bell Labs in the 1920s. The company’s engineers were seeking to improve the reliability of their telephony transmission systems. The engineers had realized the importance of reducing variation in a manufacturing
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Statistical P S i i l Process Control C l 26 August 2009 University Malaysia Perlis P li Presented by Dr Zaharah Wahid DRZ CONSULTANT 1 An Overview of Statistical Process Control (SPC) DRZ CONSULTANT 2 What is SPC Statistical : A universal language to describe and analyse the physical variability of a process. Process : The transformation of inputs including f f man‚ machinery‚ methods‚ materials‚ energy and information to attain a desired result result. Control : To make a process
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Control Charts Control Charts are use to distinguishes between specialcause or common-cause of variation that is present in a process. There are two basic types of control charts:- Variables - Quantitative data (Measured) Attributes - Qualitative data (Counted) Variable Control Charts Use actual measurements for charting Types:- Average & Range charts Median & Range charts Average & Standard deviation charts Individual & Moving Range charts Run Charts Attribute
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for Process Improvement Module 10 CONTROL CHART CONTROL CHART 1 Basic Tools for Process Improvement What is a Control Chart? A control chart is a statistical tool used to distinguish between variation in a process resulting from common causes and variation resulting from special causes. It presents a graphic display of process stability or instability over time (Viewgraph 1). Every process has variation. Some variation may be the result of causes which are not normally present
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Calculating the Probability of a Type II Error To properly interpret the results of a test of hypothesis requires that you be able to judge the pvalue of the test. However‚ to do so also requires that you have an understanding of the relationship between Type I and Type II errors. Here‚ we describe how the probability of a Type II error is computed. A Type II error occurs when a false null hypothesis is not rejected. For example‚ if a rejection region
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forms. Organizational charts are used to visually summarize the structure of a business. By using charts to study the overview of a business’ structure‚ owners can analyze how effective operations run. By identifying bottlenecks and redundancies‚ organizations ensure smoother operations and increased efficiencies. Organizational charts display businesses from different aspects depending on the nature of the business and the needs of the chart creators. When creating charts‚ it is essential to think
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mm) of a type of shaft manufactured by a new machine are obtained from an engineering workshop. Sample No. No. of Observation 1 2 3 4 5 1 5.4 5.5 6.0 5.3 5.5 2 5.6 6.0 5.4 5.4 5.5 3 5.9 5.6 5.2 5.2 5.6 4 5.5 5.5 5.9 5.3 5.3 5 5.5 5.4 5.8 5.3 5.2 6 5.4 6.0 5.9 5.3 5.6 7 5.6 5.2 5.3 5.6 5.9 8 5.8 5.2 5.3 5.6 5.5 Construct control charts for the shaft diameter for 3-sigma limit of confidence. Find whether the process is in control or not
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conducted aiming to know the accuracy‚ specificity and sensitivity of the system‚ researchers came up with such conclusions. A technique‚ Precision and Recall‚ was used to test the system’s capability of answering the user’s questions relying from correct result
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Area Chart Figure 1: Area chart Use it to... * Display over time (or any other dimension): * How a set of data adds up to a whole (cumulated totals) * Which part of the whole each element represents Variants * Percentage: The sum always represents 100% (relative scale) * Cumulative: The sum can vary according to the elements (absolute scale) Column/Bar Chart Use it to... * Present few data over a nominal (e.g. countries‚ testing conditions‚ ...) or interval
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