{"id":43553,"date":"2014-07-14T15:59:27","date_gmt":"2014-07-14T10:29:27","guid":{"rendered":"http:\/\/www.vskills.in\/certification\/tutorial\/?p=43553"},"modified":"2024-04-12T14:19:50","modified_gmt":"2024-04-12T08:49:50","slug":"collecting-and-summarizing-data","status":"publish","type":"page","link":"https:\/\/www.vskills.in\/certification\/tutorial\/collecting-and-summarizing-data\/","title":{"rendered":"Data collection and Data Summarizing"},"content":{"rendered":"\n<div class=\"wp-block-image\"><figure class=\"aligncenter size-large\"><a ref=\"magnificPopup\" href=\"https:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2020\/12\/Type-of-Channel-Members-9-1.png\"><img loading=\"lazy\" decoding=\"async\" width=\"750\" height=\"400\" src=\"https:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2020\/12\/Type-of-Channel-Members-9-1.png\" alt=\"Data collection and Data Summarizing\" class=\"wp-image-96750\" srcset=\"https:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2020\/12\/Type-of-Channel-Members-9-1.png 750w, https:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2020\/12\/Type-of-Channel-Members-9-1-300x160.png 300w\" sizes=\"auto, (max-width: 750px) 100vw, 750px\" \/><\/a><\/figure><\/div>\n\n\n<p>Data collection and Data Summarizing- Process improvement needs it to be measurable by data collection which is critical for any improvisation.<\/p>\n<h5><strong>Types of Data and Measurement Scales<\/strong><\/h5>\n<p><strong><span style=\"text-decoration: underline;\">Types of data<\/span><\/strong> \u2013 They are of two types, discrete and continuous.<\/p>\n<p><strong>Attribute or discrete data &#8211;<\/strong> It is based on counting like the number of processing errors, the count of customer complaints, etc. Discrete data values can only be non-negative integers such as 1, 2, 3, etc. and can be expressed as a proportion or percent (e.g., percent of x, percent good, percent bad). It includes<\/p>\n<ul>\n<li>Count or percentage \u2013 It counts of errors or % of output with errors.<\/li>\n<li>Binomial data &#8211; Data can have only one of two values like yes\/no or pass\/fail.<\/li>\n<li>Attribute-Nominal &#8211; The &#8220;data&#8221; are names or labels. Like in a company, Dept A, Dept B, Dept C or in a shop: Machine 1, Machine 2, Machine 3<\/li>\n<li>Attribute-Ordinal &#8211; The names or labels represent some value inherent in the object or item (so there is an order to the labels) like on performance &#8211; excellent, very good, good, fair, poor or tastes &#8211; mild, hot, very hot<\/li>\n<\/ul>\n<p><strong>Variable or continuous data &#8211;<\/strong> They are measured on a continuum or scale. Data values for continuous data can be any real number: 2, 3.4691, -14.21, etc. Continuous data can be recorded at many different points and are typically physical measurements like volume, length, size, width, time, temperature, cost, etc. It is more powerful than attribute as it is more precise due to decimal places which indicate accuracy levels and specificity. It is any variable measured on a continuum or scale that can be infinitely divided.<\/p>\n<p><strong>Converting Data Types<\/strong> &#8211; Continuous data, tend to be more precise due to decimal places but, need to be converted into discrete data. As continuous data contains more information than discrete data hence, during conversion to discrete data there is loss of information.<\/p>\n<p><strong>Measurement<\/strong> &#8211; A measurement is assigning numerical value to something, usually continuous elements. Measurement is a mapping from an empirical system to a selected numerical system. The four measurement scales employed are nominal, ordinal, interval, and ratio<\/p>\n<p><strong>Data collection methods<\/strong><br \/>Data collection is based on crucial aspects of what to know, from whom to know and what to do with the data.<\/p>\n<p>Few types of data collection methods includes &#8212;<\/p>\n<p><strong><span style=\"text-decoration: underline;\">Check sheets<\/span><\/strong> &#8211; It is a structured, well-prepared form for collecting and analyzing data consisting of a list of items and some indication of how often each item occurs.<\/p>\n<p><span style=\"text-decoration: underline;\"><strong>Coded data<\/strong>&#8211;<\/span> It is used when presence of too many digits are to be recorded into small blocks or during data capturing of large sequences of digits from a single observation or rounding off errors are observed whilst recording large digit numbers.<\/p>\n<p><strong><span style=\"text-decoration: underline;\">Automatic measurements<\/span><\/strong> &#8211; In it a computer or electronic equipment performs data gathering without human intervention like radioactive level in a nuclear reactor.<\/p>\n<p><strong>Techniques for Assuring Data Accuracy and Integrity<\/strong><br \/>Data collection and Data Summarizing- Data integrity and accuracy have a crucial in the data collection process as they ensure the usefulness of data being collected. Data integrity determines whether the information being measured truly represents the desired attribute and data accuracy determines the degree to which individual or average measurements agree with an accepted standard or reference value.<\/p>\n<p><strong>Sampling<\/strong> &#8211; Practically all items of population cannot be measured due to cost or being impractical hence, sampling is used to get a representative group of items to measure. Various sampling strategies are<\/p>\n<ul>\n<li><strong>Random Sampling<\/strong> &#8211; The use of a sampling plan requires randomness in sample selection and requires giving every part an equal chance of being selected for the sample. The sampling sequence must be based on an independent random plan. It is the least biased of all sampling techniques, there is no subjectivity as each member of the total population has an equal chance of being selected and can also be obtained using random number tables.<\/li>\n<li><strong>Sequential or Systematic Sampling<\/strong> \u2013 Init every nth record is selected from a list of the population. Usually, these plans are ended after the number inspected has exceeded the sample size of a sampling plan. It is used for costly or destructive testing. If the list does not contain any hidden order, this strategy is just as random as random sampling.<\/li>\n<li><strong>Stratified Sampling<\/strong> \u2013 It selects random samples from each group or process that is different. If the population has identifiable categories, or strata, that have a common characteristic, random sampling is used to select a sufficient number of units from each strata. Stratified sampling is often used to reduce sampling error. The resulting mix of samples can be biased if the proportion of the samples does not reflect the relative frequency of the groups.<\/li>\n<\/ul>\n<p><strong>Sample Homogeneity<\/strong> &#8211; It occurs when the data chosen for a sample have similar characteristics. It focuses on how similar the data are in a given sample.<\/p>\n<p><strong>Sampling Distribution of Means<\/strong> &#8211; If the means of all possible samples are obtained and organized, we could derive the sampling distribution of the means.<\/p>\n<p><strong>Sampling Error<\/strong> &#8211; The sample statistics may not always be exactly the same as their corresponding population parameters. The difference is known as the sampling error.<\/p>\n<p><strong>Graphical methods &#8211; <\/strong>They are effective tools for the visual evaluation of data is a graph showing the relationship between variables.<\/p>\n<p><strong><span style=\"text-decoration: underline;\">Box plot<\/span> <\/strong>&#8211; It is also called a box-and-whisker plot or \u201cfive number summary\u201d. It has five points of interest, which are the quartiles, the median, and the highest and lowest values and shows how the data are scattered within those ranges.<a ref=\"magnificPopup\" href=\"http:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Box-plot.png\"><img loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-43682 aligncenter\" src=\"http:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Box-plot.png\" alt=\"Box plot\" width=\"1024\" height=\"1024\" srcset=\"https:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Box-plot.png 1024w, https:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Box-plot-150x150.png 150w, https:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Box-plot-300x300.png 300w, https:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Box-plot-624x624.png 624w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/a><\/p>\n<p><strong><span style=\"text-decoration: underline;\">Stem and Leaf Plot<\/span> &#8211;<\/strong> It separates each number into a stem (all numbers but the last digit) and a leaf (the last digit) like, for the numbers 45, and 59, the stems are 4 and 5, while the leaves are 5 and 9.<\/p>\n<p style=\"text-align: center;\">\u00a0<a ref=\"magnificPopup\" href=\"http:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Stem-and-Leaf-Plot.gif\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-43687\" src=\"http:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Stem-and-Leaf-Plot.gif\" alt=\"Stem and Leaf Plot\" width=\"345\" height=\"232\" \/><\/a><\/p>\n<p><strong><span style=\"text-decoration: underline;\">Histograms<\/span> &#8211;<\/strong> It shows frequencies in data as adjacent rectangles, erected over intervals with an area proportional to the frequency of the observations in the interval.<\/p>\n<p><a ref=\"magnificPopup\" href=\"http:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Histogram.png\"><img loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-43683 aligncenter\" src=\"http:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Histogram.png\" alt=\"Histogram\" width=\"220\" height=\"220\" srcset=\"https:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Histogram.png 220w, https:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Histogram-150x150.png 150w\" sizes=\"auto, (max-width: 220px) 100vw, 220px\" \/><\/a><\/p>\n<p><strong><span style=\"text-decoration: underline;\">Run Charts<\/span> &#8211;<\/strong> It displays how a process performs over time as data points are plotted in chronological order and connected as a line graph.<\/p>\n<p><a ref=\"magnificPopup\" href=\"http:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Run-Charts.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-43685 aligncenter\" src=\"http:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Run-Charts.jpg\" alt=\"Run Charts\" width=\"639\" height=\"438\" srcset=\"https:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Run-Charts.jpg 639w, https:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Run-Charts-300x205.jpg 300w, https:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Run-Charts-624x427.jpg 624w\" sizes=\"auto, (max-width: 639px) 100vw, 639px\" \/><\/a><\/p>\n<p><strong><span style=\"text-decoration: underline;\">Scatter Diagram<\/span> <\/strong>&#8211; It is displays multiple XY coordinate data points represent the relationship between two different variables on X and Y-axis.<\/p>\n<p><a ref=\"magnificPopup\" href=\"http:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Scatter-Diagram.png\"><img loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-43686 aligncenter\" src=\"http:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Scatter-Diagram.png\" alt=\"Scatter Diagram\" width=\"240\" height=\"239\" srcset=\"https:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Scatter-Diagram.png 240w, https:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Scatter-Diagram-150x150.png 150w\" sizes=\"auto, (max-width: 240px) 100vw, 240px\" \/><\/a><\/p>\n<p><strong><span style=\"text-decoration: underline;\">Normal Probability Plots<\/span> &#8211;<\/strong> It is used to detect the presence of normal bell curve or Gaussian distribution in the process data.<\/p>\n<p><a ref=\"magnificPopup\" href=\"http:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Normal-Probability-Plots.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-43684 aligncenter\" src=\"http:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Normal-Probability-Plots.jpg\" alt=\"Normal Probability Plots\" width=\"262\" height=\"193\" \/><\/a><\/p>\n<p><strong><span style=\"text-decoration: underline;\">Weibull Plots<\/span> &#8211;<\/strong> It is usually used to estimate the cumulative probability that a given sample will fail under certain conditions.<\/p>\n<p><a ref=\"magnificPopup\" href=\"http:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Weibull-Plots.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-43688 aligncenter\" src=\"http:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2014\/07\/Weibull-Plots.jpg\" alt=\"Weibull Plots\" width=\"262\" height=\"193\" \/><\/a><\/p>\n<p><a href=\"https:\/\/www.vskills.in\/practice\/startPracticeTest\/Six-Sigma-Green-Belt-Mock-Test\"><strong>Take Free Mock Test on Six Sigma Green Belt<\/strong> <\/a><\/p>\n<p><em><strong>Become Vskills Certified Six Green Belts Professional. Gain some knowledge on the module &#8220;Data collection and Data Summarizing&#8221;. <\/strong><\/em><\/p>\n<p><strong>Apply for Certification Exam !!<\/strong><\/p>\n<p><a href=\"https:\/\/www.vskills.in\/certification\/quality\/certified-six-sigma-green-belt-professional\"><strong>Certified Six Sigma Green Belt Professional<\/strong><\/a><\/p>\n<p>\u00a0<\/p>\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter size-large\"><a href=\"https:\/\/www.vskills.in\/practice\/six-sigma-green-belt\" target=\"_blank\" rel=\"noopener\"><img loading=\"lazy\" decoding=\"async\" width=\"961\" height=\"150\" src=\"https:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2020\/12\/TRY-FREE-PRACTICE-TEST-NOW-2-1.png\" alt=\"\" class=\"wp-image-96404\" srcset=\"https:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2020\/12\/TRY-FREE-PRACTICE-TEST-NOW-2-1.png 961w, https:\/\/www.vskills.in\/certification\/tutorial\/wp-content\/uploads\/2020\/12\/TRY-FREE-PRACTICE-TEST-NOW-2-1-300x47.png 300w\" sizes=\"auto, (max-width: 961px) 100vw, 961px\" \/><\/a><\/figure><\/div>\n\n\n\n<p><a href=\"https:\/\/www.vskills.in\/certification\/tutorial\/six-sigma-green-belt-tutorial-six-sigma-quality\/\" target=\"_blank\" rel=\"noreferrer noopener\">Go back to Tutorial<\/a>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; <a href=\"https:\/\/www.vskills.in\/certification\/certified-six-sigma-green-belt-professional\" target=\"_blank\" rel=\"noreferrer noopener\">Go to Home Page<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Data collection and Data Summarizing- Process improvement needs it to be measurable by data collection which is critical for any improvisation. Types of Data and Measurement Scales Types of data \u2013 They are of two types, discrete and continuous. Attribute or discrete data &#8211; It is based on counting like the number of processing errors,&#8230;<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"categories":[3897,6304],"tags":[6882,6868,6867,6871],"class_list":["post-43553","page","type-page","status-publish","hentry","category-quality","category-six-sigma-green-belt","tag-collecting-and-summarizing-data","tag-green-belt","tag-six-sigma","tag-tutorials"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Six Sigma Green Belt Tutorial | Data collection and Data Summarizing<\/title>\n<meta name=\"description\" content=\"Become Vskills Certified Six Green Belts Professional. 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