Material Data Set Worksheet In 150 to 350 words, define and describe structured data sets. Use at least one outside source in your response. Structured data sets are information or data that is organized in a uniform manner so that a computer can identify it and process it. Structured data is commonly used for things like templates, drop down lists, medical vocabularies (LOINC or SNOMED CT), and boxes that can be checked (Futrell, 2013). Information that is organized in structured data sets can
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Littletown Café Data Analysis QNT/275 January 25, 2016 The Littletown Café has a different schedule it’s busy season and off season. Careful analysis of statistical data will aid in future decisions for the business. By using qualitative and qualitative data, information gathered can determine the number of staff that is needed for the busy season. Graphs and charts are used when presenting this type of data to show variations between seasons. As with any data, there can be several factors
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Paper 258-2013 Data Set Compression using COMPRESS= ABSTRACT DUE TO AN INCREASED AWARENESS ABOUT DATA MINING, TEXT MINING AND BIG DATA APPLICATIONS ACROSS ALL DOMAINS THE VALUE OF DATA HAS BEEN REALIZED AND IS RESULTING IN DATA SETS WITH A LARGE NUMBER OF VARIABLES AND INCREASED OBSERVATION SIZE. OFTEN IT TAKES A LOT OF TIME TO PROCESS THESE DATASETS WHICH CAN HAVE AN IMPACT ON DELIVERY TIMELINES. WHEN THERE IS LIMITED PERMANENT STORAGE SPACE, STORING SUCH LARGE DATASETS MAY CAUSE SERIOUS PROBLEMS
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July 6, 2014 Data Set Student | Gender | Age | Years of Work Experience | Time Spent on the Homework | Jenny | F | 35 | 11 | 2.5 | Sandy | F | 52 | 6 | 4 | Linda | F | 47 | 25 | 3 | Lilly | F | 25 | 7 | 2 | Nichole | F | 43 | 5 | 4.5 | Sally | F | 60 | 30 | 3.5 | Lisa | F | 38 | 2 | 4 | Brook | F | 22 | 4 | 1.5 | John | M | 23 | 5 | 2 | Dave | M | 32 | 14 | 2.5 | Shawn | M | 54 | 31 | 5 | Kurt | M | 29 | 7 | 3 | Brandon | M | 36 | 18 | 4.5 | Brian | M | 42 | 26 |
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research data about Gender, Probability factors and several other data sets that they need to use for reporting purposes. This data will help the AIU make sound and responsible decisions in regards to the data that they are looking to collect. Memo To: Director, American Intellectual Union From: John C. Carter Date: 8/2/2014 Subject: Distribution and Probability of data collected Dear Sir: As we discussed in earlier meetings, the AIU is looking for research data to help provide
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patterns in data set, to summarize the information revealed in a data set and to present information in a convenient form that individuals can use to make decisions (Singpurwalla, 2013).Descriptive statistics main goal is to describe a data set, hence the class of descriptive statistics include both numerical measures and graphical displays of data. Inferential statistics utilizes sample data to make estimates, decisions, predictions, or other generalizations about a larger set of data (Singpurwalla
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“the science that deals with the collection, classification, analysis, and interpretation of information or data.” Thus, a statistician isn’t just someone who calculates batting averages at baseball games or tabulates the results of a Gallup poll. Professional statisticians are trained in statistical science—that is, they are trained in collecting numerical information in the form of data, evaluating it, and drawing conclusions from it. Furthermore, statisticians determine what information is relevant
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numerical facts or data, and that, by use of mathematical theories of probability, imposes order and regularity on aggregates of more or less disparate elements (2015).” Identify different types and levels of statistics Types and levels of statistics include: Descriptive statistics: numerical and graphical methods that observe patterns in data set to give a summary of the information so it can be presented in an understandable format. Inferential statistics: is sample data that comes up
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tractable even for larger data sets, dealing with as high as 60000 data sets in our case. * KNN algorithm is analytically tractable. * KNN algorithm is highly adaptive to local information. We have used Euclidean distance metrics in our KNN algorithm to estimate the closest data points. Thus the algorithm is able to take full advantage of the local information in the training datasets to form a highly nonlinear, highly adaptive decision boundaries for each data point. * KNN algorithm
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electronics has had difficulty with their circuit board manufacturing and has attempted to determine the problem. Thirty samples were taken of four boards each due to unacceptable variability and the results from each data set were placed in a chart. (Staff Writer, 2010) CHART 1 – Sample Data DATA | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 1 | 4.92 | 4.65 | 5.77 | 6.25 | 5.27 | 5.22 | 5.47 | 5.71 | 5.24 | 4.42 | 5.14 | 4.92 | 5.79 | 4.92 | 5.68 | 2 | 4.26 | 5.54 | 5.26 | 4
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