Data Representation Data and instructions that are presented in a written or typed format can only be understood by the user. If the data is not in the user’s language‚ s/he will not be able to understand it. It is the same way with the computer; the computer’s language is binary 0s and 1s. The computer cannot understand typed or written instructions or data. Whenever data or instructions or input to the computer it is first converted to 0s and 1s‚ these are called binary digits (bits). There
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HATCO Data Set Description The HATCO data set gives data from a survey of customers of the HATCO company. The data set consists of 100 observations on 14 separate variables. Three types of information were collected. The first type of information is the perception of HATCO on seven attributes identified in past studies as the most influential in the choice of suppliers. The respondents‚ purchasing managers of firms buying from HATCO‚ rated HATCO on each attribute. Each of these 7 variables
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Data Processing During the collection of data‚ our group noted the effect that temperature change had on aquatic macro invertebrates. Our data was collected from three different ponds amongst the Lake Harriet/Lake Calhoun vicinity. We took samples from the bird sanctuary pond‚ Lake Calhoun holding pond and the Lake Harriet duck area. Prior to our procedure‚ we measured the temperatures of each pond area. We used the low-temperature climate (bird sanctuary pond) to compare to the higher-temperature
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5.3.3 Data cleaning Data cleaning helps to remove all unnecessary data. Data cleaning attempts to fill in missing values‚ smooth out noise while identifying outliers and correct inconsistencies in the data. Data cleaning is usually an iterative two-step process consisting of discrepancy detection and data transformation. 5.3.4 Data analysis Data analysis is also known as analysis of data or data analytics‚ is a process of inspecting‚ cleansing‚ transforming and modeling data with the goal of discovering
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Thunderbird. Weibo Jan 22 – Feb 22 (Monthly Data) Weibo: Engagement: 20+8/363=7.71% Increased from 345 to 363 Growth Rate of Followers: 345-363/345 = 5.21% Weibo Feb 23 – Mar 23 (Monthly Data) Engagement: 20+9/375=7.73% Growth Rate of Followers: 363-375/363 = 3.34% Renren.com Jan 22 – Feb 22 (Monthly Data) Engagement: 4/40 = 10% Increased 4 followers from 36 Growth Rate of Followers: = 36-40/40=10% Renren.com Feb 23 – Mar 23 (Monthly Data) Engagement: 3/47 = 6.4% Increased
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Standardized Testing Education is extremely important in today’s society. Knowledge is power. According to Christine Armario from the associated press‚ “United States’ students are continuing to trail behind their peers in a pack of higher performing nations‚ according to results from a key international assessment.” (XXX) Out of 34 countries‚ the U.S. ranked 14th in reading‚ 17th in science and 25th in math. (XXX)It is obvious that something in the education system in America is not working out
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struggle or have a disability. Also‚ it isn’t fair because it stresses students out‚ make them sleep deprived‚ or have anxiety. Too much emphasis is put on standardized testing because some students struggle to get high scores‚ they aren’t an accurate measurement of their abilities‚ and test decrease students love of learning. Standardized tests don’t take into consideration certain characteristics of a student that may affect how they perform on the test. For instance‚ when the author talked about
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Factors that influence the selection of data collection instruments Data Collection is an important aspect of any type of research study. Inaccurate data collection can impact the results of a study and ultimately lead to invalid results. Data collection methods for impact evaluation vary along a continuum. At the one end of this continuum are quantitative methods and at the other end of the continuum are Qualitative methods for data collection. A data collection instrument is a tool for monitoring
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measures widely used to measure complexity in manufacturing systems. With reference to this second framework‚ two indexes were selected (static and dynamic complexity index) and a Business Dynamic model was developed. This model was used with empirical data collected in a job shop manufacturing system in order to test the usefulness and validity of the dynamic complex index. The Business Dynamic model analyzed the trend of the index in function of different inputs in a selected work center. The results
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Distinguish between primary data and secondary data? Primary data is the data that is collected first hand from the original source for the purpose of making statistical inference while secondary data is the data that is collected by the method of abstraction and is used to make statistical inference by using primary data already collected by an investigator. Primary data is collected by Identifying population of interest choosing sample analyse sample information draw inference from
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