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Cutting Edge Data Analytical Tools
Published in Chong Ho Alex Yu, Data Mining and Exploration, 2022
Although IBM SPSS Statistics includes several data mining and predictive modeling tools, its primary function is to run traditional statistics. The major data mining software application offered by IBM is SPSS Modeler, which uses a flow-chart interface for quick development and deployment of predictive modeling. SPSS Modeler can be used for mining numeric data. For texting mining an additional module named SPSS Modeler Premium is needed. SPSS Modeler can be used as a standalone module on a local computer, but it can also be used in a distributed network (IBM 2020). Figure 3.10 displays a typical SPSS modeler project. Like many other modern data mining tools, SPSS modeler allows the user to drag and drop icons representing different functions into the canvas to generate a sequence of actions. In addition, SPSS Modeler offers many automated procedures, such as Auto Classifier, Auto Numeric, Auto Cluster, etc. (see Figure 3.10). In this example, after Auto Cluster is placed on the canvas, the system explores different clustering algorithms and then suggests the best solution to the user.
Statistical Process and Quality Control
Published in William M. Mendenhall, Terry L. Sincich, Statistics for Engineering and the Sciences, 2016
William M. Mendenhall, Terry L. Sincich
Cola bottle filling process. A soft-drink bottling company is interested in monitoring the amount of cola injected into 16-ounce bottles by a particular filling head. The process is entirely automated and operates 24 hours a day. At 6:00 a.m. and 6:00 p.m. each day, a new dispenser of carbon dioxide capable of producing 20,000 gallons of cola is hooked up to the filling machine. To monitor the process using control charts, the company decided to sample five consecutive bottles of cola each hour beginning at 6:15 A.m. (i.e., 6:15 A.m., 7:15 A.m., 8:15 A.m., etc.). The data for the first day are saved in the file. An SPSS descriptive statistics printout for the data is shown below.
Measuring smart office index as part of smart building: A case from Telkom Landmark Tower
Published in Indira Rachmawati, Ratih Hendayani, Managing Learning Organization in Industry 4.0, 2020
Indrawati, M.R.M. Siahaan, H. Amani
At the time of the interview, the informants underwent a process of evaluating variables and indicators; besides being asked about their perceptions per indicator, they were also asked for their perceptions per variable. This was intended as a way for researchers to perform inferential statistics. The first hypothesis examined the relationship between indicators and variables, and the second addressed the relationship between variables of smart offices. In this study, researchers performed calculations using the Spearman rank correlation. Data processing was completed using IBM SPSS Statistics 17 software. The result of the calculation is shown in Table 1.
Eye-tracking study of the celebrity effect on microblogging browsing: an example from Sina microblog
Published in Behaviour & Information Technology, 2021
Huishan Pang, Ying Ge, Jibo He, Lingcong Zhang
In this study, the experimental data were first exported from the SMI Corporation's eye movement analysis software SMI BeGaze 2.0 in the.txt format. Then, the data was imported into Microsoft Office Excel 2010, collated and organised into a format suitable for SPSS processing, and then imported into the software package SPSS 18.0 for performing statistical analysis. G-power 3.1.6 were employed to analyse the size of the effect.