Scientific Study from the year 2017 in the subject Computer Science - Commercial Information Technology, grade: A, language: English, abstract: The primary aim of the study was to develop a regression model for forecasting monthly cloud storage consumption. Second, to ascertain if the month is a reliable predictor of cloud storage capacity consumed. The model was developed using Minitab18 statistical software. The dependent variable was cloud storage capacity consumed, while the independent variable was the month of cloud storage consumption. The model was validated by checking the assumptions of regression to establish its suitability in making future predictions. Twelve-month data sets was analyzed to make future prediction for each passing month. The model made predictions with near accuracy from the actual cloud storage data consumed in each month. The model determines the intervals of monthly storage consumption. The study concluded that the month is a globally significant linear predictor of cloud storage capacity consumed over a period.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Mr Ziraba Abdallah holds Masters of Education degree in Information and Communication Technology, Integration of ICT in Education, ICT and Educational Management, and ICT pedagogy from Makerere University. He is currently a lecturer at the ICT University USA, Cameroon Campus. A seasoned educationist with over 10 years of teaching experience at Secondary school and several academic institutions including Universities, Mr Ziraba has taught students from diverse social and cultural backgrounds. He possesses excellent administrative, verbal communication and written skills along with constructive and effective teaching methods that promote a stimulating learning environment. Contacts: Email: abdallah.ziraba@ictuniversity.org Phone: ]237651625643
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Scientific Study from the year 2017 in the subject Computer Science - Commercial Information Technology, grade: A, , language: English, abstract: The primary aim of the study was to develop a regression model for forecasting monthly cloud storage consumption. Second, to ascertain if the month is a reliable predictor of cloud storage capacity consumed. The model was developed using Minitab18 statistical software. The dependent variable was cloud storage capacity consumed, while the independent variable was the month of cloud storage consumption. The model was validated by checking the assumptions of regression to establish its suitability in making future predictions. Twelve-month data sets was analyzed to make future prediction for each passing month. The model made predictions with near accuracy from the actual cloud storage data consumed in each month. The model determines the intervals of monthly storage consumption. The study concluded that the month is a globally significant linear predictor of cloud storage capacity consumed over a period. N° de réf. du vendeur 9783668660403
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Scientific Study from the year 2017 in the subject Computer Science - Commercial Information Technology, grade: A, , language: English, abstract: The primary aim of the study was to develop a regression model for forecasting monthly cloud storage consumption. Second, to ascertain if the month is a reliable predictor of cloud storage capacity consumed. The model was developed using Minitab18 statistical software. The dependent variable was cloud storage capacity consumed, while the independent variable was the month of cloud storage consumption. The model was validated by checking the assumptions of regression to establish its suitability in making future predictions. Twelve-month data sets was analyzed to make future prediction for each passing month. The model made predictions with near accuracy from the actual cloud storage data consumed in each month. The model determines the intervals of monthly storage consumption. The study concluded that the month is a globally significant linear predictor of cloud storage capacity consumed over a period. 20 pp. Englisch. N° de réf. du vendeur 9783668660403
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Taschenbuch. Etat : Neu. Neuware -Scientific Study from the year 2017 in the subject Computer Science - Commercial Information Technology, grade: A, , language: English, abstract: The primary aim of the study was to develop a regression model for forecasting monthly cloud storage consumption. Second, to ascertain if the month is a reliable predictor of cloud storage capacity consumed. The model was developed using Minitab18 statistical software. The dependent variable was cloud storage capacity consumed, while the independent variable was the month of cloud storage consumption. The model was validated by checking the assumptions of regression to establish its suitability in making future predictions. Twelve-month data sets was analyzed to make future prediction for each passing month. The model made predictions with near accuracy from the actual cloud storage data consumed in each month. The model determines the intervals of monthly storage consumption. The study concluded that the month is a globally significant linear predictor of cloud storage capacity consumed over a period.Books on Demand GmbH, Überseering 33, 22297 Hamburg 20 pp. Englisch. N° de réf. du vendeur 9783668660403
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Taschenbuch. Etat : Neu. Forecasting Cloud Storage Consumption Using Regression Model | Mbata David (u. a.) | Taschenbuch | 20 S. | Englisch | 2018 | GRIN Verlag | EAN 9783668660403 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand. N° de réf. du vendeur 112533851
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