menu
{ "item_title" : "Forecasting Cloud Storage Consumption Using Regression Model", "item_author" : [" Abdallah Ziraba", "Mbata David "], "item_description" : "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.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/3/66/866/040/3668660409_b.jpg", "price_data" : { "retail_price" : "37.90", "online_price" : "37.90", "our_price" : "37.90", "club_price" : "37.90", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Forecasting Cloud Storage Consumption Using Regression Model|Abdallah Ziraba

Forecasting Cloud Storage Consumption Using Regression Model

local_shippingShip to Me
In Stock.
FREE Shipping for Club Members help

Overview

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.

This item is Non-Returnable

Details

  • ISBN-13: 9783668660403
  • ISBN-10: 3668660409
  • Publisher: Grin Verlag
  • Publish Date: March 2018
  • Dimensions: 10 x 7 x 0.04 inches
  • Shipping Weight: 0.12 pounds
  • Page Count: 20

Related Categories

You May Also Like...

    1

BAM Customer Reviews