Data analysis

overwhelmed with data. When taking into account how much data is collected in a daily timeframe, then multiply that by 365 days in a year, the data obtained can be turned into information and help achieve advancements within the medical field. Data is defined as “uninterpreted elements such as a person’s name, weight, or age. Because they are uninterpreted, they do not have meaning (Nelson & Staggers, 2014).” In order for data to have meaning, an analysis would need to be done to translate the…

CASE STUDY: PREDICTIVE ANALYSIS MOUNIKA ENUGALA NORTHEASTERN UNIVERSITY  INTRODUCTION Predictive analysis is the process in the advanced analytics field which predicts the unknown scenarios in future. It uses lot of techniques like machine learning, data mining, probability and statistics, IT, data management etc. It brings down the results of previous input data searches and manages to understand the connections between the data thus identifying all the opportunities and risks of future which…

Big Data Analytics Introduction In this report, the term Big Data Analytics will be explained and studied, it has been broken down into sub-headings of which Big Data Analytics consists of. The following examines what Big Data is, how it benefits businesses and companies, it determines who is using Big Data and the three V’s of Big Data Analytics. This report examines what Big Data offers and the many opportunities for businesses and companies who wish to collect a lot of information from either…

Regression Analysis Regression analysis is a statistical technique used to study the relationship between variables (Draper, & Smith, 2014). It is often of interest to know the effect that one or several variables can cause on another, and even to predict, to a greater or lesser…

right of the fifth amendment. This error could also have occurred in the collection of data when the participants were asked if they texted while at work. Although, the three questions could show relationship amongst average text message person and fanatic text message person, and whether or not they choose to bed the rules to text in a compromising environment. For this researcher it is assumed that the data is flawed due to the unwillingness to be forthcoming accurate information, because of…

and Methodology As you know, the data collection has two types which are primary and secondary data. The primary data are collecting information from different sources such as observation, interviews, and survey or questionnaire. While the secondary data is information collected previously by someone else and it is available on the internet or journals and in a company the records. I choice primary data collection, which is a questionnaire. Thus primary data has advantages which are great…

Big Data you will notice big corporations like IBM, SAS, Oracle providing enterprise solutions with punch lines “Transform Your Business” and “Big Data Can Generate Big Brainstorms” promising business growth. The reality behind investing in Big Data analytics is still hidden. Today we have the tools to analyze massive amount of data but we still lack the expertise to derive correlations from it. In the public realm finding relation between health and air pollution can be an example of Big Data…

Segmentation has a great importance in digital image analysis. It is also one of the most difficult low-level image analysis tasks. Many image processing application apply segmentation as primary step. Image segmentation serve a variety of applications, such as handwritten character identification, medical image analysis as breast cancer detection, in infrared image, automatic target recognition, radar image application, and in pattern recognition application...etc. The quality of the…

The term data-driven instruction (DDI), also called data supported instruction, is a systematic approach that is used to improve student learning based on available data (Lewis, Madison-Harris, Muoneke, & Times, 2010). It is a cyclic and precise process that continually improves learner’s success. The cycle has three repetitive stages, namely, assessment, analysis, and action. The latter stages provide a school-wide support framework for improving students learning throughout the year by…

The Counterfeit Coins Problem is a well-known complex search problem in mathematics as well as in computer science. It can be related to the data structure (such as binary tree) computer program, algorithm, Graph Theory, Therefore researching this problem is meaningful. The Counterfeit Coins problem can be described as given a set of n look-alike Coins containing One Counterfeit which is a bit heavier or lighter than the genuine Coins. The objective is to find the Counterfeit Coins in minimum…