Data analysis and Reports

Data reporting is the process of collecting and submitting data to authorities entrusted with compiling statistics. Accurate data reporting gives rise to accurate analyses of the facts on the ground; inaccurate data reporting can lead to vastly uninformed decisions based on erroneous evidence. When data is not reported, the problem is known as underreporting; the opposite problem leads to false positives.

Data reporting can be an incredibly difficult endeavor. Census bureaus may hire even hundreds of thousands of workers to achieve the task of counting all of the residents of a country.Teachers use data from student assessments to determine grades; cellphone manufacturers rely on sales data from retailers to point the way to which models to increase production of. The effective management of nearly any company relies on accurate data.Poor data reporting leads to flawed information in the hands of decision-makers and journalists, especially when they fail to scrutinize the data and blindly trust the assertions of the data reporters. For example, poor data reporting from a crowd-sourced website led to a highly incorrect article by FiveThirtyEight.[citation needed]

Hickey’ debut article for the site, which ironically used unreliable data in an example about properly interpreting statistics, attempted to determine the entrée item at McDonald’s that provided the highest calorie count for the money. The mathematical techniques that he used (dividing the calorie total by the price) were flawless,[citation needed] as were the calorie counts, which McDonald’s provides as the law requires and which serve as an example of accurate data reporting. However, when Hickey looked to collect data on prices at McDonald’s, he relied on a website that in turn relied on unpaid “crowd-sourced” data reporting.[citation needed]

Hickey’s data reporting was inaccurate,[citation needed] including the improbable assertion that a two-patty cheeseburger cost less than a one-patty cheeseburger. Since Hickey failed to review or scrutinize the incorrectly reported data, his analysis failed on multiple levels, leading to several blatantly false conclusions.[citation needed] After publication, reader complaints convinced Hickey to insert a correction for the prices of one of the burgers, but he failed to notice any of the other errors in his article. As none of the site’s editors (including noted statistician Nate Silver) caught the errorData analysis, also known as analysis of data or data analytics, is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social science domains.

Data mining is a particular data analysis technique that focuses on modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing on business information.In statistical applications data analysis can be divided into descriptive statistics, exploratory data analysis (EDA), and confirmatory data analysis (CDA). EDA focuses on discovering new features in the data and CDA on confirming or falsifying existing hypotheses. Predictive analytics focuses on application of statistical models for predictive forecasting or classification, while text analytics applies statistical, linguistic, and structural techniques to extract and classify information from textual sources, a species of unstructured data. All are varieties of data analysis.

Data integration is a precursor to data analysis, and data analysis is closely linked to data visualization and data dissemination. The term data analysis is sometimes used as a synonym for data modeling.