Data Analysis Course Descriptions
Introduction to Data Analysis
Data analysis is a method in which data is collected and organized so that one can derive helpful information from it. In other words, the main purpose of data analysis is to look at what the data is trying to tell us. For example, what does the data show or do? What does the data not show or do? Data analytics technologies and techniques are widely used in commercial industries to enable organizations to make more-informed business decisions and by scientists and researchers to verify or disprove scientific models, theories and hypotheses.
Data mining is the process of sorting through large data sets to identify patterns and establish relationships to solve problems through data analysis. Data mining tools allow enterprises to predict future trends.
Data visualization is the presentation of data in a pictorial or graphical format. It enables decision makers to see analytics presented visually, so they can grasp difficult concepts or identify new patterns. With interactive visualization, you can take the concept a step further by using technology to drill down into charts, graphs for more detail, interactively changing what data you see, and how it is processed.
Probability sampling is any method of sampling that utilizes some form of random selection. In order to have a random selection method, you must set up some process or procedure that assures that the different units in your population have equal probabilities of being chosen.
This course will familiarize students with the assumptions underlying various statistical techniques and assist in identifying their appropriateness in a variety of situations. Students should be able to perform statistical analysis and interpret results in a meaningful way. Students are expected to relate results of such analyses to become information-based decision makers.