You will learn to calculate and apply to real-world examples the most important uncertainty measures used in business, including classification error rates, entropy of information, and confidence intervals for linear regression.Р”Р„ll the data you need is provided within the course, all assignments are designed to be done in MS Excel, and you will learn enough Excel to complete all assignments. Your role as a data-analyst is to reduce uncertainty for decision-makers by a financially valuable increment, while quantifying how much uncertainty remains. The second big idea this course seeks to demonstrate is that your data-analysis results cannot and should not aim to eliminate all uncertainty. The two models should demonstrate to you in a practical, hands-on way the idea that your choice of business metric drives your choice of an optimal model. Your first model will focus on minimizing default risk, and your second on maximizing bank profits. In the Final Project (module 6) you will assume the role of a business data analyst for a bank, and develop two different predictive models to determine which applicants for credit cards should be accepted and which rejected. This course will prepare you to design and implement realistic predictive models based on data. We use Excel to do our calculations, and all math formulas are given as Excel Spreadsheets, but we do not attempt to cover Excel Macros, Visual Basic, Pivot Tables, or other intermediate-to-advanced Excel functionality. Upon successful completion of this course, students will be able to analyze and visualize data using Microsoft Excel and associated tools.Important: The focus of this course is on math - specifically, data-analysis concepts and methods - not on Excel for its own sake. This course is designed for students who already have foundational knowledge and skills in Excel and who wish to perform robust and advanced data and statistical analysis with Microsoft Excel using PivotTables, use tools such as Power Pivot and the Data Analysis ToolPak to analyze data, and visualize data and insights using advanced visualizations in charts and dashboards in Excel. These capabilities enable people who use Excel for data analysis to turn data into thoughtful action. Excel can connect to a wide range of data sources, perform robust data analysis, and create diverse and robust data-backed visualizations to show insights and trends, and create reports. MicrosoftР’В® ExcelР’В® is designed for this purpose. Beyond the analysis, data analysts in all job roles must be able toР”В®ffectively present and communicate their findings in visually compelling ways. Leveraging that data effectively can provide timely insights and competitiveР”Вata to find issues, insights, and opportunities is now a critical part of many Storage, allowing organizations of all sorts to capture and store data. Rise of cloud computing, which provides an abundance of computational power and The era of РІР‚Сљbig dataРІР‚Сњ has exploded due to the

*Click here to view upcoming D.A.V.E classes.Р”Р„nd the data that it both collects and makes accessible is now interwoven withР”В«usinesses and lives.

Advanced data analysis with excel