Foundation of Data Analytics
(FDNDA.AE1)
/ ISBN: 9781644592779
Foundation of Data Analytics
Enhance your data analytics skills with a Data Analytics foundation course and lab. The course and lab offer interactive learning resources that help candidates learn how to use data typologies, data analytics tools, business statistics, data visualization with the working and value of data, and many more. The course also covers the subject areas like processing, collecting, storing, and analyzing to help you in advancing your professional career. The course will help you in advancing your professional career.
Lessons

7+ Lessons

9+ Exercises

64+ Quizzes

112+ Flashcards

112+ Glossary of terms
TestPrep

51+ Pre Assessment Questions

53+ Post Assessment Questions
LiveLab

35+ LiveLab

29+ Video tutorials

38+ Minutes
 Opening Case
 Introduction
 Managers and Decision Making
 The Business Analytics Process
 Business Analytics Tools
 Business Analytics Models: Descriptive Analytics, Predictive Analytics, and Prescriptive Analytics
 Summary
 Discussion Questions
 Closing Case 1
 Closing Case 2
 Some Sample Data
 Moving Quickly with the Control Button
 Copying Formulas and Data Quickly
 Formatting Cells
 Paste Special Values
 Inserting Charts
 Locating the Find and Replace Menus
 Formulas for Locating and Pulling Values
 Using VLOOKUP to Merge Data
 Filtering and Sorting
 Using PivotTables
 Using Array Formulas
 Solving Stuff with Solver
 OpenSolver: I Wish We Didn't Need This, but We Do
 Opening Case
 Introduction
 Managing Data
 The Database Approach
 Big Data
 Data Warehouses and Data Marts
 Knowledge Management
 Summary
 Discussion Questions
 ProblemSolving Activities
 Closing Case 1
 Closing Case 2
 Introduction to Probability
 Structure of Probability
 Marginal, Union, Joint, and Conditional Probabilities
 Addition Laws
 Multiplication Laws
 Conditional Probability
 Revision of Probabilities: Bayes' Rule
 Introduction to Hypothesis Testing
 Testing Hypotheses About a Population Mean Using the z Statistic (σ Known)
 Testing Hypotheses About a Population Mean Using the t Statistic (σ Unknown)
 Testing Hypotheses About a Proportion
 Testing Hypotheses About a Variance
 Solving for Type II Errors
 Summary
 Formulas
 Supplementary Problems
 Analyzing the Databases
 Case  ColgatePalmolive Makes a “Total” Effort
 Why Should Data Scientists Know Optimization?
 Starting with a Simple TradeOff
 Fresh from the Grove to Your Glass…with a Pit Stop through a Blending Model
 Modeling Risk
 Wait, What? You're Pregnant?
 Don't Kid Yourself
 Predicting Pregnant Customers at RetailMart Using Linear Regression
 Predicting Pregnant Customers at RetailMart Using Logistic Regression
 For More Information
 Correlation
 Introduction to Simple Regression Analysis
 Determining the Equation of the Regression Line
 Residual Analysis
 Standard Error of the Estimate
 Coefficient of Determination
 Hypothesis Tests for the Slope of the Regression Model and Testing the Overall Model
 Estimation
 Using Regression to Develop a Forecasting Trend Line
 Interpreting the Output
 Summary
 Formulas
 Supplementary Problems
 Analyzing the Databases
 Case  Caterpillar, Inc.
 Getting Up and Running with R
 Doing Some Actual Data Science
 Why Do We Visualize Data?
 How Do We Visualize Data?
 Color
 Common Chart Types
 When Our Visual Processing System Betrays Us
 Every Decision Is a Compromise
 Summary
Hands on Activities (Live Labs)
 Summarizing the Aspects of Business Analytics and its Applications
 Freezing the Top Row
 Using the AVERAGE Function
 Using Relative, Absolute, and Mixed References
 Formatting Numbers
 Applying Conditional Formatting
 Using the Paste Special Feature
 Analyzing Data Using a Line Chart
 Creating a PivotTable Automatically
 Calculating the Minimum and Maximum Sales Value
 Using the SUM Function
 Using the MATCH Function
 Using the VLOOKUP Function
 Sorting Data
 Understanding Big Data
 Understanding the Relational Database Model
 Understanding Business Statistics
 Calculating the Statistics
 Using the SUMIF Function
 Using the IF Function
 Using the factor() Function
 Using the str() Function
 Using the sqrt() Function
 Using the matrix() Function
 Using the length() Function
 Using the rbind() and cbind() Functions
 Using the aggregate() Function
 Using the order() Function
 Using the predict() Function
 Using the print() Function
 Using the summary() Function
 Using the which() Function
 Visualizing Data
 Understanding Data Visualization
 Creating and Analyzing Chart Types
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