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Available dates

Oct 28—Nov 1, 2019
5 days
Washington, District of Columbia, United States
USD 1739
USD 347 per day
Nov 18—22, 2019
5 days
Atlanta, Georgia, United States
USD 1739
USD 347 per day
Dec 2—6, 2019
5 days
Tysons, Virginia, United States
USD 1739
USD 347 per day
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About the course

Insight into sound business strategy is critical to problem-solving and decision-making within a mission-critical organization. Developing a strong foundation in data analysis techniques helps lead to this gained insight. You will learn numerous analytical techniques, including data preparation, integration, statistical analysis, and presentation skills. Working collaboratively through real-world scenarios using Microsoft Excel, you’ll be prepared to perform the most relevant, mission-critical analyses.

Learning Objectives

  • Explain the importance of data analysis and how to use Excel to analyze data for effective decision-making
  • Use ranges, reference anchors, and data tables to increase efficiency when performing data analysis
  • Demonstrate how to sort and filter data in order to identify the relevant information for problem-solving
  • Use pivot tables to summarize data to quickly gain a better understanding of it
  • Import data into Excel from a variety of sources
  • Use data retention and integration functions to effectively manage your data
  • Use text manipulation functions to turn raw data into usable data
  • Visualize data through analysis software
  • Identify real-world applications for statistical data analysis
  • Use Excel to generate descriptive statistics and interpret the data
  • Construct a frequency distribution to analyze data and translate it into relevant information
  • Calculate the likelihood that an event will occur using probability
  • Use probability distribution functions to forecast how often an outcome will occur over a period of time
  • Use sampling to avoid the potential for hidden bias in expressing statistical findings
  • Calculate the correlation between two variables and make predictions using simple linear regression
  • Use the data analysis features of Excel to assist in complex problem-solving

Course Topics

Introduction to Data Analysis

  • The Importance of Data Analysis
  • Using Excel for Data Analysis

Ranges, Anchoring, and Data Tables

  • Range References
  • Anchoring References
  • Named Ranges
  • Data Tables

Sorting and Filtering

  • Sorting Data
  • Filtering Data

Pivot Tables

  • Overview of the Pivot Table Tool
  • Creating a Pivot Table Report

Importing Data for Analysis

  • Importing Text Files for Analysis
  • Importing Data from a Database
  • Refreshing the Data

Data Retention and Integration

  • Curating and Retaining Data Sets
  • Data Integration
  • Linking Data Between Sets
  • Data Integration Functions

Text Manipulation

  • Overview of Text Manipulation Functions
  • Using Text Manipulation Functions

Charting Data

  • Levels of Measurement
  • Introduction to Charting Data
  • Formatting Charts
  • Chart Types and Applications

Introduction to Statistics

  • Statistics Overview

Descriptive Statistics

  • Measures Central Tendency
  • Measures of Variation
  • Analysis ToolPak Descriptive Statistics

Frequency Distribution

  • What Is a Frequency Distribution?
  • Creating Histograms


  • Probability in Practice
  • Counting Outcomes

Probability Distributions

  • Binomial Distribution
  • Normal Distribution

Statistical Sampling and Confidence Intervals

  • Overview of Statistical Sampling
  • Methods of Statistical Sampling
  • Statistical Error and Sample Size
  • Sampling Distribution of the Mean
  • Confidence Intervals

Correlation and Regression

  • Correlation Analysis and Applications
  • Linear Regression Analysis and Applications

Course Capstone

  • Capstone Exercise

Who should attend

This course is designed for professionals who seek formal training or a refresher course in foundational skills for data analytics.

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