# INTRODUCTION TO DATA ANALYSIS

Course:  DAI
Duration:  2 Days
Level:  I
Course Summary

Analyzing data is an important skill for any professional to possess. The existence of data in its raw collected state has very little use without some sort of processing.

Introduction to Data Analysis harnesses the power of Excel and transforms it into a tool for learning basic statistical analysis. Participants learn statistics in the context of analyzing data. Participants work with real data, analyzing real-world problems, so that they understand the subtleties and complexities of analysis that make statistics such an integral part of understanding our world.

This two-day workshop will help participants develop skills for visualizing and analyzing data. Topics include descriptive statistics, histograms, cross tabulations and pivot tables, correlation and regression, and confidence intervals. Use of graphs to explore patterns and relationships in the data is emphasized.

Throughout the workshop, Excel functionality is introduced using easy to understand examples which are demonstrated in a way that learners can become comfortable in understanding and applying them.

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Topics Covered In This Course

# Basics of Data Analysis

• Introduction to Data Analysis
• Data: The basics
• How do we analyze data ? methodologies, tools and techniques
• How to summarize and describe raw information - the data
• The main purpose of statistics: Testing a hypothesis
• Statistics: Turning information into knowledge
• Simple graphical and numerical summaries of a data set

# The Role of Statistics and the Data Analysis Process

• Understanding Statistics
• Understanding basic probability concepts
• Collecting data sensibly
• Use of simulations in data analysis investigations
• Foundations for inference: Sampling distributions
• Foundations for inference: Confidence intervals
• Inference for numerical data
• Inference for categorical data
• Sampling distributions and the Central Limit Theorem
• Introduction to linear regression
• Multiple linear regression
• T tests, including paired and two sample, assuming equal and unequal variances
• Z tests
• The Normal Distribution and Z-Scores
• P-value, or the degree of disagreement between the data and the hypothesis
• And more

# Customizing the Excel Environment

• Configure Excel Options

# Creating Advanced Functions and Formulas

• Logical functions
• Conditional functions
• Financial functions
• Text functions
• Date and time functions
• Specialized Functions
• Range Names in Formulas
• Array Formulas
• Calculation options

# Analyzing Data with Functions and Conditional Formatting

• Analyze Data by Using Text and Logical Functions

# Lookups and Data Tables

• Using lookup functions
• Creating data tables

# Organizing and Analyzing Datasets and Tables

• Create and Modify Tables
• Validating cell entries
• Sort Data
• Filter Data
• SUBTOTAL and Database Functions

# Hypothesis Testing

• Using Excel to get the critical values and the P-values needed to complete the test
• Functions used to get critical values and P-values
• Hypothesis Tests About a Proportion
• Functions that use the standard normal (z) distribution
• Hypothesis Tests About a Mean: Not Known (t-test)
• Functions that use the t-distribution
• Hypothesis Tests About a Mean: Known
• Functions that use the standard normal (z) distribution.

# Visualizing Data with Basic Charts

• Create Charts
• Modify and Format Charts

• Chart formatting options
• Combination charts
• Graphical objects

# Preparing Data and Creating PivotTables

• Prepare Data
• Working with PivotTables
• Create a PivotTable from a Local Data Source
• Create a PivotTable from Multiple Local Data Sources
• Create a PivotTable from an External Data Source
• Modifying PivotTable data

# Examining Data Using PivotTables

• Format a PivotTable
• Filter PivotTable Data
• Refresh and Change PivotTable Data
• PowerPivot

# Analyzing Data with PivotTables, Slicers, and PivotCharts

• Organize PivotTable Data
• Summarize PivotTable Data
• Analyze PivotTable Data
• Using PivotCharts
• Present Data with PivotCharts
• Filter Data by Using Slicers

# Working with PivotCharts

• Create a PivotChart
• Manipulate PivotChart Data
• Format a PivotChart
What You Can Expect

At the end of this workshop, participants will be able to:

• Apply the important concepts and techniques in data analysis using Excel 2013
• Turn real world data into business insights in Excel
• Use Excel for statistical and financial functions
• Navigate and analyze data
• Confidently use the most crucial Excel functions and techniques for analysis
• Manipulate and prep datasets in Excel
• Apply analysis techniques to datasets in Excel
• Correctly use the appropriate charts in Excel
• Understand ways to present data using charts and tables, including time series data
• Work with external databases, PivotTables, and PivotCharts
• Describe the need to build presentation ready dashboards in Excel
• Create your own formulas in Excel
• Make the most of the latest features of Excel 2013
Who Should Take This Course

Anyone who wants to learn the core concepts of data analysis and wants to be able to turn data into business insights in Excel.

Recommended Prerequisites

Familiarity with Excel, including knowing how to enter simple formulas and use built-in functions.

Training Style

Instructor led, group-paced, classroom-delivery learning model with structured hands-on activities.

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