Statistical Data Analysis using Microsoft Excel

INTRODUCTION

Microsoft Excel is a very powerful tool for statistical data analysis. In fact there are numerous instances when a data analyst does not require to use other specialized data analysis software such as SPSS, Stata, R, etc, as long as they have access to Microsoft Office Excel. This course will help improve participants' familiarity with Excel statistical functions and hence achieve great effectiveness and efficiency in research. The course describes how to use the Analysis ToolPack in Microsoft Excel, numerous statistical functions and data management techniques as applicable in most research endevours. An explanation of Excel limitation and how to overcome them will also be provided. Keen attention would be made in guiding participants on how to present results from Microsoft Excel data analysis as well as writing research reports.

DURATION

5 Days

COURSE OBJECTIVES

By the end of this training, participants will become knowledgeable in the following:

• Data management techniques using Microsoft Excel
• Descriptive statistics and methods of results interpretation and presentation.
• Multivariate methods of data analysis and subsequent methods of results interpretation and presentation.
• Selection of appropriate statistical model.
• How to present/communicate data analysis results.

Course Outline

Module 1:

Data management in Microsoft Excel

• Computing new variable information
• Protecting data in Microsoft Excel
• Generating variables through calculations
• How to remove unwanted characters in data
• How to compare data
• Finding and searching data in Excel
• Substituting and replacing data in Excel
• Outlining Data
• Sorting data
• Formatting text data into columns
• Cleaning of data using flash fill
• Detecting and removing duplicate data
• Selecting data that meets a certain criteria

Preparing data for analysis

• How to Create a Structured Reference Table
• Conditional formatting
• What-If Analysis
• Data Validation
• How to consolidate worksheet data
• Importing/Exporting data in/from Excel
• Pivot tables
• Using Excel data form to add, edit and delete records (rows) and display only those records that meet certain criteria.
• Using macros to automate Excel data management tasks
• Using Sparkline’s in Excel to graph data in cells.

Descriptive Statistics

Measures of Variability and Central Tendency  

• Describing quantitative data
• Describing qualitative data

Excel Graphics

• Graphing quantitative data
• Graphing qualitative data

Module 2: Correlation, Chi-square and mean comparison analysis

Correlation  

• Correlation
• Subgroup Correlations
• Scatterplots of Data by Subgroups
• Overlay Scatterplots

Chi-Square 

• Goodness of Fit Chi Square All Categories Equal
• Goodness of Fit Chi Square Categories Unequal
• Chi Square for Contingency Tables

Comparing Means

• Confidence Interval for the Mean
• Test of Hypothesis Concerning the Population Mean
• Difference Between Mean of Two Populations
• One Sample t-tests
• Paired Sample t-tests
• Independent Samples t-tests
•  Comparing Means Using One-Way ANOVA 

Module 3: Important Excel functions

• Text Functions
• Logical Functions
• Information Functions
• Date and Time Functions
• Lookup and Reference Functions
• Math and Trig Functions
• Statistical Functions
• Other Functions

 Module 4: Data Analysis (continued)

• Normal Distribution
• Regression Analysis
• Analysis of Covariance

Module 5: Analysing Data in Time and Forecasting

Analysing Data in Time

• Trends/Regression line
• Linear, Logarithmic, Polynomial, Power, Exponential, Moving Average Smoothing
• Seasonal fluctuations analysis

Forecasting

• Extrapolation