Training or Development Class Information

Statistical Data Analysis using Microsoft Excel

Statistical Data Analysis using Microsoft Excel, Nairobi, Kenya
Training or Development Class Title
Statistical Data Analysis using Microsoft Excel
Event Type
Training or Development Class
Training or Development Class Date
15-02-2021 to 19-02-2021
Last Date for Applying
Nairobi, Kenya

Organization Name / Organize By
FineResults Research Services
Organizing/Related Departments
FineResults Research Services
Organization Type
Training or Development Class Category
Both (Technical & Non Technical)
Training or Development Class Level
All (State/Province/Region, National & International)
Related Industries


Business Development

Nairobi, Kenya


FineResults Research Services invites you to training on:

Statistical Data Analysis using Microsoft Excel

DATE: 15th to 19th  February 2021

COST: USD 800 Or Ksh 65000



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.



5 Days



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 Sparklines 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



Subgroup Correlations

Scatterplots of Data by Subgroups

Overlay Scatterplots



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






This training can also be customized for your institution upon request. You can also have it delivered your preferred location. For further inquiries, please contact us through Mobile: +254 759 285 295. You can also email us on: [email protected]



Participants should be reasonably proficient in English. During the trainings, participants should come with their own laptops.



The course fee covers the course tuition, training materials, two break refreshments, lunch, and study visits.



Accommodation is arranged upon request. For reservations contact us through Mobile: +254 759 285 295 or Email: [email protected]



Payment should be transferred to FineResults Research Services bank  account before commencement of training. Send proof of payment through the email: [email protected]



  • All requests for cancellations must be received in writing.
  • Changes will become effective on the date of written confirmation being received.


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Registration Fees
Not Mention
Registration Ways
FineResults Research services Training Center 
Official Email ID
Edith Warigia

[email protected]

   +254 759 285 295