Name: Essential Mathematics for Data Analysis in Microsoft Excel
Rating: 5.0 (5 reviews)

Data analysis is inextricably linked with maths. While statistics are the most important mathematical element, it also requires a good understanding of different formulas and mathematical inference.

This course is designed to build up your understanding of the essential maths required for data analytics. It’s been designed for anybody who would like to refresh their maths knowledge or learn it in a simplified way before embarking on further data analytics training.

Build your knowledge of basic statistics

Explore summary statistics and learn how to make statistical predictions so that you can analyse data across any field or discipline. You’ll discover how to apply statistical methods to your data, and will practice the formula required to do that so that you can analyse and understand your data sets.

Understand simple mathematical notation

Mathematical notations include numbers, variables, delimiters, functions, relational symbols, and operator symbols. You’ll learn basic notation and expressions, and find out how they are applied to Excel formulas to complete simple calculations.

Apply your maths to business forecasting methods

Once you have a good understanding of the maths behind it, you’ll move onto forecasting future trends using your data. You’ll apply inferential maths to your data sets and calculate business metrics and KPIs to turn your new knowledge into genuine business value.

Syllabus

Week 1
Introduction to Working with Data
- About this Course
  This activity introduces you to the course outline and the learning outcomes, as well as information on navigating the course on the FutureLearn platform and your CloudSwyft Hands-on Labs
- Introduction to Data and Variables
  Understanding how to set up a tidy set of data and to extract data from a data set are integral skills for statistical analysis.
- Types of Data
  Here you will be introduced to the different types of data that are common when analysing data sets.
- Notation
  Understanding how to represent data using formulas as well as being able to work with different formulas is a core skill for a data analyst. This activity introduces you to unpacking formulas.
- Means and Deviations
  One of the most common things to calculate in data is the mean average of the range. In this activity, you will also be introduced to the formula for calculating standard deviation.
- Weekly Wrap Up
  This marks the end of the week’s activities. First, we will start off with recap of the week, followed by a preview of what can be expected in the week to follow.
Week 2
Summarising and Graphically Representing Data
- Summarising Data with Distributions and Graphs
  In this activity, we will understand why histograms are a good way to represent data and to identify the skewness of a data set.
- Bar Graphs and Pie Charts
  In this activity, we will explore why Pie Charts are not a great way to represent statistical data and how Bar Graphs differ from Histograms.
- Mode, Mean and Median
  There are different ways to find the centre of our data set. We shall explore each of them in this activity.
- SD vs IQR
  Standard deviation does not always give us an accurate result, so we will introduce the semi-interquartile range as another option for finding the deviation of our mean.
- Proportions
  When dealing with categorical data, it is important to take proportions into account to get a better view of our data.
- Weekly Wrap Up
  You have come to the end of your week's learning. Take a moment to review what you have learnt and track your progress.
Week 3
Business Statistics and KPI's
- Business Statistics
  Being able to apply your knowledge about data analysis in the business world is a fundamental skill. In this activity, we will look at applying statistics using business maths and creating KPIs.
- Business KPIs
  In this activity, you will be able to put into practice your knowledge of Business Statistics.
- Introduction to Inferential Math and Forecasting
  Forecasting is an important step that every business needs to implement in order to project future stability. Using past trends, we are able to forecast future likelihoods.
- Course Wrap Up
  You have reached the end of this course! Now it's time to check your knowledge and recap what you have learned.

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Who is this accredited by?

Microsoft:

This course is accredited by Microsoft

Learning on this course

On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.

What will you achieve?

By the end of the course, you‘ll be able to...

Demonstrate how to handle data sets for analysis purposes
Apply mathematical notations
Calculate business metrics and KPIs to derive business value from data sets
Summarize data with distributions and graphs

Who is the course for?

This course is for anybody who would like to refresh their maths, statistics, and mathematical notation in order to be a better data analyst. This may include aspiring data analysts or new managers who need to upskill to understand the data within their business.

What software or tools do you need?

The upgrade version of this course will include all the required CloudSwyft Hands-On Lab practice environments to be used by students and learners on this course, powered by CloudSwyft.

You will need a computer running Windows, Mac OSX or Linux, and a web browser.

Who developed the course?

CloudSwyft Global Systems, Inc.

CloudSwyft has partnered with the top global technology companies to deliver cutting edge digital skills learning across the modern workplace.

About this ExpertTrack

Learn data analysis from scratch, including an introduction to essential maths and Microsoft Excel.

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