Essential Mathematics for Data Analysis in Microsoft Excel
This course is designed to build up your understanding of the essential maths required for data analytics.
Duration
3 weeks
Weekly study
5 hours
Included in an ExpertTrack
Course 4 of 4
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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.
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.
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.
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.
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
Understanding how to set up a tidy set of data and to extract data from a data set are integral skills for statistical analysis.
Here you will be introduced to the different types of data that are common when analysing data sets.
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.
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.
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.
In this activity, we will understand why histograms are a good way to represent data and to identify the skewness of a data set.
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.
There are different ways to find the centre of our data set. We shall explore each of them in this activity.
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.
When dealing with categorical data, it is important to take proportions into account to get a better view of our data.
You have come to the end of your week's learning. Take a moment to review what you have learnt and track your progress.
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.
In this activity, you will be able to put into practice your knowledge of Business Statistics.
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.
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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