We use “statistics” (sometimes abbreviated “stats”) any time we collect, organize, analyse, interpret and present data. They help us to get an overview about trends and developments, they help us to understand what something is made up of. They translate data into visual images. Therefore, if we want to be informed in an objective way, it is absolutely necessary to be able to read and understand them.
You can imagine that statistics are widely used, not only in universities, laboratories or any other scientific context, but also in any jobs that need to assess data regularly. From Big Business to Startup companies, from industrial manufacturers to banks and the stock market: As soon as you work for one of these, it will be important to be able to speak about statistics – and often in the language of work and business, English.
There are different types of statistics. It all depends what you want to display, and where you want to put your focus on. So, first of all, let us get an overview about the most common types of statistics.
I. Overview: The most common types of statistics
I. Pie Charts
- with butter642
- without butter358
- Night owl768
- Early bird232
- One cushion486
- No cushion156
- Lots of cushions215
Pie charts make sense when we have a total amount of something (100%) and we then want to split this amount up into different slices. This is why this form is called a pie chart. Just think of a lovely apple pie with vanilla ice cream! Each slice represents one component and all slices add up together as a whole.
Let’s look at an example. You have a company, and you’re selling cars. In the next shareholders meeting you want to present the amount of petrol-driven cars in contrast to the amount of electric and hydrogen-powered cars. Each group represents a percentage, together they add up to a whole pie. Makes sense, right?
II. Line Graphs
Line Graphs are great tools to show information that is connected in some way, often as it changes over time. Usually we then create a timeline on the x-axis and the values on the y-axis.
A real-world use case could be a company that produces ready-made pizzas. They want to see at which period in the year people eat the largest amount of pizzas, and which type of pizza they choose. (Except Pizza Hawai’i – because that’s just awful and an insult to every Italian out there.)
Our timeline will then contain the 12 months of the year, and there will be different lines to show how many pizzas have been sold in the previous year – Pepperoni, Mushrooms, Onions,
Pineapple… you get the idea.
III. Bar charts
We use Bar Charts when we want to compare different categories of data. These bars belong to one major category, but represent different groups within this category. Each of these categories can reach 100%.
Certainly you have already dealt with your printer at home. Some printers have a typical set of ink cartridges in the CMYK pattern. (The C stands for cyan (aqua), M stands for magenta (pink), Y for yellow, and K for Key, usually black.) With four bars in a bar chart you can now see how much of each ink cartridge is left. So our major category is ink, our groups within that category are the four colors cyan, magenta, yellow and key / black.
How much time kids expend for different activities
|Kid 1||Kid 2||Kid 3|
|Binge-watching on streaming platforms||25%||37%||42%|
|Playing video games||12%||50%||23%|
Finally, tables are used when we organize data that is too detailed or complicated to be described in text or any other form. It helps our readers to see the results in an orderly and structured way.
Imagine, you are the CEO of an important company, and you want to know how well each of your 10 products is doing in the different markets around the world. This gets chaotic quite quickly if you create a pie or a bar chart; at least, you will need many of them! In a table, the first row be designated to show the markets Europe, America and Asia, while the first column contains all the different products.
Alone or together with your learning partner, revise these types of statistics and study when and why they are used. Think of other examples that could well be displayed by either one of the charts, the graph or the table.
II. Method: How to construct your analysis
Basically, an analysis of a chart, graph or table always follows this pattern:
Such an analysis is usually done in the Simple Present; unless you speak about events in the past, then you should use the appropriate tense there.
Example: Bar Chart
Take the bar chart above as an example.
Your first question or focus should always be the classical question: Who made this chart? Is the source given? Do we know when the data was collected and published, over which period it was collected…?
"The table / bar graph / line graph / pie chart with the title ... was published by ... in 2021. It deals with..."
The bar graph with the title “What share of children are not able to read with comprehension by the end of primary school age?” was published by the organisation “Our World in Data”. It is based on the data collected by researcher Joao Pedro Azevedo in 2021 in his “Will Every Child Be Able to Read by 2030?“.
It deals with the question whether the income level in different countries correlates with (has got something to do with) the ability to read by the end of primary school.
Now, it is about describing as detailed as possible. Say first how the data is displayed. Then, mention things that are striking or stand out.
"The largest share / majority of children who are not able to read with comprehension by the end of primary school age come from... The minority of them lives in... It is striking that the global average amounts to... An outstanding fact is that ...
The data is divided into six horizontal bars. Four of them show different categories of countries, split up into “Low income”, “Lower-middle income”, “Upper-middle income” and “High income”. They are shown in dark red. A “Global average” bar is shown in blue, and a bar with the “Best-performing countries” in lime green.
It is striking to notice that the percentage of children who are not able to read while comprehending the text by the end of primary school increases when the income of their parents decreases. The difference between high income countries, where one out of ten children is not really able to read and comprehend, and low income countries, where the same problem exists for nine out of ten children, is especially astonishing. Finally, it is noticeable that the problem does not really exist for the best-performing countries due to a rate of only 1.6-3%, while it must be particularly problematic for the worst-performing countries where, as mentioned, 90% suffer from this inability.
When we analyse something, we break things down and study or examine something in very close detail, in order to discover more about it. The aim of a good analysis is to explain and interpret data.
"The numbers / figures show / suggest that..."
The figures suggest that the education level in a country depends on the overall income situation.
One possible explanation is that parents who don’t earn enough in one job to provide for their family need to take on second or third jobs in order to do so. This is why they have got less time to spend with their children to read or to help them with their schoolwork.
Another possible explanation can be that a high-income level means that there are more specialized jobs, and that these jobs need a good education. If the parents already enjoyed a good education, they are more likely to pass it on to their children.
In the conclusion, we sum up: What have we learnt from our analysis of this chart, graph or table?
"From the numbers given we can draw the conclusion that..."
From the numbers given we can draw the conclusion that children are better at comprehensive reading when their parents earn more.
A consequence can be, that governments in these countries should focus even more on school politics children in order to educate a society that can take on more complex and mentally demanding jobs.
A piece of advice:
In order to practise a description of line graphs (step 2 of this analysis), there is an excellent course on ieltstutors.com. My recommendation is to study them in the following order:
Our World in Data is an excellent site with many interesting charts and graphs. Go there, select one that you’re most interested in and analyse it according to the steps mentioned above.