Basic understanding of data is vital in this respect. The course will run again from the 14 September , to find out more please visit the course page. Before you go Did you find this article on Twitter , LinkedIn or Facebook? Remember to go back and share it with your friends and colleagues! Products and Services Products and Services.
Products and Services Our innovative products and services for learners, authors and customers are based on world-class research and are relevant, exciting and inspiring. About Us We unlock the potential of millions of people worldwide.
You are here: Home Blogs The misinterpretation of data: why we all need to be data literate. Data literacy is a life skill Data is often thought of as something scary, an intimidating and impenetrable set of facts or figures.
Data is everywhere, but how do we make sense of it? This is a really good course to change your perception, improve your skills and give you the confidence to deal with data. Telling a story through data Data story telling is about helping an audience develop a connection to the information presented.
I thought I was data driven prior to this course but now I am even more keen on looking at the story that data tells with a more critical lens. As someone who is an end user of reports, this course has helped me understand how data is presented in statistical reports and the pros and cons of each type. For example, there might be an association between eating at restaurants and better cardiovascular health. That might lead you to believe there is a causal connection between the two.
You can avoid this error by remembering to think about third factors when you see a correlation. Could that third factor cause both observed outcomes? A lot of mischief occurs in the scaling and labelling of the vertical axis on graphs.
But sometimes the graph maker chooses a narrower range to make a small difference or association look more impactful. On a scale from 0 to , two columns might look the same height. But if you graph the same data only showing from Be especially sceptical of unlabelled graphs.
Festival of Social Science — Aberdeen, Aberdeenshire. Edition: Available editions United Kingdom. Become an author Sign up as a reader Sign in. Where are the error bars? Assuming small differences are meaningful Many of the daily fluctuations in the stock market represent chance rather than anything meaningful.
The Daily did mention that numerous factors contribute to changes in the crime rate. However, it looks as if some journalists took this statement to be a fact. The connections found in the newspaper headlines are purely speculation and were not revealed in the objective data. The journalists misinterpreted the release most likely because they misunderstood the underlying causes and effects of crime. Statistics Canada representatives spend much time reviewing the media use of release data each day.
These representatives also answer media questions regarding the data and make certain that the data are properly understood. If a misunderstanding has occurred, then the representatives try their best to correct it. It is important to understand the statistical definitions and concepts behind the information that you are using. If you are examining labour force issues, you should become familiar with the definitions for terms such as unemployment , employment , and participation rate.
If you are looking at data on environmental issues, you will need to consider the definition and concepts associated with words such as forest , woodland , extinct , endangered species , and national park. A great advantage of statistical information is that it can be compared, allowing trends and characteristics to be revealed. For example, one can compare the weather of Vancouver with that of Halifax, past sporting results with the present, or the academic performance of men with that of women.
However, problems can arise in the comparison of statistics when the underlying definitions, classification or methods of data collection are different.
This is especially true for statistics from different sources. Nowhere is this more apparent than with vital statistics. Consider Table 1 below. According to Statistics Canada, the definition of married includes people who are legally married and living together, those who are legally married and separated, and those who are living in common-law unions. If you were to compare the numbers in the table with numbers from a survey that did not include 'common-law' in the 'married' category, the results would be very different since the definitions are not the same.
Look at the data in the above table. Why do they indicate that there are more married women than men? Logically, the two numbers should be the same. What appears to be happening here is that individuals are attaching their own definitions to the term married , and this causes the numbers to be slightly different.
0コメント