Okanagan College Library Data & Statistical Services

Few students come to us with well developed skills for working with data and statistics.

Researchers in the field have come up with five areas where we can focus in order to assist students in starting to develop their data and statistical analysis skills:

 

1.  Statistical Literacy

There is no shortage of statistical information in today's world. Students need to develop skills that help them to critically analyze statistical information in order to contextualize, interpret, and synthesize such information. Developing expertise relating to

• discerning correlation from causation
• recognizing the differences in the mean of mean, median and mode
• understanding what margin of error means
• learning how to identify potential biases in questionnaire design, data collection and analysis 

All of these skills are necessary for the comprehension of scholarly research, understanding debates in the popular media, and interpreting the various forms of information that they are subjected to on a daily basis.

Ideally all students should take a Introduction to Statistics Course. The reality is most will not.

The solution may be integrating small brief statistical literacy segments into an existing course - learning sessions that focus on understanding what the terms mean and how they are used rather than on the underlying mathematics.

Statistics Canada Introduction to Basic Statistics. 

 

2.  Data Visualization 

Students are exposed to and asked to create mapped data in the form of graphs, charts and emerging forms of visualized data ranging from infographics to complex geographical information system representations of data and statistics. We need to help them understand how to ensure that the data and statistics used for such endeavors is sound in nature and properly prepared for its intended purpose.

Ideally every student would take a course in data visualization. Reality is that few will. More than likely they are going to learn about it through trial and error using one of the wide array of visualization software available to them.

The solution: maybe building in a segment where students examine and discuss the strengths and weaknesses of data visualization into an existing course. Then examine the tools and techniques employed in data visualization.

Data Visualization Statistics Canada style. 

 

3. Data in Argument 

Our students need to be able to put together data and statistical facts in a fashion that allows them to support the position from both information and persuasive points of view.  They need to identify information, data  and statistics, and then to use it to create arguments that form the basis of their research papers.

Statistics Canada - Telling the data story: How to create stories that matter.

 

4. Reliability and the Challenges of Data Cleaning

One of the most important tasks when working with data is knowing that it is of good and reliable quality (this is why we tend to point students towards using official statistical agencies such as Statistics Canada).

With the availability of data and statistics (Open Access Data) on the Internet and the advent of Big Data there is a real and present danger that students end up working with such data and statistical information.

A simple project that you can incorporate in to a class is a data analysis assignment using a modified version of the CRAAP test and a small data clean up project.

 

5. Ethical Data Use

Data and statistical information are not inherently good or bad, but they can be framed, edited, manipulated and presented in an unethical manner.  

This is probably the most important aspect of skills development for students. An in class discussion of what makes data good or bad examining using actual world examples.