Bivariate Data 1: Scatter Graphs and Identifying Trends
Learn to plot scatter graphs and identify trends for IB MYP Year 5 Standard Maths. Covers positive, negative and no correlation with real-world examples.
What Is Bivariate Data?
Bivariate data involves two variables collected from the same subjects — for example, a student's hours of study and their exam score. Analysing bivariate data allows us to explore whether a relationship exists between the two variables.
Plotting Scatter Graphs
A scatter graph displays bivariate data as a set of points on a coordinate grid. Each point represents one individual observation with one variable on the x-axis and the other on the y-axis.
Key Skills
- Choosing appropriate axes and scales
- Plotting points accurately from a table of values
- Labelling axes with variable names and units
Take care when plotting — a single misplotted point can change the perceived trend entirely.
Identifying Trends
Once plotted, you should describe the direction and strength of any visible relationship:
- Positive correlation: As x increases, y tends to increase
- Negative correlation: As x increases, y tends to decrease
- No correlation: No clear pattern between the variables
At this stage, trend identification is qualitative — you are describing what you see. Quantitative analysis of correlation comes later in the Extended pathway.
Reading Context Into the Data
MYP questions frequently present scatter graphs with a real-world scenario. Always read the axis labels carefully and connect your observations to the context. A Criterion D question might ask: "What does the trend in this graph suggest about the relationship between temperature and ice cream sales?"
Common Mistakes
- Plotting (y, x) instead of (x, y)
- Using inconsistent scale intervals on an axis
- Describing correlation when the scatter graph shows no clear pattern