MPM1D – Exam Review
Chapter 2: Relations
1. Distance-time graphs
 These graphs show how someone moves over time.
 The time is along the x-axis and the distance is along the y-axis.
 The slope of the line is the speed:
i. A steep slope means the person is moving fast
ii. A positive slope means the person is moving away from the object, a
negative slope means they are moving towards the object.
iii. A horizontal (flat) line means there is no movement.
2. Correlation (positive, negative, no correlation)
 Positive correlation means if one variable goes up, the other one also goes up.
For example: number of times per week eating at McDonald’s and weight
gained.
 Negative correlation means if one variable goes up, the other one goes down.
For example: price of an album on iTunes and number of people who buy it.
 No correlation means if one variable goes up, the other one won’t change. For
example: number of courses taken at school and number of siblings.
3. Independent and dependent variables
 The independent variable is the variable you need to know first. Its value
determines the value of the dependent variable.
 The dependent variable is the one that you measure or calculate based on the
value of the independent variable.
 In equations, tables of values, and graphs, x is the independent variable and y
is the dependent variable.
4. Scatter plots
 Determine your dependent and independent variables.
 Plot the points. Be careful not to mix up x and y, and remember that positive
means up or to the right, negative means down or to the left.
 Label your graph. This means add a title, label each axis, and include units.
 Look for outliers: an outlier is a point that doesn’t fit the trend. It is very far
away from all other points.
 Draw a line of best fit. This line passes through or close to as many points as
possible. There should be about as many points above the line as below the
line.
 Interpolation means using your line of best fit to estimate a value that is
between two points on your graph.
 Extrapolation means using your line of best fit to estimate a value that is
outside your graph (past all your points).