Review the key concepts, formulae, and examples before starting your quiz.
🔑Concepts
A Scatter Diagram is a graphical representation of the relationship between two variables, where each point represents a pair of data values.
Correlation describes the nature of the relationship: Positive correlation means as increases, increases; Negative correlation means as increases, decreases.
The Strength of correlation (Strong, Moderate, or Weak) indicates how closely the data points cluster around a straight line.
The Line of Best Fit (or Trend Line) is a straight line that best represents the data on a scatter plot. It should pass through the mean point . Natural variation means roughly half the points should be above the line and half below.
Interpolation is the process of estimating a value within the range of the given data set. This is generally considered reliable.
Extrapolation is the process of predicting a value outside the range of the given data. This is less reliable as the trend may not continue.
📐Formulae
💡Examples
Problem 1:
A student records the number of hours spent studying () and the test scores () for five students: . Calculate the mean point .
Solution:
First, calculate : . Then, calculate : . The mean point is .
Explanation:
The mean point is the average of all -coordinates and all -coordinates. Every line of best fit must pass through this point.
Problem 2:
A line of best fit passes through the mean point and another point . Find the equation of the line in the form .
Solution:
Find the gradient : Substitute and point into : The equation is .
Explanation:
Using the gradient formula and one known point (the mean point), we can determine the specific linear relationship between the variables.
Problem 3:
Using the equation , predict the test score for a student who studies for hours and hours. Identify which prediction is interpolation.
Solution:
For : . For : . Since the original data range for study hours was between and , the prediction for hours is interpolation.
Explanation:
Predictions within the observed range () are interpolations. Predictions outside this range are extrapolations and may result in impossible values (like a score of if the test is out of ).