๐ Topic Summary
Scatter plots are a fantastic way to visualize the relationship between two different variables. Each point on the plot represents a single observation, and its position is determined by the values of the two variables. By looking at the overall pattern of the points, we can get an idea of whether there's a correlation (a trend) between the variables. Scatter plots can show positive correlations (as one variable increases, the other tends to increase), negative correlations (as one variable increases, the other tends to decrease), or no correlation at all (the points are scattered randomly). They're super useful in science, business, and even everyday life to spot trends and patterns!
๐ Part A: Vocabulary
Match the term with its definition:
| Term |
Definition |
| 1. Correlation |
A. A graph of plotted points that shows the relationship between two sets of data. |
| 2. Positive Correlation |
B. A correlation where as one variable increases, the other variable tends to decrease. |
| 3. Negative Correlation |
C. A measure of the extent to which two variables are related. |
| 4. No Correlation |
D. A correlation where there is no clear relationship between the two variables. |
| 5. Scatter Plot |
E. A correlation where as one variable increases, the other variable tends to increase. |
Match the terms with their correct definitions: 1-C, 2-E, 3-B, 4-D, 5-A
โ๏ธ Part B: Fill in the Blanks
Scatter plots help us visualize the (1) between two variables. A trend that shows an upward direction is a (2) correlation. When there is no visible pattern, it is considered (3) correlation. Scatter plots are used in many fields to identify potential (4) and make (5).
Answers: 1. relationship, 2. positive, 3. no, 4. trends, 5. predictions
๐ค Part C: Critical Thinking
Imagine you collect data on the number of hours students study per week and their exam scores. How might you use a scatter plot to analyze this data, and what conclusions could you potentially draw from it?