In figure matrices, if one pattern (like superimposition) seems too complex or doesn't work, try a simpler logic. Count elements, shaded regions, or number of lines. Sometimes the pattern is numerical (e.g., 1, 2, 4) rather than purely geometric.
Step 1: Understanding the Concept:
This problem requires identifying the underlying pattern in a 3x3 matrix of figures, either row-wise or column-wise, to determine the missing figure. Step 2: Detailed Explanation:
Let's analyze the matrix row by row to find a consistent pattern. A plausible pattern relates to the number of shaded sub-sections within the main shape.
Row 1 (Triangles): The figure in column 2 has 1 shaded section. The figure in column 3 has 1 shaded section.
Row 2 (Circles): The figure in column 2 has 1 shaded section. The figure in column 3 has 2 shaded sections (a semicircle).
Row 3 (Squares): The figure in column 2 has 1 shaded section.
Let's check the options:
Option 1: 2 shaded regions.
Option 2: 4 shaded regions.
Option 3: 1 shaded region.
Option 4: The whole figure is shaded (can be considered 1 or 4 regions depending on interpretation, but the pattern is inside the 'X' division).
Option 2 fits the pattern of the number of shaded regions doubling in the third column (1 \(\rightarrow\) 2 \(\rightarrow\) 4). Step 3: Final Answer:
Following the pattern of the number of shaded regions in the third column doubling from one row to the next, the missing figure must have 4 shaded regions. Therefore, Option 2 is the correct choice.
