https://file.aiquickdraw.com/mathbot/file/1725462868842m64zaale.jpg

I see the assignment image you've uploaded. Let's break down the questions shown and solve them one by one.

### Question 1
The first question asks about the description of the data points shown in a graph (Figure 3) with \( X_1 \) and \( X_2 \) axes. The graph seems to represent an ellipse.

To accurately determine the answer, I'll need to infer the following:
- What the horizontal and vertical axes represent.
- The distribution pattern of the data points.

Since the image suggests analyzing how the data points are distributed, the correct answer will likely describe the shape, orientation, and relation of these points.

The given options are:
- (4, 4)
- (4, 5)
- (5, 4)
- (5, 5)

**Analysis:** Based on the ellipse shown in the figure, it's crucial to determine how far the ellipse extends along the \( X_1 \) (horizontal) and \( X_2 \) (vertical) axes.

### Question 2
This question involves selecting the correct options that relate to steps in the MDA (Multidimensional Data Analysis) process. The options include:
- Normalize the data
- Minimize the intra-class scatter
- Maximize the inter-class scatter

Here, it's important to understand the basic steps in MDA:
1. **Normalization** is usually the first step to ensure all variables contribute equally.
2. **Minimizing intra-class scatter** means making the data points within a class more similar.
3. **Maximizing inter-class scatter** means increasing the distance between different classes.

The given choices are combinations of these steps.

### Next Steps:
I will provide detailed solutions based on the analysis:

1. **First Question Solution:** Based on the distribution in the graph, identify the ellipse’s relation to the given points and determine the answer.
2. **Second Question Solution:** List the correct steps in MDA and compare them with the provided options.

Would you like detailed explanations for these questions, or should I directly proceed with the solutions?

Assessing the data points in an ellipse and determining the appropriate steps in MDA (Multidimensional Data Analysis) based on the given options.

This guide explores how to assess data points within an ellipse, followed by identifying the correct steps in the Multidimensional Data Analysis (MDA) process, including data normalization, minimizing intra-class scatter, and maximizing inter-class scatter.

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