Scatter Plots Quick Check%0D%0A5 of 55 of 5 Items%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0AQuestion%0D%0AUse the image to answer the question.%0D%0A%0D%0A%0D%0A%0D%0AWhat are the characteristics of the graph?%0D%0A%0D%0A(1 point)%0D%0AResponses%0D%0A%0D%0AThere is one cluster and one outlier.%0D%0AThere is one cluster and one outlier.%0D%0A%0D%0AThere are no outliers.%0D%0AThere are no outliers.%0D%0A%0D%0AThere are no clusters.%0D%0AThere are no clusters.%0D%0A%0D%0AThere are no outliers and one cluster.
Based on the given information, the characteristics of the graph are:
- There is one cluster and one outlier.
There is one cluster and one outlier.
To determine the characteristics of the graph, we need to analyze the image provided. Unfortunately, as an AI text-based bot, I cannot directly observe or analyze images. However, I can guide you on how to analyze scatter plots in general.
A scatter plot is a graph that displays the relationship between two sets of data. It consists of plotting individual data points on a horizontal and vertical axis using dots, which allows us to identify patterns or trends in the data.
To analyze a scatter plot, you should consider the following characteristics:
1. Clusters: Look for groups of data points that are closely packed together. These clusters indicate a possible relationship or correlation between the two variables being plotted.
2. Outliers: Look for individual data points that are significantly different from the majority of the other points. Outliers can suggest exceptions or extreme values in the data.
Based on the responses given, it seems that the question is asking about the number of clusters and outliers in the graph. The options provided are as follows:
- "There is one cluster and one outlier."
- "There are no outliers."
- "There are no clusters."
- "There are no outliers and one cluster."
Without being able to directly observe the image, it is difficult to determine the correct answer. However, you can analyze the scatter plot yourself by looking for closely packed groups of dots (clusters) and any individual points that stand out (outliers). Once you have identified these patterns, you can select the most appropriate response from the given options.