Are there any outliers in the data shown on the scatterplot? If so, where? (1 point) Responses Yes, at (74, 200) Yes, at left parenthesis 74 comma 200 right parenthesis Yes, at (74, 240) Yes, at left parenthesis 74 comma 240 right parenthesis Yes, at (65, 205) Yes, at left parenthesis 65 comma 205 right parenthesis No, there are no outliers in the data.
r u sure??
To determine if there are any outliers in the data shown on the scatterplot, we need to visually analyze the plot. Since the coordinates (74, 200) and (74, 240) are the only options given, we need to check if these points are visually distant from the other points on the scatterplot.
As there is no scatterplot provided in the question, I cannot determine if there are any outliers in the data.
I apologize for any confusion. Without a scatterplot provided or any specific data points mentioned, it is not possible for me to accurately determine if there are any outliers in the data.
To identify outliers on a scatterplot, we need to observe any data points that significantly deviate from the general pattern of the data. By examining the answer choices provided, we can determine if any of these points are considered outliers.
The first answer choice states that there is an outlier at (74, 200), and the second answer choice further clarifies this as "left parenthesis 74 comma 200 right parenthesis." Similarly, the third and fourth answer choices indicate an outlier at (74, 240).
However, the fifth and sixth answer choices mention an outlier at (65, 205).
To decide if any of these points are outliers, we should assess if they deviate significantly from the general pattern of the data. Without having access to the actual scatterplot, it is challenging to determine with certainty which of these points are outliers.
If you have access to the scatterplot, here is what you can do:
1. Plot the data points on a scatterplot using the provided coordinates.
2. Examine the overall pattern and distribution of the data.
3. Look for any points that seem isolated or distant from the main cluster of points.
4. Analyze if these points are significantly different from the majority of the data points.
5. Determine if they can be considered outliers based on statistical analysis or specific criteria set for the data set.
Therefore, without the scatterplot itself, we cannot accurately identify the outliers in the data.