The x-axis represents the temperature degrees Celsius and the y-axis the feet above/below sea level.
What type of data is represented in this scatterplot? (Choose 3)
(3 points)
Responses
Non Linear Relationship
Non Linear Relationship
Bivariate
Bivariate
Decreasing
Decreasing
Increasing
Increasing
Univariate
Univariate
Linear Relationship
Bivariate, Non Linear Relationship, and Linear Relationship
The type of data represented in this scatterplot is:
1. Bivariate: The scatterplot shows the relationship between two variables - temperature degrees Celsius (x-axis) and feet above/below sea level (y-axis).
2. Non-linear relationship: The points in the scatterplot do not form a straight line, indicating a non-linear relationship between the variables.
3. Univariate: Although the scatterplot displays two variables, each variable is represented separately on the x-axis and y-axis, making it univariate.
To determine the type of data represented in this scatterplot, we need to analyze the characteristics of the data displayed on the x-axis and y-axis.
The given information states that the x-axis represents temperature degrees Celsius and the y-axis represents feet above/below sea level.
1. Bivariate: This term describes data that involves two variables, which are temperature (x-axis) and feet above/below sea level (y-axis). Since the scatterplot shows both of these variables, it can be considered bivariate.
2. Nonlinear Relationship: A nonlinear relationship exists when the relationship between variables cannot be represented by a straight line. Without further information, we cannot determine whether the data in the scatterplot shows a nonlinear relationship or not. Therefore, we cannot conclude this point based on the given information.
3. Univariate: Univariate refers to data that involves only one variable. However, since the scatterplot shows two variables, temperature and sea level, it cannot be classified as univariate.
Therefore, the three types of data represented in this scatterplot are Bivariate, Nonlinear Relationship (potentially), and Univariate (not applicable).