| CARVIEW |
- Courses
- Tutorials
- Practice
- Jobs
Exploring Bivariate Numerical Data
Scatter plots are a useful tool for determining how two sets of quantitative data are or are not connected with one another. Learn how to create a scatter plot and estimate the degree of connection between two data sets using linear regression.
Question 1
What does a scatter plot with a downward trend indicate about the relationship between two numerical variables?
The variables increase together
The variables decrease together
As one variable increases, the other decreases
There is no relationship between the variables
Question 2
What does a correlation coefficient close to -1 indicate?
A strong positive linear relationship
No linear relationship
A strong negative linear relationship
A perfect nonlinear relationship
Question 3
In the context of bivariate numerical data, what is the purpose of the line of best fit?
To divide the data into equal parts
To predict the value of one variable based on the value of another
To measure the spread of the data
To create categories within the data
Question 4
What is the impact of outliers on the correlation coefficient between two variables?
Outliers have no impact
Outliers can make the correlation coefficient appear stronger
Outliers can weaken or distort the true relationship
Outliers convert a non-linear relationship into a linear one
Question 5
Why is it important to consider the scale of measurement when analyzing bivariate numerical data?
Different scales can lead to misinterpretation of the relationship
The scale of measurement affects the calculation of the correlation coefficient
Changing the scale can turn a non-linear relationship into a linear one
Scale impacts the number of outliers in the data
There are 5 questions to complete.
