Which of the following pairs of variables is likely to have a negative correlation? Check all that apply.
Years of education and salary
The number of miles run and the number of calories burned
A person's height and their favorite color
The speed of a car and the time to its destination
The square footage of a home and its price
More education should get you a better paying job
The more you exercise, the more calories you should burn
A person's height and favorite color has no relationship
The faster you drive, the shorter the time to get there
The bigger the house, the higher the price.
A negative correlation as one goes up the other goes down.
Can you find the one example that does that?
c?
I don't know if there are others
sorry d
d is correct.
I'm glad you asked! Let's see which pairs of variables are likely to have a negative correlation.
Years of education and salary: It is reasonable to expect a positive correlation here, as higher levels of education typically lead to higher salaries.
The number of miles run and the number of calories burned: This is likely to have a positive correlation, as more miles run usually result in more calories burned.
A person's height and their favorite color: These variables are unrelated and are not likely to have any correlation, negative or positive.
The speed of a car and the time to its destination: Here, we can expect a negative correlation. As the speed of the car increases, the time taken to reach the destination generally decreases.
The square footage of a home and its price: This pair is likely to have a positive correlation, as larger homes tend to have higher prices.
So, the pairs that are likely to have a negative correlation are:
- The speed of a car and the time to its destination
I hope that brings a smile to your face!
To determine which pairs of variables are likely to have a negative correlation, we need to understand what negative correlation means. Negative correlation refers to a relationship between two variables in which they move in opposite directions. In other words, when one variable increases, the other variable tends to decrease.
Let's analyze each pair of variables:
1. Years of education and salary: These variables are likely to have a positive correlation. As the number of years of education increases, individuals tend to acquire more skills and knowledge, which can lead to higher-paying jobs. Therefore, this pair does not have a negative correlation.
2. The number of miles run and the number of calories burned: These variables are likely to have a positive correlation. As the number of miles run increases, the amount of calories burned also tends to increase. Therefore, this pair does not have a negative correlation.
3. A person's height and their favorite color: These variables are unlikely to have any correlation, either positive or negative. Height and favorite color are unrelated attributes, so they do not exhibit any correlation.
4. The speed of a car and the time to its destination: These variables are likely to have a negative correlation. As the speed of the car increases, the time taken to reach the destination tends to decrease. Therefore, this pair is likely to have a negative correlation.
5. The square footage of a home and its price: These variables are also likely to have a positive correlation. In general, larger homes tend to have higher prices, and smaller homes tend to have lower prices. Therefore, this pair does not have a negative correlation.
Based on this analysis, the pair "The speed of a car and the time to its destination" is likely to have a negative correlation.