The number of wins for a high school football team is measured for the season. When the team plays at home, it is generally believed that they will win. Comparing the location of the game and the number of wins, a correlation coefficient of 0.891 is calculated. What would this imply about the football team winning at home? The scatter plot would closely resemble a straight line with a positive slope. The data has a strong, positive correlation, but causation cannot be determined.
The scatter plot would closely resemble a straight line with a positive slope. The data has a strong, positive correlation, and a causal relationship exists between the team playing at home and winning.
The scatter plot would not be represented by a line of best fit with a positive slope. There is a weak correlation between the football team playing at home and winning.
There is no causation and almost no correlation between the football team playing at home and winning.

The scatter plot would closely resemble a straight line with a positive slope. The data has a strong, positive correlation, but causation cannot be determined.

Step-by-step explanation:

As we know that the correlation coefficient(r) tells about the direction and the strength of the correlation but nothing about the causation.

So, if we have only correlation coefficient(r) , then causation cannot be determined.

Given , Comparing the location of the game and the number of wins, a correlation coefficient of 0.891 is calculated.

Since , correlation coefficient is positive , it means it shows a positive coreelation.

Also, 0.891 lies between 0.7 and 1 , it means it indicates a strong correlation between the location of the game and the number of wins.

Hence, the correct summarized statement about the football team winning at home would be :

"The scatter plot would closely resemble a straight line with a positive slope. The data has a strong, positive correlation, but causation cannot be determined."

The scatter plot would closely resemble a straight line with a positive slope. The data has a strong, positive correlation, but causation cannot be determined.

The answer is A

Step-by-step explanation:

y=mx+b

step-by-step explanation:

m is slope, b is y-intercept

idk

step-by-step explanation:

i don't know