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 −0.91 is calculated. What would this imply about the football team winning at home?

The scatter plot would closely resemble a straight line with a negative slope. The data has a strong, negative correlation, and a causal relationship exists between the team playing at home and winning.

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

The scatter plot would not be represented by a line of best fit with a negative 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 negative slope. The data has a strong, negative correlation, and a causal relationship exists between the team playing at home and winning.

Step-by-step explanation:

In a scatter plot, the values of two variables are shown, on the x-axis and the y-axis.

The correlation coefficient is a number calculated from the data in the plot, that represents how much the two variables are related to each other.

The value of the correlation coefficient is between -1 and 1.

In particular, we have:

- If the coefficient is positive and near to 1, there is a strong positive correlation: it means that as the independent variable increases, the dependent variable increases as well

- If the coefficient is close to zero, there is no correlation: the two variables are independent from each other

- If the coefficient is negative and near to -1, there is a strong negative correlation: it means that as the independent variable increases, the dependent variable decreases

In this problem, the correlation coefficient is -0.91, so we have strong negative correlation. Therefore, the correct answer is

The scatter plot would closely resemble a straight line with a negative slope. The data has a strong, negative correlation, and a causal relationship exists between the team playing at home and winning.

so a parallelogram is just like a square base times height. multiply 40 and 39 to get 1560 inches.

a triangle is base times height divided by two. so multiply 7.9 and 5 and then divide it by 2 to get 19.75inches.

the kite can be split into two separate triangles and added together to get the total area. 30 x 4 /2 which equals 60. make sure to double it for the two triangles making 120.