Flower bed A:
circumference= 2 x pi x r= 2x pi x10/2
=10pi feet
Area= pi x r^2=25pi square feet
Flower bed B:
circumference=12 pi feet
Area=36 pi square feet
There is a positive, linear relationship between the correct and guessed calories. The guessed calories for 5 oz. of spaghetti with tomato sauce and the cream-filled snack cake are unusually high and do not appear to fit the overall pattern displayed for the other foods. The correlation is r = 0.825 . This agrees with the positive association observed in the plot; it is not closer to 1 because of the unusual guessed calories for spaghetti and cake. The fact that the guesses are all higher than the true calorie count does not influence the correlation. The correlation r would not change if every guess were 100 calories higher. The correlation r does not change if a constant is added to all values of a variable because the standardized values would be unchanged. The correlation without these two foods is r = 0.984 . The correlation is closer to 1 because the relationship is much stronger without these two foods.
Answer:
37.7
Step-by-step explanation:
Large circle = 
r² = 5² = 78.54
Medium circle = 3²= 28.27
Small circle = 2²= 12.57
78.54-28.27-12.57 = 37.7
The expression y = 660(0.902)ˣ represents a decay , the rate of decrease is 9.8% .
In the question ,
it is given that ,
the the exponential function is y = 660(0.902)ˣ
we need to determine that , the equation represents a growth or decay .
0.902 is the variable that will determine a growth or decay .
Since, 0.902 is less than 1 , so it represents a decay function .
To find the rate we subtract 0.902 from 1
= 1 - 0.902
= 0.098
= 9.8% decrease rate
Therefore , The expression y = 660(0.902)ˣ represents a decay , the rate of decrease is 9.8% .
The given question is incomplete , the complete question is
Identify if it's Growth or Decay , and determine the percentage rate of increase or decrease , the function is y = 660(0.902)ˣ ?
Learn more about Growth and Decay here
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There could be a strong correlation between the proximity of the holiday season and the number of people who buy in the shopping centers.
It is known that when there are vacations people tend to frequent shopping centers more often than when they are busy with work or school.
Therefore, the proximity in the holiday season is related to the increase in the number of people who buy in the shopping centers.
This means that there is a strong correlation between both variables, since when one increases the other also does. This type of correlation is called positive. When, on the contrary, the increase of one variable causes the decrease of another variable, it is said that there is a negative correlation.
There are several coefficients that measure the degree of correlation (strong or weak), adapted to the nature of the data. The best known is the 'r' coefficient of Pearson correlation
A correlation is strong when the change in a variable x produces a significant change in a variable 'y'. In this case, the correlation coefficient r approaches | 1 |.
When the correlation between two variables is weak, the change of one causes a very slight and difficult to perceive change in the other variable. In this case, the correlation coefficient approaches zero
