Independent variable is the predictor variable which is the height and dependent variable is the response variable which is weight in this scenario.
The square of correlation coefficient gives the coefficient of determination. It is denoted by R² (R squared).
We are given:
R = 0.75
So,
R² = 0.75²
R² = 0.5625
R² = 56.25 %
The coefficient of determination tells how much of the trend of dependent data can be explained by the independent data using the linear regression model. So in the given case, Height can explain 56.25% of the trend in the weight.
First row is 3 cookies for every $1, proportional, and Table to the right
Second row is 3 more cookies than donuts, non-proportional, and the Table on the left
70-80=10
hope this help the
68 rounded to the nearest tenth equals 70
and 76 rounded to the nearest tenth equals 80
so if you subtract 80-70=10 Tito increased the percent up to 10 dollars
Answer:5.435
Step-by-step explanation: In math, the average value in a set of numbers is the middle value, calculated by dividing the total of all the values by the number of values. To find this answer, we need to find the average of a set of data, we add up all the values and divide this total by the numbers of values. So if you add 4.40, 3.12, 8.00 and 6.22 together, we get 21.74. There are four values (4.40, 3.12, 8.00 and 6.22) so we divide the amount of values there are, which would be four. 21.47/4 would then get you 5.435
Answer:
3.48%
Step-by-step explanation:
Probability = Area of hole / Area of board
= 3.14 x 2 x 2 / 12 x 30
= 12.56 / 360
= 0.0348
= 3.48%
