There are around 8 booklets in the lab because 6÷2 is 3 and 25÷3=8.3333333333333333333
Answer:
μ = 0.169
ME = 0.051
Step-by-step explanation:
The confidence interval is:
CI = μ ± ME
So the mean is the middle of the confidence interval, and the margin of error is half the difference.
μ = (0.118 + 0.220) / 2 = 0.169
ME = (0.220 − 0.118) / 2 = 0.051
Answer:
d) Squared differences between actual and predicted Y values.
Step-by-step explanation:
Regression is called "least squares" regression line. The line takes the form = a + b*X where a and b are both constants. Value of Y and X is specific value of independent variable.Such formula could be used to generate values of given value X.
For example,
suppose a = 10 and b = 7. If X is 10, then predicted value for Y of 45 (from 10 + 5*7). It turns out that with any two variables X and Y. In other words, there exists one formula that will produce the best, or most accurate predictions for Y given X. Any other equation would not fit as well and would predict Y with more error. That equation is called the least squares regression equation.
It minimize the squared difference between actual and predicted value.
Answer:
Hardy has 470 more tennis balls than Kerns.
Step-by-step explanation:
Given that:
Total number of tennis balls = 940
Let,
x represents the number of tennis balls Hardy has.
y represents the number of tennis balls Kerns has.
According to given statement,
x+y=940 Eqn 1
x = 3y Eqn 2
Putting x = 3y in Eqn 1
3y+y=940
4y=940
Dividing both sides by 4

Putting y=235 in Eqn 2
x = 3(235)
x = 705
Difference = Hardy's tennis balls - Kerns' tennis balls
Difference = 705 - 235 = 470
Hence,
Hardy has 470 more tennis balls than Kerns.
Answer:
The coordinates for X are (4, 8).
Step-by-step explanation: