Answer:
The 95% confidence interval the average maximum power is (596.0 to 644.0)
Step-by-step explanation:
Average maximum of the sample = x = 620 HP
Standard Deviation = s = 45 HP
Sample size = n = 16
We have to calculate the 95% confidence interval. The value of Population standard deviation is unknown, and value of sample standard deviation is known. Therefore, we will use one sample t-test to build the confidence interval.
Degrees of freedom = df = n - 1 = 15
Critical t-value associated with 95% confidence interval and 15 degrees of freedom, as seen from t-table =
= 2.131
The formula to calculate the confidence interval is:

We have all the required values. Substituting them in the above expression, we get:

Thus, the 95% confidence interval the average maximum power is (596.0 to 644.0)
Answer: 5/12
Step-by-step explanation:
because the denominators are not the same you have to multiply to get a common base and then you can subtract from there to see how much he has left.
Given that the decay rate of the uranium is given to be 57%, this means that on the second day only 43% of the Uranium-233 will be left. The equation therefore, that will allow us to answer the question is that,
A(t) = A(0)(1 - r)^n
where A(t) is the amount after n days, A(0) is the original amount, r is the decimal equivalent of the rate and n is the number of days. Substituting the known values,
A(t) = (3,820 pounds)*(1-0.57)^15
A(t) = 0.0121 pounds
This is unfortunately not found in the choices.
For a hyperbola

where

the directrix is the line

and the focus is at (0, c).
Here, we have c = 5, a² = 9, so b² = 5² - 9 = 16.
a = √9 = 3
b = √16 = 4
Your hyperbola's constants are ...
a = 3
b = 4
______
Please note that the equation of a hyperbola has a negative sign for one of the terms. The equation given in your problem statement is that of an ellipse.
Answer:
<em>A: For each increase in the number of procrastination days by 1, the predicted grade decreases by 3.64 points.</em>
Step-by-step explanation:
<u>The slope of a Regression Line</u>
A straight line can be represented in the slope-intercept form:
y = mx + b
Where m is the slope and b is the y-intercept.
The slope describes how fast and in what direction the graph goes when x changes values.
If m is positive, increments in x imply increments in y.
If m is negative, increments in x imply decrements in y.
The regression line is:
ŷ = –3.64x + 96.5
Where:
x = the number of procrastination days
ŷ = the predicted grade
We can say the slope is m=-3.64. This means that:
A: For each increase in the number of procrastination days by 1, the predicted grade decreases by 3.64 points.