Answer: The rate of change in the value of the guitar is modeled by 0.95, which represents a decrease of 5% per year.
Step-by-step explanation:
Hi, to answer this question we have to apply an exponential decay function:
A = P (1 - r) t
Where:
p = original price
r = decrease rate (decimal form)
t= years
A = price after t years
Replacing with the values given:
A(t)=145(0.95)t.
Where
0.95 = 1-r
0.95-1 = r
-0.05 =-r
0.05 =r
Converting to percentage form:
0.05 x 100 = 5%
Feel free to ask for more if needed or if you did not understand something.
One side let it be 5 1/2, so 5 units and a half of one and then the other side make it 7 units wide.
Then connect the two end points to make a triangle, the area would be 19 1/4
Now you would need two.. just do the exact same thing but flip it so it doesn’t look alike
Remember you said the scale shows you 10% heavier.
So that's an increase of 10%
So value = 10% + 100% = 110%
So scale would show 110% of 82
110% of 82
= (110/100) * 82
= 1.1 * 82
= 90.2
OR
We can simply find 10% of 82 and add it to the original 82.
10% of 82
(10/100) * 82
0.1 * 82 = 8.2
8.2 + 82 = 90.2 Same answer as before.
So scale shows 90.2 kg.
To get the greatest possible quotient, you need the biggest possible
dividend and the smallest possible divisor.
96,432 divided by 225 = 428.5666... <== greatest possible
23,469 divided by 522 = 44.9597... <== smallest possible
Answer:
Using a formula, the standard error is: 0.052
Using bootstrap, the standard error is: 0.050
Comparison:
The calculated standard error using the formula is greater than the standard error using bootstrap
Step-by-step explanation:
Given
Sample A Sample B
Solving (a): Standard error using formula
First, calculate the proportion of A
The proportion of B
The standard error is:
Solving (a): Standard error using bootstrapping.
Following the below steps.
- Open Statkey
- Under Randomization Hypothesis Tests, select Test for Difference in Proportions
- Click on Edit data, enter the appropriate data
- Click on ok to generate samples
- Click on Generate 1000 samples ---- <em>see attachment for the generated data</em>
From the randomization sample, we have:
Sample A Sample B
So, we have:
