The formula we use for continuous compounding is
where P is the initial amount invested, r is the rate as a decimal, and t is time in years. Our P = 1300, our r = .042, and our t = 5.75 (9 months is 3/4 of a year, and 3/4 in a decimal is .75). Putting all that into our formula we have
. We have to multiply those 2 powers together and then raise euler's number to it, then multiply by 1300. Doing all of that, we get the amount at the end to be $1,655.10
Answer:
yes
Step-by-step explanation:
We can factor a -2 and an x^2 out of this using GCF.
<h3><u>-2x^2(x - 3) is what we're left with, and is the fully factored form.</u></h3>
Recall the double angle identity:
With 
measuring between 0º and 90º, we know 
. So from the Pythagorean identity, we get
Then
Answer:
Linear correlation exists
Step-by-step explanation:
Given the data :
X : | 2 4 5 6
Y : | 6 9 8 10
Using technology to fit the data and obtain the correlation Coefficient of the regression model,
The Correlation Coefficient, r is 0.886
To test if there exists a linear correlation :
Test statistic :
T = r / √(1 - r²) / (n - 2)
n = number of observations
T = 0.886 / √(1 - 0.886²) / (4 - 2)
T = 0.866 / 0.3535845
T = 2.449
Comparing Pvalue with α
If Pvalue < α ; Reject H0
Pvalue = 0.1143
α = 0.05
Pvalue > α ; We reject the null and conclude that linear correlation exists
