Answer:
$5,490
Step-by-step explanation:
i = prt
i = ($61,000)(.03)(3)
5,490
Answer:
the answer is 4.8
Step-by-step explanation: i had this on a test and i got it right
Answer:
Step-by-step explanation:
Multiply each term of the first polynomial with the second polynomial. Then combine the like terms.
(3a<em>² + 5a - 2)* (5a² -3a + 4)</em>
<em> = 3a² *(5a² -3a + 4) + 5a*(5a² -3a + 4) - 2*(5a² -3a + 4)</em>
<em>=3a²*5a² - 3a*3a² + 4*3a² + 5a*5a² - 3a*5a + 4*5a + 5a²*(-2) - 3a*(-2) + 4*(-2)</em>
<em>=15a⁴ - 9a³ + 12a² + 25a³ - 15a² + 20a - 10a² + 6a - 8</em>
<em>= 15a⁴ </em><u><em>- 9a³ + 25a³</em></u><em> +</em><u><em> 12a² - 15a² - 10a²</em></u><em> +</em><u><em> 20a +6a </em></u><em>- 8</em>
<em>= 15a⁴ + 16a³ - 13a² +26a - 8</em>
Answer:
Bias for the estimator = -0.56
Mean Square Error for the estimator = 6.6311
Step-by-step explanation:
Given - A normally distributed random variable with mean 4.5 and standard deviation 7.6 is sampled to get two independent values, X1 and X2. The mean is estimated using the formula (3X1 + 4X2)/8.
To find - Determine the bias and the mean squared error for this estimator of the mean.
Proof -
Let us denote
X be a random variable such that X ~ N(mean = 4.5, SD = 7.6)
Now,
An estimate of mean, μ is suggested as

Now
Bias for the estimator = E(μ bar) - μ
= 
= 
= 
= 
= 
= 3.9375 - 4.5
= - 0.5625 ≈ -0.56
∴ we get
Bias for the estimator = -0.56
Now,
Mean Square Error for the estimator = E[(μ bar - μ)²]
= Var(μ bar) + [Bias(μ bar, μ)]²
= 
= 
= ![\frac{1}{64} ( [{3Var(X_{1}) + 4Var(X_{2})] }) + 0.3136](https://tex.z-dn.net/?f=%5Cfrac%7B1%7D%7B64%7D%20%28%20%5B%7B3Var%28X_%7B1%7D%29%20%2B%204Var%28X_%7B2%7D%29%5D%20%20%7D%29%20%2B%200.3136)
= ![\frac{1}{64} [{3(57.76) + 4(57.76)}] } + 0.3136](https://tex.z-dn.net/?f=%5Cfrac%7B1%7D%7B64%7D%20%5B%7B3%2857.76%29%20%2B%204%2857.76%29%7D%5D%20%20%7D%20%2B%200.3136)
= ![\frac{1}{64} [7(57.76)}] } + 0.3136](https://tex.z-dn.net/?f=%5Cfrac%7B1%7D%7B64%7D%20%5B7%2857.76%29%7D%5D%20%20%7D%20%2B%200.3136)
= ![\frac{1}{64} [404.32] } + 0.3136](https://tex.z-dn.net/?f=%5Cfrac%7B1%7D%7B64%7D%20%5B404.32%5D%20%20%7D%20%2B%200.3136)
= 
= 6.6311
∴ we get
Mean Square Error for the estimator = 6.6311