<Q and <R are complementary angles. If m<Q = (31 - 3x)° and m<R = (19x - 5)°, find m<R
2 answers:
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Answer:
.
Step-by-step explanation:
We are given and
are zeros of the polynomial
.
We want to find the value of if
.
Lets use veita's formula.
By that formula we have the following equations:
(-b/a where the quadratic is ax^2+bx+c)
(c/a)
Let's simplify those equations:
If and
, then
.
Let's solve this for k:
Subtract 6 on both sides:
Find a common denominator:
Simplify:
.
Kindly find complete question attached below
Answer:
Kindly check explanation
Step-by-step explanation:
Given a normal distribution with ;
Mean = 36
Standard deviation = 4
According to the empirical rule :
68% of the distribution is within 1 standard deviation of the mean ;
That is ; mean ± 1(standard deviation)
68% of subjects :
36 ± 1(4) :
36 - 4 or 36 + 4
Between 32 and 40
2.)
95% of the distribution is within 2 standard deviations of the mean ;
That is ; mean ± 2(standard deviation)
95% of subjects :
36 ± 2(4) :
36 - 8 or 36 + 8
Between 28 and 44
3.)
99% is about 3 standard deviations of the mean :
That is ; mean ± 3(standard deviation)
99% of subjects :
36 ± 3(4) :
36 - 12 or 36 + 12
Between 24 and 48
Answer:
1. Mean square B= 5.32
2. Mean square E= 16.067
3. F= 0.33
4. p-value: 0.28
Step-by-step explanation:
Hello!
You have the information of 3 groups of people.
Group 1
n₁= 20
X[bar]₁= 3.2
S₁²= 14.3
Group 2
n₂= 20
X[bar]₂= 4.2
S₂²= 17.2
Group 3
n₃= 20
X[bar]₃= 7.6
S₃²= 16.7
1. To manually calculate the mean square between the groups you have to calculate the sum of square between conditions and divide it by the degrees of freedom.
Df B= k-1 = 3-1= 2
Sum Square B is:
∑ni(Ÿi - Ÿ..)²
Ÿi= sample mean of sample i ∀ i= 1,2,3
Ÿ..= general mean is the mean that results of all the groups together.
General mean:
Ÿ..= (Ÿ₁ + Ÿ₂ + Ÿ₃)/ 3 = (3.2+4.2+7.6)/3 = 5
Sum Square B (Ÿ₁ - Ÿ..)² + (Ÿ₂ - Ÿ..)² + (Ÿ₃ - Ÿ..)²= (3.2 - 5)² + (4.2 - 5)² + (7.6 - 5)²= 10.64
Mean square B= Sum Square B/Df B= 10.64/2= 5.32
2. The mean square error (MSE) is the estimation of the variance error (σ →
), you have to use the following formula:
Se²=<u> (n₁-1)S₁² + -(n₂-1)S₂² + (n₃-1)S₃²</u>
n₁+n₂+n₃-k
Se²=<u> 19*14.3 + 19*17.2 + 19*16.7 </u>= <u> 915.8 </u> = 16.067
20+20+20-3 57
DfE= N-k = 60-3= 57
3. To calculate the value of the statistic you have to divide the MSB by MSE
4. P(F ≤ F) = P(F
≤ 0.33) = 0.28
I hope you have a SUPER day!