Rearrange the equation as
cos(x) - √(1 - 3 cos²x) = 0
cos(x) = √(1 - 3 cos²x)
Note that both sides have to be positive, since the square root function is non-negative. If we end up with any solutions that make cos(x) < 0, we must throw them out.
Take the square of both sides.
(cos(x))² = (√(1 - 3 cos²(x))²
cos²(x) = 1 - 3 cos²(x)
4 cos²(x) = 1
cos²(x) = 1/4
cos(x) = ± √(1/4)
cos(x) = ± 1/2
We throw out the negative case and we're left with
cos(x) = 1/2
This has general solution
x = arccos(1/2) + 360° n or x = -arccos(1/2) + 360° n
(where n is any integer)
x = 60° + 360° n or x = -60° + 360° n
Now just pick out the solutions that fall in the interval 0° ≤ x < 360°.
• From the first solution set, we have x = 60° when n = 0.
• From the second set, we have x = 300° when n = 1.
So the answer is D.
If he bought the bike for $400 and lost 35% of his profit, you would divide 35 by 100. Next, you would multiply that number (0.35) by 400. When you do that, you get an answer of $140. In conclusion, if he bought the bike for $400 and sold it at a loss of 35%, he would lose $140 from that $400.
Additionally, if you wanted to know what exactly he sold it for, you would simply subtract 140 from 400. Which would be $260.
So, he bought the bike for $400, but when he resold it, he lost $140 of that pay. Basically, he resold the bike for $260.
I hope this helps! :) Let me know if you need help with anything else!
Answer:
a. The null hypothesis for this test is that the observed distribution is the same as uniform distribution
b. The degrees of freedom do you have for this test is 4
c. The calculated value of the test statistic is 9.250
Step-by-step explanation:
a. According to the given data we can conclude that the null hypothesis for this test is that the observed distribution is the same as uniform distribution.
b. In order to calculate the degrees of freedom do you have for this test we would have to make the following calculation:
degrees of freedom=k-1
degrees of freedom=5-1
degrees of freedom=4
c. In order to calculate the value of the test statistic first we have to calculate the frecuency expected as follows:
expected frecuency=total observed frecuency/total number of category
expected frecuency=1,000/5
expected frecuency=200
Hence, to calculate the value of the test statistic we have to calculate the following formula:
x∧2=∑(fo-fe)∧2/fe
=(185-200)∧2/200+(230-200)∧2/200+(215-200)∧2/200+(180-200)∧2+(190-200)∧2
=9.250
The calculated value of the test statistic is 9.250
