we can factor the whole thing:
(2sin(x) -1)(sin(x)+1) = 0.
Therefore, sin(x) = -1 and sin(x) = 1/2.
For the first one x = 3π/2 and the second is π/6 and 5π/6
So 3π/2, π/6 and 5π/6 are the solutions.
I do kind of have a problem with this because it doesn't mention if you should go over 360°. Otherwise, you have to add in an 2nπ into the equations like 3π/2 + 2nπ; 
but I don't know if that is necessary for you.
Answer:
Option A
The p-value is less than the significance level of 0.05 chosen and so we reject the null hypothesis H0 and can conclude that the proportion of the subjects who have the necessary qualities is less than 0.2.
Step-by-step explanation:
Normally, in hypothesis testing, the level of statistical significance is often expressed as the so-called p-value. We use p-values to make conclusions in significance testing. More specifically, we compare the p-value to a significance level "α" to make conclusions about our hypotheses.
If the p-value is lower than the significance level we chose, then we reject the null hypotheses H0 in favor of the alternative hypothesis Ha. However, if the p-value is greater than or equal to the significance level, then we fail to reject the null hypothesis H0
though this doesn't mean we accept H0 automatically.
Now, applying this to our question;
The p-value is 0.023 while the significance level is 0.05.
Thus,p-value is less than the significance level of 0.05 chosen and so we reject the null hypothesis H0 and can conclude that the proportion of the subjects who have the necessary qualities is less than 0.2.
The only option that is correct is option A.
Answer:
2. option D and 3. option A
Step-by-step explanation:
2. 7 + y = 30
<u>7 - 7</u> + y = <u>30 - 7</u>
y = 23
3. w - 32 = 55
w <u>-</u><u> </u><u>32</u><u> </u><u>+</u><u> </u><u>32</u> = <u>55</u><u> </u><u>-</u><u> </u><u>32</u>
w = 87
Basically the answers you choose are right. Hope this helps, thank you :) !!
The answer would be 2 to the 2nd power
Answer:
The difference between the sample statistic and population parameter is called sampling error.
Step-by-step explanation:
We are given the following in the question:
- A sample is a part of population, it is a subset of population.
- A sample statistic describes the sample. It is a characteristic of sample and different from the population.
- A parameter describes the population. It is characteristic of a population.
- A sample may not be able to represent the whole population and this may lead to error.
- Thus, sampling error is the difference between the sample statistic and population parameter.
- It arises when the sample is not able to describe the population.
The difference between the sample statistic and population parameter is called sampling error.
