Answer:
Option A) One tailed test is a hypothesis test in which rejection region is in one tail of the sampling distribution
Step-by-step explanation:
One Tailed Test:
- A one tailed test is a test that have hypothesis of the form
- A one-tailed test is a hypothesis test that help us to test whether the sample mean would be higher or lower than the population mean.
- Rejection region is the area for which the null hypothesis is rejected.
- If we perform right tailed hypothesis that is the upper tail hypothesis then the rejection region lies in the right tail after the critical value.
- If we perform left tailed hypothesis that is the lower tail hypothesis then the rejection region lies in the left tail after the critical value.
Thus, for one tailed test,
Option A) One tailed test is a hypothesis test in which rejection region is in one tail of the sampling distribution
Answer:
The position of the three cities do not form a right-triangle.
Step-by-step explanation:
There are three cities on a map (say A, B, and C).
Now, the distances between them are 45 miles, 56 miles, and 72 miles.
i.e. AB= 45 miles, BC= 56 miles and CA =72 miles.
If the three cities A, B, C form a right-angled triangle on the map, then applying Pythagoras Theorem AB² +BC² =AC²
or, AC= √(AB² +BC²) must be satisfied.
Now, right-hand side of the above equation =√(45²+56²) =71.84 ≠ 72 (AC)
Hence, Right-hand side ≠ Left-hand side.
Therefore, the positions of the three cities do not form a right triangle. (Answer)
Answer:
Null hypothesis: 
Alternative hypothesis: 
A type of error II for this case would be FAIL to reject the null hypothesis that the population proportion is equal to 0.0147 when actually the alternative hypothesis is true (the true proportion is different from 0.0147).
Step-by-step explanation:
Previous concepts
A hypothesis is defined as "a speculation or theory based on insufficient evidence that lends itself to further testing and experimentation. With further testing, a hypothesis can usually be proven true or false".
The null hypothesis is defined as "a hypothesis that says there is no statistical significance between the two variables in the hypothesis. It is the hypothesis that the researcher is trying to disprove".
The alternative hypothesis is "just the inverse, or opposite, of the null hypothesis. It is the hypothesis that researcher is trying to prove".
Type I error, also known as a “false positive” is the error of rejecting a null hypothesis when it is actually true. Can be interpreted as the error of no reject an alternative hypothesis when the results can be attributed not to the reality.
Type II error, also known as a "false negative" is the error of not rejecting a null hypothesis when the alternative hypothesis is the true. Can be interpreted as the error of failing to accept an alternative hypothesis when we don't have enough statistical power.
Solution to the problem
On this case we want to test if the proportion of children diagnosed with Autism Spectrum Disorder (ASD) is different from 0.0147, so the system of hypothesis would be:
Null hypothesis:
Alternative hypothesis:
A type of error II for this case would be FAIL to reject the null hypothesis that the population proportion is equal to 0.0147 when actually the alternative hypothesis is true (the true proportion is different from 0.0147).
Answer:
48°
Step-by-step explanation:
..,.............,...........
CDB = ABD( given)
CBD= ADB( given)
Now,
CBD+CDB+C = 180°
70°+62°+ C = 180°
C= 180°-132°
C= 48°
