Answer:
Step-by-step explanation:
Step1: find the interval of roots. Consider -3 and -2


Hence, the root must be on [-3,-2]
Step2: consider the middle point -2.5

Then, the root must be on [-3, -2.5]
Step 3: Repeat step 2 by finding the value of f at the middle point -2.75

Step 3: Repeat step 2 by finding the value of f at the middle point of the interval [-2.75,-2.5] which is -2.625

Step4: Repeat step 2 on [-2.75, -2.625]
Repeat step 2 until you got the root which is -2.701
The square it’s self without the side triangles is 132ft^2 and the triangles them selves are 18ft^2.
Since there are 2 triangles both combined would be a total of 36ft^2
The total area of the square is 132ft^2
Total area of one triangle is 18ft^2
Total area is 168ft^2
Side length dimensions:
Square without sides: 12x11 ft
Each triangle: 1/2 12x3
Answer:
Step-by-step explanation:
First Group like terms:

Add similar elements:




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).