D is true hope this helps
Answer:
The value is 
The correct option is a
Step-by-step explanation:
From the question we are told that
The margin of error is E = 0.05
From the question we are told the confidence level is 95% , hence the level of significance is

=> 
Generally from the normal distribution table the critical value of is

Generally since the sample proportion is not given we will assume it to be

Generally the sample size is mathematically represented as
![n = [\frac{Z_{\frac{\alpha }{2} }}{E} ]^2 * \^ p (1 - \^ p )](https://tex.z-dn.net/?f=n%20%3D%20%5B%5Cfrac%7BZ_%7B%5Cfrac%7B%5Calpha%20%7D%7B2%7D%20%7D%7D%7BE%7D%20%5D%5E2%20%2A%20%5C%5E%20p%20%281%20-%20%5C%5E%20p%20%29%20)
=> ![n = [\frac{ 1.96 }{0.05} ]^2 *0.5 (1 - 0.5)](https://tex.z-dn.net/?f=n%20%3D%20%5B%5Cfrac%7B%201.96%20%7D%7B0.05%7D%20%5D%5E2%20%2A0.5%20%281%20-%200.5%29%20)
=> 
Generally the margin of error is mathematically represented as

Generally if the level of confidence increases, the critical value of
increase and from the equation for margin of error we see the the critical value varies directly with the margin of error , hence the margin of error will increase also
So If the confidence level is increased, then the sample size would need to increase because a higher level of confidence increases the margin of error.
It is statistical because there can be a variety of answers.
Using Visual inspection, the model which fits the data in the distribution better is the power function.
The power and linear functions can of the data can both be modeled using technology,
<u>Using Technology</u> :
The power function in the form
which models the data is 
The linear function in the form
which models the data is 
- Where A = intercept and B = slope
- From the model, correlation coefficient given by the power and linear models are 0.999 and 0.986 respectively.
- Hence, the power model is a better fit for the data than the linear model.
Therefore, Inspecting the models visually, the power function fits the data better as the points on the curve are closer to the regression line than on the linear model.
Learn more :brainly.com/question/18405415