Answer:

Step-by-step explanation:

I hope this helps, and as always, I am joyous to assist anyone at any time.
Answer:
1.3 repeating
Step-by-step explanation:
Answer:
We are confident that the true proportion of people satisfied with the quality of education the students receive is between (0.3995, 0.4564), since the lower value for this confidence level is higher than 0.38 we have enough evidence to conclude that the parents' attitudes toward the quality of education have changed.
Step-by-step explanation:
For this case we are interesting in the parameter of the true proportion of people satisfied with the quality of education the students receive
The confidence level is given 95%, the significance level would be given by
and
. And the critical values are:
The estimated proportion of people satisfied with the quality of education the students receive is given by:

The confidence interval for the proportion if interest is given by the following formula:
And replacing the info given we got:
We are confident that the true proportion of people satisfied with the quality of education the students receive is between (0.3995, 0.4564), since the lower value for this confidence level is higher than 0.38 we have enough evidence to conclude that the parents' attitudes toward the quality of education have changed.
Answer:
C) a positive correlation
Step-by-step explanation:
<em>More people ⇒ Longer time</em> is a positive correlation between those variables. However, <em>longer time</em> is not the desired outcome.
Rather, <em>shorter time</em> is the desired outcome. The correlation between <em>more people</em> and <em>shorter time</em> is negative. In order to compute that correlation numerically, one would have to define a function that would give a numerical value for "shorter time" that would model the goodness of outcome as time gets shorter.
No. The sample size is too small to be reliable. If there were many bags of 500 candies that consistently showed a larger-than-marketed amount of green candy, that will be better proof.