The researchers were most concerned about External events.
<h3><u>Explanation: </u></h3>
Quasi-experimental designs are different from true experimental designs. They resemble the experimental research but it is not the real one. There are various types of quasi-experiment design, one of the important designs is the pretest and posttest design which is discussed in the above scenario.
The most likely reason for the experimental effect is based on selection bias. Self-fulfilling Prophecy & Instrument Decay might be the potential cause of the internal validity that is linked with the experiment done by the staff.
Sounds like a horror city with nothing normal happening, everyone having a tough time with imagination being normal,
For a more useful answer it looks like a town full of uncivilized people that understand a more violent interaction with the world around them and a poor education system.
Answer:
Measurements of performance.
Explanation:
In many dictionaries, the metric is linked to metrification and is identified as a set of rules for verse measurement. However, in the area that interests you, it shows the result of efforts in numbers, especially those related to marketing. Another interesting point is that, besides the results, the metric also quantifies behaviors and trends, which is very important for the right decision making. In addition to these concepts, we must consider what concept metrics assume in a supply chain, in which case the metric takes forms of measurements of performance.
The correct answer is B.
<u>Therefore the appropiate null and alternative hypothesis are the following:</u>
. H 0 : p 1 = p 2
H 1 : p 1 ≠ p 2
The aim of the test would be to conclude whether H0 should be rejected or not at a 10% significance level.
<u>In this case a billateral significance test needs to be conducted,</u> as such a test consists on testing the equality of the test value with a given value. In this case the H0 would be rejected if the test value is significanly different, both in the case that it is superior or inferior.
On the contrary, an unilateral significance test would have been conducted if aiming to check whether a value is superior or equal to the test value (left unilateral) or inferior or equal to this value (right unilateral).
Then, the result of the test is the one stated: rejecting H0 at the 10% significance level.
