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murzikaleks [220]
3 years ago
8

While humans try to make rational and logical decisions, we are prevented from doing so by our cognitive limitations that limit

the quality and quantity of information available to us. This limitation is called:________. a. cognitive load b. heuristics c. overconfidence d. bounded rationality
Social Studies
1 answer:
sashaice [31]3 years ago
5 0

Answer:

bounded rationality

Explanation:

When decisions are constrained by time and costs, or when information available is partly accessible or incomplete, then bounded rationality limits our decision making. Even in conditions when we would think that we are acting on behalf of reason, there will be always some constraints that prevent us from being rational.

The decision makes that work in small and big organizations are aware of this and therefore they try to take into account the bounded rationality factors.

In this sense, managers will always pursue to play the more rational approach while taking decisions, and the use of computers and having the complete picture as well as the most information will somehow lessen the effect of bounded rationality, and despite it, a decision will always be human even if its aided with data served by a computer, as compared to a complete environment where only machines would operate in a cold-hearted and fully rational world.

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Answer:

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Explanation:

1.

Co-variance= Cov(x,y)= sum[(x-xbar)(y-ybar)]/n

xbar=sumx/n=32/5=6.4

ybar=sumy/n=35/5=7

x 7 8 5 3 9

x-xbar 0.6 1.6 -1.4 -3.4 2.6

y 7 5 9 7 7

y-ybar 0 -2 2 0 0

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Cov(x,y)= sum[(x-xbar)(y-ybar)]/n=-6/5=-1.2

Cov(x,y)=-1.2

2.

correlation coefficient=r

r=\frac{sum(x-xbar)(y-ybar)}{\sqrt{sum(x-xbar)^2sum(y-ybar)^2} }

x 7 8 5 3 9

x-xbar 0.6 1.6 -1.4 -3.4 2.6

y 7 5 9 7 7

y-ybar 0 -2 2 0 0

(x-xbar)(y-ybar) 0 -3.2 -2.8 0 0

(x-xbar)² 0.36 2.56 1.96 11.56 6.76

(y-ybar)²  0 4 4 0 0

r=\frac{-6}{\sqrt{23.2(8)} }

r=-0.4404

3. Since the value of correlation coefficient is negative and less than 0.5 , so, we can say that there is weak negative relationship between x and y.

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