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{}, "type": "numberentry", "maxValue": "emv[2]", "minValue": "emv[2]", "showCorrectAnswer": true, "marks": 1}], "type": "gapfill", "prompt": "\n

Calculate the Expected Monetary Value (EMV) for each option:

\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
 EMV
{Cat[0]}[[0]]
{Cat[1]}[[1]]
{Cat[2]}[[2]]
\n ", "showCorrectAnswer": true, "marks": 0}, {"displayType": "radiogroup", "choices": ["{Cat[0]}", "{Cat[1]}", "{Cat[2]}"], "matrix": "mm", "prompt": "\n

Hence determine the optimal course of action:

\n

 

\n ", "distractors": ["", "", ""], "shuffleChoices": false, "scripts": {}, "maxMarks": 0, "type": "1_n_2", "minMarks": 0, "showCorrectAnswer": true, "displayColumns": 0, "marks": 0}], "statement": "\n

{Something} {hasdonethis} {decision}

\n

A. {Cat[0]}

\n

B. {Cat[1]}

\n

C. {Cat[2]}

\n

{info} has the following probabilities associated to the following {outcomes} for the {product}:

\n

{Att[1]}, {Att[2]} or {Att[3]}.

\n

{table([['<strong>Probability</strong>']+p],Att)}

\n

The next table shows {expectedreturn} for each option against these {outcomes}:

\n

{table(b,Att)}

\n ", "tags": ["checked2015", "MAS1403"], "rulesets": {}, "preamble": {"css": "", "js": ""}, "type": "question", "metadata": {"notes": "\n \t\t

29/12/2012:

\n \t\t

Added tag sc (as configurable to other applications).

\n \t\t

Also added tag table.

\n \t\t

The tables need sorting out. OK, but need better table functions.

\n \t\t

Checked calculations, OK.

\n \t\t

 

\n \t\t", "licence": "Creative Commons Attribution 4.0 International", "description": "

Given data on probabilities of three levels of success of three options and projections of the profits that the options will accrue depending on the level of success, find the expected monetary value (EMV) for each option and choose the one with the greatest EMV.

"}, "advice": "\n

The Expected Monetary Value for the first option:  {Cat[0]} is given in four steps (all numbers below are in {units}):

\n

1.  Multiplying the probability $\\var{p1}$  of a {Att[1]} outcome by the expected profit $\\var{a[0][0]}$,  gives:

\n

expected profit = $\\var{p1}\\times \\var{a[0][0]}=  \\var{p1*a[0][0]}$ 

\n

 

\n

2.  Multiplying the probability $\\var{p2}$  of a {Att[2]} outcome  by the expected profit,  $\\var{a[0][1]}$ gives:

\n

 expected profit =  $\\var{p2}\\times \\var{a[0][1]}=  \\var{p2*a[0][1]}$  

\n

 

\n

3.   Multiplying the probability $\\var{p3}$  of a {Att[3]} outcome  by the expected profit,  $\\var{a[0][2]}$ gives:

\n

 expected profit =  $\\var{p3}\\times \\var{a[0][2]}=  \\var{p3*a[0][2]}$ 

\n

4. Finally add these three together to get the Expected Monetary Value  for the option {Cat[0]} :

\n

$\\var{p1*a[0][0]}+\\var{p2*a[0][1]}-\\var{abs(p3*a[0][2])}=\\var{emv[0]}$

\n

 

\n

You calculate in the same way for the other options - the next table gives the Expected Monetary Value for all three::

\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
 EMV
{Cat[0]}{emv[0]}
{Cat[1]}{emv[1]}
{Cat[2]}{emv[2]}
\n

The optimal course of action is take to be that which has the highest Expected Monetary Value (EMV) and this is seen to be :

\n

{Correct} with EMV  $\\var{maxemv}$.

\n

 

\n

 

\n

 

\n

 

\n

 

\n ", "contributors": [{"name": "Newcastle University Mathematics and Statistics", "profile_url": "https://numbas.mathcentre.ac.uk/accounts/profile/697/"}]}]}], "contributors": [{"name": "Newcastle University Mathematics and Statistics", "profile_url": "https://numbas.mathcentre.ac.uk/accounts/profile/697/"}]}