The answer to this question is "VALENCE" such as when the HR Manager told Jim that the company pays the total health insurance costs for a family of four and as a single man, this benefit did not seem especially important and significant to him right now. Here, then Jim is a low on the valence element of the expectancy theory.
Answer:
Option B $17,285 is correct the answer.
Explanation:
<u>Computation Table </u>
<u>Particular Amount</u>
Ending balance $18,600
Add: Deposit in transit $1,550
Less: Outstanding $2,100
Add: NSF check $800
Add: Bank charges $35
<u>Less</u><u>: EFT $1,600
</u>
<u>Cash balance $17285
</u>
<u></u>
By definition, empirical probability is equal to C. Number of successful trials/Total number of trials.
<h3>What is an empirical probability?</h3>
It should be noted that empirical probability simply means a experimental probability that is based on historical data.
In this case, by definition, empirical probability is equal to the number of successful trials divided by the total number of trials.
Learn more about empirical probability on:
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<span>The point of the long-run aggregate supply curve.
I hope this helps!
</span>
Answer: 13.2%
Explanation:
Given data:
No of stores in the market = 5000
No. of store owners = 2000.
Allison charges = $8/month
Sam charges = $8/month.
Solution:
The market penetration rate would be calculated based on potential customers.
Using our general formula,
Market penetration=Numbers of customers who purchased Allison derived sales and Sam derived sales /Total potential population
Where,
Total potential population=1,500
•Allison derived sales = 129 customers
•Sam derived sales = 69 customers
•Numbers of customers who purchased Allison derived sales and Sam derived sales=129 customers+ 69 customers
•Numbers of customers who purchased Allison derived sales and Sam derived sales =198 customers
Let’s input this into our general formula.
Market penetration
= 169 customers/1,500
= 0.132*100
= 13.2%
The market penetration rate based on potential customers is 13.2%