# USING EXPERIMENTAL PROBABILITY TO MAKE A QUALITATIVE PREDICTION

## About "Using experimental probability to make a qualitative prediction"

Using experimental probability to make a qualitative prediction :

A prediction is something we reasonably expect to happen in the future. A qualitative prediction helps we decide which situation is more likely in general.

## Using experimental probability to make a qualitative prediction - Examples

Example 1 :

A doctor’s office records data and concludes that, on average, 11% of patients call to reschedule their appointments per week. The office manager predicts that 23 appointments will be rescheduled out of the 240 total appointments during next week. Explain whether the prediction is reasonable.

Solution :

Method 1 :

Given : 11 out of 100 patients reschedule.

Let "x" be the number of patients reschedule out of 240.

Write a proportion.

11 : 100  =  x : 240

Product of extremes = Product of means

(11)(240)  =  100x

2640  =  100x

Divide both sides by 100

2640/100  =  100x/100

26.4  =  x

Method 2 :

Given : 11% of the patients reschedule.

Find how many patients out of 240 reschedule using percent equation.

x  =  11 % of 240

x  =  (0.11)(240)

x  =  26.4

Conclusion :

The prediction of 23 is reasonable but a little low, because 23 is a little less than 26.4.

Reflect :

Does 26.4 make sense for the number of patients ?

The number of patients should be a whole number, so to be more accurate we should round to the nearest whole number.

Example 2 :

In emails to monthly readers of a newsletter 3% of the emails come back undelivered. The editor predicts that if he sends out 12,372 emails, he will receive 437 notices for undelivered email. Do you agree with his prediction ?

Solution :

Method 1 :

Given : 3 out of 100 emails come back undelivered.

Let "x" be the number of emails come back undelivered out of 12,372 emails.

Write a proportion.

3 : 100  =  x : 12,372

Product of extremes = Product of means

(3)(12,372)  =  100x

37,116  =  100x

Divide both sides by 100

37,116/100  =  100x/100

371.16  =  x

Method 2 :

Given : 3% of the emails come back undelivered.

Find how many emails comeback undelivered out of 12,372 emails.

x  =  3 % of 12,372

x  =  (0.03)(12,372)

x  =  371.16

Conclusion :

From the calculations done in the above two methods, it is about 371 emails out of 12,372 come back undelivered.

But the prediction given in the question is 437 emails.

It is too high.

Hence, we can not agree with the prediction of the editor. After having gone through the stuff given above, we hope that the students would have understood "Using experimental probability to make a qualitative prediction".

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