To get a better understanding of the random process involved here, we should look at many more trials of the process, under identical conditions. We will turn to technology to do so. The applet to the right (or click here) will allow you to select a strategy and play the game thousands of times.
(e) Use the applet to simulate playing this game 10 times with the Stay strategy:
 Click on a door and then press that door again to stay.
 The computer will reveal whether you won or lost and will keep track
 Press on any of the doors again or press the Play Again button and repeat until you have played ten times
Record the percentage of wins in these 10 plays with the Stay strategy in the table in your lab report.
 Now have the computer play 10 more times with the Stay strategy by pressing the Go button. Record the percentage of wins in these 20 games in the table in your lab report.
 Then press Go again to simulate another 10 games, and record the overall percentage of wins at this point (after 30 games). Keep doing this in multiples of 10 games until you reach 100 total games played with the Stay strategy.
Record the overall percentages of wins after each additional multiple of 10 games in the table in your lab report.
Number of games 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100 
Percentage of wins 










(f) Now uncheck the Animate simulation box and change the times to play from 10 to 1000 and press Go. Report the resulting percentage of wins.
(g) What do you notice about how the percentage of wins changes as you play more games? Does this percentage appear to be approaching some common value?
Definition: The probability of an outcome refers to the longrun proportion of times that the outcome would occur if the random process were repeated a very large number of times under identical conditions. You can approximate a probability by simulating the process many times. Simulation leads to an empirical estimate of the probability, which is the proportion of times that the event occurs in the simulated repetitions of the random process. 
(h) Based on your simulation results so far, what do you estimate for the probability of winning the Monty Hall game if you use the Stay strategy? [
Hint: Keep in mind that probabilities should always be expressed as decimal values between 0 and 1.]
The probability of winning with the Stay stragtegy being 1/3 makes sense, because your chance of picking the correct door to begin with is oneoutofthree. Many people believe the probability of winning with the Switch strategy is 0.5 because there are now just two doors. Our simulation tools give us a very easy way to investigate this.
 Return to the Monty Hall applet and use the pulldown menu to now use the "Switch" strategy.
 Set the number of times to 1000
 Uncheck the Animate simulation box
 Press the Go button


When you create output like this, we will often want you to save your results. Options for Screen Captures.
(i) Create a screen capture of your results (the table and the Cumulative Win Proportion graph). Based on the 1000 simulated repetitions of playing this game, what is your estimate for the probability of winning the game with the “switch” (i.e, change) strategy?
(j) Does one strategy appear to be better than the other? If so, by a lot or just a little? Justify your answers.
(k) The probability of winning with the “switch” strategy can be shown mathematically to be 2/3. (One way to see this is to recognize that with the “switch” strategy, you only lose when you had picked the correct door in the first place.) Explain what it means to say that the probability of winning equals 2/3.[Hint: Recall our earlier definition of probability. I want an interpretation of this number, not simply an evaluation statement of whether you think it is large or small.]