Transcript Statistics Chapter 1 Statistical Reasoning: Investigating

Section 1.2
Discrimination in the Workplace:
Inference through Simulation

Inference:

Simulation:
a statistical procedure that involves deciding
whether an event can reasonably attributed to chance OR if
you should look for another explanation.
Setting up a model to simulate the actual
process and repeating it to see what happens. This is then
compared to what actually occurred.

Summary Statistics: a single number that
condenses and summarizes the data.

Average or Mean is a summary statistic
 Sum of the data values / # of data values (n)

Simulate selecting 3 employees out of 10 to
lay off. Like round 2 of the lay offs from 1.1.
 How would you do that with simple materials?

Refer to page 13 for an example simulation.

Follow these steps.
 The ages to use are written on the board.
 Repeat the process 10 times.



Using a TI-83 or higher:
Assign each employee a number 1 – 10.
Use the “randInt” function to randomly select
a value from 1-10.
 MATH key
 PRB
 randInt(1,10,n) (start, end, n selections)
 What if you select the same number twice?
▪ randInt(1,10,6): take the first 3 non-duplicated values.
Create a classroom Dot Plot of your averages for each
repetition.
 Look at the Dot Plot: How many times did we get a
result of 58 or higher?
 Based on our simulation, what is the probability that
you would randomly get an average age of 58 or
higher?

 Probability: proportion of successes out of total trials in
the long run.

If Westvaco was truly unbiased by age would you
expect that they chose the people they did? Explain.

If we decided that the probability was high enough that
there was reasonable possibility that Westvaco could have
chosen those employees without bias, then they may be off
the hook.

However, if the probability was very low, we can say that it is
very unlikely that they chose those employees unbiased of
age.
 They may still have valid reasoning, but now the need for
an explanation is on them.

P5 on page 17

E11 on page 19