# Thread: (Inferential) Statistics Concept Problem

1. ## (Inferential) Statistics Concept Problem

An airport executive wants to know the number of on-time arrivals at the airport yesterday.

a) How can you use statistical inference to answer his question?
b) Which variables would you collect and how many observations would your dataset hold?
c)What is the population of interest? Sample?
d) Parameter?
e) What is an example of a statistic?

a) Estimating how many flights were scheduled for yesterday.
b)
c) People on board that arrived to their destination. Sample by gathering the # of people that arrived on time
d)parameter - proportion of people that arrived on time
e)mean number of on-time arrivals

can someone help me with this problem? I missed the class first day and didn't really get to learn this material. I tried to learn by reading the book and sorta applying it on this problem. thanks for any help.

2. Originally Posted by xfyz
An airport executive wants to know the number of on-time arrivals at the airport yesterday.

a) How can you use statistical inference to answer his question?
b) Which variables would you collect and how many observations would your dataset hold?
c)What is the population of interest? Sample?
d) Parameter?
e) What is an example of a statistic?

a) Estimating how many flights were scheduled for yesterday.
b)
c) People on board that arrived to their destination. Sample by gathering the # of people that arrived on time
d)parameter - proportion of people that arrived on time
e)mean number of on-time arrivals

can someone help me with this problem? I missed the class first day and didn't really get to learn this material. I tried to learn by reading the book and sorta applying it on this problem. thanks for any help.
Statistical inference via pure probability: $\displaystyle \frac{arrivals}{arrivals + cancels}$

Who is your population of interest? Not the people, but the airplanes coming into the airport. People can be applied the same way that airplanes can. The mean is a rational number, rather than a probability statistic that is less than one.

Poisson distributions can play a huge role here, but that is way above where you are currently studying.