Atlanta’s Hartsfield-Jackson International Airport is the busiest airport in the world. On average there are 2,500 arrivals and departures each day.
How many airplanes arrive and depart the airport per hour?
What is the probability that there are exactly 100 arrivals and departures in one hour?
What is the probability that there are at most 100 arrivals and departures in one hour?
Let
X = the number of airplanes arriving and departing from Hartsfield-Jackson in one hour. The average number of arrivals and departures per hour is
$\frac{2,500}{24}$ ≈ 104.1667.
X ~
P (104.1667), so
P (
x = 100) = poissonpdf(104.1667, 100) ≈ 0.0366.
P (
x ≤ 100) = poissoncdf(104.1667, 100) ≈ 0.3651.
The Poisson distribution can be used to approximate probabilities for a binomial distribution. This next example demonstrates the relationship between the Poisson and the binomial distributions. Let
n represent the number of binomial trials and let
p represent the probability of a success for each trial. If
n is large enough and
p is small enough then the Poisson approximates the binomial very well. In general,
n is considered “large enough” if it is greater than or equal to 20. The probability
p from the binomial distribution should be less than or equal to 0.05. When the Poisson is used to approximate the binomial, we use the binomial mean
μ =
np . The variance of
X is
σ^{2} =
μ and the standard deviation is
σ =
$\sqrt{\mu}$ . The Poisson approximation to a binomial distribution was commonly used in the days before technology made both values very easy to calculate.
On May 13, 2013, starting at 4:30 PM, the probability of low seismic activity for the next 48 hours in Alaska was reported as about 1.02%. Use this information for the next 200 days to find the probability that there will be low seismic activity in ten of the next 200 days. Use both the binomial and Poisson distributions to calculate the probabilities. Are they close?
Let
X = the number of days with low seismic activity.
Using the binomial distribution:
P (
x = 10) = binompdf(200, .0102, 10) ≈ 0.000039
Using the Poisson distribution:
Calculate
μ =
np = 200(0.0102) ≈ 2.04
P (
x = 10) = poissonpdf(2.04, 10) ≈ 0.000045
We expect the approximation to be good because
n is large (greater than 20) and
p is small (less than 0.05). The results are close—both probabilities reported are almost 0.
On May 13, 2013, starting at 4:30 PM, the probability of moderate seismic activity for the next 48 hours in the Kuril Islands off the coast of Japan was reported at about 1.43%. Use this information for the next 100 days to find the probability that there will be low seismic activity in five of the next 100 days. Use both the binomial and Poisson distributions to calculate the probabilities. Are they close?
Let
X = the number of days with moderate seismic activity.
Using the binomial distribution:
P (
x = 5) = binompdf(100, 0.0143, 5) ≈ 0.0115
Using the Poisson distribution:
Calculate
μ =
np = 100(0.0143) = 1.43
P (
x = 5) = poissonpdf(1.43, 5) = 0.0119
We expect the approximation to be good because
n is large (greater than 20) and
p is small (less than 0.05). The results are close—the difference between the values is 0.0004.
given that a sample is normally distributed with M=10 sd=8 determine
Rosy
disscuss probability sampling
Rosy
Discuss probability sampling
Rosy
What is mean
Rosy
Probability sampling is based on the fact that every member of a population has a known and equal chance of being selected. For example, if you had a population of 100 people, each person would have odds of 1 out of 100 of being chosen. With non-probability sampling, those odds are not equal.
Willard
The Arithmetic Mean is the average of the numbers: a calculated "central" value of a set of numbers.
To calculate it:
• add up all the numbers,
• then divide by how many numbers there are.
Example: what is the mean of 2, 7 and 9?
Add the numbers: 2 + 7 + 9 = 18
Divide by how many numbers, 3
you
Willard
get 6
Willard
guidelines of designing a table
Anuradha
you can find that information on this website there is a lot of information. It's about interpreting what the concept of information & data you are getting from the graph and understanding how to read the graph and analyze the information. ***understandinggraphics.com/design/data-table-design/
sample survey is done by local government in each and every field.
syeda
statistics is used in almost every government organisations such as health department, economic department, census, weather forecasting fields
raghavendra
that's true
syeda
statistics is one of the tool that represents the falling and rising of any cases in one sheet either that is in population census whether forecast as well as economic growth
Aadil
statistic is a technique, and statistics is a subject
Probability tells you the likelihood of an event happening. ... The higher the probability, the more likely it is to happen. Probability is a number or fraction between 0 and 1. A probability of 1 means something will always happen, and a probability of 0 means something will never happen...
what statistical analysis can i run on growth and yield of spinach.
guillio
format of the frequency distribution table
henry
what is pearson correlation coefficient indicates?
Eticha
Statistic is the mean of the sample.
Raman
can anyone determine the value of c and the covariance and correlation for the joint probability density function Fxy(x,y)=c over the range 0<x<5,0<y,and x-1<y<x-1.