Question

Problem 2 ( 1 ____( solve_R__RStudio )

A particle measurement system in Shandong, China measures the count of particles less than 10 microns in diameter (PM10). It produces daily averages. It measures PM10 levels in the “alert” range of between 150 to 250 mg/m³ a number of times during the last 50 days – listed in the data sheet as “past alerts=9”. Predict the probability of the number of “future alerts” in the next 30 days, predicted alerts = 5

future alerts" = "predicted alerts".

Problem 5 ( 1 ____( solve_R__RStudio ))

-If in problem 2 the data set was comprised of measurements every minute, do you think the procedure predicting the next 30 minutes based on the last 50 minutes would work? Why or why not? What conditions are necessary for your calculation in problem 2 to be valid?

- In 4 coin tosses the probability of getting 2 heads is 0.375. The probability of getting 1 head out of 2 tosses is 0.50. In both cases half the tosses are predicted to be heads, so why is the probability higher for 1 of 2 tosses versus 2 of 4 tosses?

-In many of the calculations above we are assuming that any time you take a sample, the statistics of the larger population do not change. But you know when you are drawing cards, if two aces have been drawn, the probability of drawing another ace is reduced. Why can we normally ignore the effect of drawing a sample on the statistics of the parent population?

Answer 1

There are more than 1 questions, as per the Q&A guidelines i am answering first question. If you want to get the answers for the rest of the parts, please post the question in a new post.

Please give me a thumbs-up if this helps you out. Thank you!