I need help solving this statistics problem. The waiting times between a subway departure schedule and the arrival of a passenger are uniformly distributed between 0 and 7 minutes. Find the probability that arandomly selected passenger has a waiting time greater than 3.25 minutes.Find the probability that a randomly selected passenger has a waiting time greater than 3.25 minutes.(Simplify your answer. Round to three decimal places as needed.)Help Me Solve ThisView an ExampleGet More Help -Clear AllCheck AnswerB.82°F Sunnyamaon(99+

Given X~U(0,7) We want to find the probability P(X>3.25)= ?

Answered: The waiting times between a subway…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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I need help with just part c. Someone on here already answered it for me but I'm really confused as there are steps missing and I'm not sure what to put in the calculator. " The first quartile separates the lowest 25% of the observations from the higher 75% of the observations. The first quartile is denoted by Q1. The second quartile separates the lower 50% of the observations from the higher 50% of the observations. The second quartile is denoted by Q2.The second quartile is same as median. The third quartile separates the lowest 75% of the observations from the higher 25% of the observations. The third quartile is denoted by Q3. The third quartile can obtained as follows...." Third Quartile is 1 somehow, and I don't understand how it is.
I am doing a case study for statistics and I have to do a report with it. What do I include on the report? Do I just add bar graphs scatter plots and histograms? can I add multiple regression tables to the report? What should I not include?
Please help with this problem. Can you please explain using a calculator. Thank you.
If the data points do not lie in a straight line, there is no relationship between the variables True False
Here is an example from John and Jenn. When we return exams in our classes, we find it beneficial to share with students information on the distribution of scores. We provide this information so that students will have an idea of how they scored on the exam in comparison to their peers. However, deciding which descriptive information to provide to the class is not always an easy decision. These are modified grades from one of Jenn’s statistics classes. For this data set, the mean is 77, the mode is 92, and the median is 86. If you were the professor of the class, do you think sharing the mean scores on the exam with the class is a representative score of the data set? Why or why not? 9 or 11. The researchers predicted that the more a mother weighed during pregnancy, the higher the fat mass would be in the child. Such findings would support the developmental over nutrition hypothesis, which states that overeating during key developmental times has an influence on the offspring. The…
please explain!
The process of moving from theory to data, where the data would test the theory, is known as.......?
If most of the scores in a large data set are about close together except for a few scores that are quite a bit higher, how would the mean and median of the data set compare and what shape would a histogram of the data set have? The mean would be smaller than the median and the histogram would be skewed with a long tail towards higher scores. The mean would be larger than the median and the histogram would be skewed with a long tail towards lower scores. The mean would be smaller than the median and the histogram would be skewed with a long tail towards lower scores. The mean would be larger than the median and the histogram would be skewed with a long tail towards higher scores. The mean would be equal to the median and the histogram would be symmetrical. None of the answers listed.
On average, a sample of n = 36 scores will provide a better estimate of the population mean than a sample of n = 49 scores from the same population.
The time data is therefore the (Chebyshev's Rule, Empirical Rule) says we should expect of the time data to be minutes.
You are a paranoid delusional statistician with far too much time on your hands. One day, you sit down to have a bowl of soup. This bowl of soup happens to be Tic-Tac-Toe themed, meaning that you have some noodles that are shaped like an X, and some that are shaped like an O. As you stir your soup, you notice that this bowl seems to have a particularly high number of X- shaped noodles in it. Being paranoid, you conclude that this has some meaning like someone is trying to give you a message, possibly warning you of the dangers of x-rays. You jump out of your seat and run to get your x-ray-proof cape, and then you pause for a moment and think that you should calculate a chi-square statistic for the frequency of X-shaped noodles before freaking out. First, you carefully separate each of the noodles by shape and count them. Here is what you find: Frequency of Noodles X-shaped 33 O-shaped 21 2. Write out the null and alternative hypotheses using symbols: Но: На:
Melinda thinks that stress might predict lower grades on a statistics final exam. She gives a sample of statistics students a questionaire and then looks for relationships between their answers and their final exam scores. Although she finds no support for her original hypothesis, she does find that the the numbers of hours that students work outside of school is related to exam performance. When she reports the results of her study, she presents them as if the relationship between number of hours worked and exam performance was her original hypothesis. This is a questionable research practice known as: a. open science b. p-hacking c. HARKing d. constraints of generality

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