The table gives data about a random sample of 16 cats brought to a veterinarian'soffice during one week.SexWeight(pounds)12Age(years)11Age(years)SexWeight(pounds)9.MaleFemaleFemale9.Male12Female8.12Female713Male1015Male1111Female1010Female1013Male1110Male136.Male1011Female8.12Male117Female91658 f) For the age data, Q1 = 8.5 and Q3 = 12.5. By examining the histogram of theage distribution, find the probability that the age of a randomly chosen cat fallsbetween Q1 and Q3. Why does that make sense?%3Df).

Given: Age data after sorting. 2 5 7 8 9 10 10 11 11 11 12 12 13 13…

Answered: f) age distribution, find the…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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A 1 6. Height (om) 2 179 3 174 4 156 171 6. 170 7 165 8. 170 157 10 155 11 157 12 177 13 172 14 154 15 155 16 158 17 170 18 174 19 170 20 154 21 172 22 164 23 173 24 164 25 172 26 173 27 150 28 150 29 160 30 150 31 166
Which set of data would probably show a strong positive linear correlation? a) the number of defective light bulbs produced and the time of the day when they were manufactured b) marks on a history test and the heights of the students c) the colour of cars sold and the annual income of the car buyers d) the height of corn in a field and the amount of precipitation during the growing season acer
Warren wants to know if the amount of coffee that you drink is related to the number of hours that you stay awake. He recruits 50 participants using random sampling to report how much coffee they drank and the time of the day that they went to sleep. He then performs a correlation to determine the association between the amount of coffee that was consumed and the number of hours that they stayed awake. There was a statistically significant positive correlation between amount of coffee that participants drank and the number of hours that they stayed awake, r(49) = .82, p < .05, two-tailed, r2 = .08. This was a small effect – 8% of the variance in the amount of coffee drank is explained by hours that you stay awake (and vice versa).
Cody took his first physics exam and scored an 80. The population mean for this exam is 70, and the standard deviation is 5. What is the probability of selecting a person with a score greater than Cody’s?
Which set of data would probably show a strong positive linear correlation? a) the number of defective light bulbs produced and the time of the day when they were manufactured b) marks on a history test and the heights of the students c) the colour of cars sold and the annual income of the car buyers d) the height of corn in a field and the amount of precipitation during the growing season
The NJ Department of Health has reported the average life span of NJ residents is 81 years. If the standard deviation is σ = 4 years, what is the probability of a person living to at least 92 years of age?
Micah is interested in testing whether college students' levels of gratitude change over the course of the semester. He randomly selects a sample of 100 students and assesses their levels of gratitude at the beginning, and end of the semester. Question 17 options: ANOVA Paired samples t test Independent samples t test Correlation
If the proportion of Hs is .25 out of 200 flips, what is the p-value? Round to three places.
find the z score in which 93.70% of the z scores in a population are below that value
There is a negative correlation between the average litres of wine consumed by residents of a country and the incidence of national coronary deaths. Explain why correlation in this case does not imply causation by suggesting a third variable z that explains the correlation. Is z a common response or a confounding variable? Draw a digraph illustrating the between x, y, and z
(b) Calculate the sample correlation coefficient r. (c) Describe the type of correlation, if any, and interpret the correlation in the context of the data. (d) Use the table of critical values for the Pearson correlation coefficient to make a conclusion about the correlation coefficient.
A=14%B=34%

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f) age distribution, find the probability that the age of a randomly chosen cat falls between Q1 and Q3. Why does that make sense? For the age data, Q1 = 8.5 and Q3 = 12.5. By examining the histogram of the %3D