Professor Rouge wants to see if the color red increases people's attraction. For all participants, sheshows them someone in a red shirt, someone in a blue shirt, and someone in a green shirt - and theparticipant rates each person from 1-10 in terms of their attractiveness. The data that she collectedare below. Conduct the appropriate statistic in order to test her hypothesis. Include calculations ofthe effect size. Report your findings in a brief paragraph (a complete paragraph, like the one fromclass) and include the two tables that we did in class.ParticipantRedGreen Blue1726.1076.48UploadChoose a File6.

Answered: Image /qna-images/answer/f0b30ba6-937b-4a2a-b4b7-c8c3160af72a.jpg

Answered: Professor Rouge wants to see if the…

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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A new cream was developed to reduce the irritation caused by poison ivy. To test the effectiveness, researchers placed an ad online asking for volunteers to participate in the study. One hundred subjects replied and were informed that one group would receive the new cream and the other group would Which of the following accurately describes the benefit of comparison in the experiment? O The overall level of irritation can be compared to see if the new cream had a significant effect. O The level of irritation for both groups can be receive a cream with no active ingredient. All 100 subjects were exposed to poison ivy. Fifty were then randomly assigned to the group with the new cream, and 50 were randomly assigned to the group with the cream with no active ingredient. After three days, the subjects' level of irritation was measured. compared to see if the new cream had a significant effect. O The level of irritation in the treatment group only can be compared to see if the new cream had…
What is the coefficient of determination for two variables that have perfect positive linear correlation or perfect negative linear correlation? Interpret your answer. Choose the correct answer below. O A. Two variables that have perfect positive or perfect negative linear correlation have a correlation coefficient of 1 or 0, respectively. This means 100% of the variation in the response variable is explained by the variation in the explanatory variable. O B. Two variables that have perfect positive or perfect negative linear correlation have a correlation coefficient of 1 or - 1, respectively. In either case the coefficient of determination is 1, which means 100% of the variation in the response variable is explained by the variation in the explanatory variable. O C. Two variables that have perfect positive or perfect negative linear correlation have a correlation coefficient of 1 or - 1, respectively. In either case the coefficient of determination is 1, which means 0% of the…
The stated goal of a chain of service stores is to provide a lube and oil change for anyone's automobile in 15 minutes. The manager at one store thinks that there is a growing disparity among his workers in the time it takes to lube and change the oil of an automobile. To monitor this, the manager has selected a sample of 20 days and has recorded the time it took five randomly selected employees to service an automobile. The data are found below. Complete parts a through d Click the icon to view the data. a. The manager noticed that the longest time it took to service a car was 25.73 minutes. Suppose the distribution of fimes to service a car was normal, with a mean of 15. Without analyzing the sample data, use your knowledge of a normal distribution to give the manager an estimate for the population standard deviation for the time it takes to service a car. The standard deviation is minutes. (Round to two decimal places as needed.) b. Use the data to construct an x- and an R-chart.…
Suppose a researcher is interested in examining the relationship between a person 's age and whether he or she likes the taste of cilantro. She collects a sample of n- 10 people and asks them whether they like the taste of cilantro. The following table summarizes the results. Does not like Cilantro Does like Cilantro 18 years old 2 18+ years old 3 The researcher wants to calculate the correlation between a person 's age and whether he or she likes the taste of cilantro. To do so, you (the researcher) must first create a table of the data by converting each variable to a numerical value. Assign a 0 to "< 18 years old" and 1 to "18+ years old." Then assign O to "does not like the taste of cilantro" and a 1 to " likes the taste of cilantro." Complete the top two rows of the your (the researcher's) data. Age (0 is <18; 1 is 18+) Likes the taste of Cilantro (0 is no; 1 is yes) a) ob) 1 a) Ob) 1 a) ob) 1 a) Ob) 1 1 1 1 1 1 1 1 The phi-coefficient is a) -0.09 b) -0.16 c) -0.20 d) 0.80
There is a correlation between the number of hours you study for an Exam and a higher score. The following data was collected from a recent class survey compairing the Number of hours spent preparing for an exam and that person final score. Data Follows: Kyle studied 1 hr, score 65%, Sue studied 4 hrs, 88%, Jim studied 3 hrs, 80%, Paul studied 0 hrs, 63%, Alex studied 5 hrs, 97%, Linda studied 2 hrs, 73%, Mindy studied 4.5 hrs, 90%, Joel studied 1.5 hrs, 72%. DISPLAY THE DATA ON A LINE GRAPH USING THE "X" AXIS FOR THE NUMBER OF HOURS STUDIED, AND USE "Y" AXIS FOR THE SCORES EARNED ON TEST. WHEN COMPLETED, DRAW A FITTED LINE TO SHOW A NEGTIVE OR POSTIVE CORRELATION.
time in studying, the higher is their academic performance. O b. There isa strong negative correlation between the number of hours spent by the learners in studying and their academic performance. As a learner spends more time in studying, the lower is their academic performance. O c. There is a perfect correlation between the number of hours spent by the learners in studying and their academic performance. As a learner spends more time in studying, the higher is their academic performance. O d. There is no correlation between the number of hours spent by the learners in studying and their academic performance. From the study "Increasing Mathematics Achievement through Contextualized and Localized Materials in Distance Learning", which of the following statement/s are true about its dependent and independent variables? I. Mathematics achievement is the dependent variable
A pediatrician wants to determine the relation that may exist between a child's height and head circumference. She randomly selects eleven 3-year-old children from her practice and measures their heights and head circumference. According to the data, the linear correlation coefficient between the height and head circumference of a child is 0.918. Compute the coefficient of determination, R². A. 91.8% O B. 84.3% OC. 82.6% O D. 8.2%
Mr. Friend noticed that meetings tended to start late when there were a lot of people in attendance and decided to study that relationship. He collecting data on the number of people who were attending each meeting and the number of minutes late that the meeting started. He noticed there was one point that seemed unusual, so he removed it from the data set. What is true about the point that was removed? a. the point is not unusualb. It is an influential observationc. It has the largest residuald. The slope changes little when the point is removedSelected:e. The correlation is lower with the removal of the point
Please answer the letters d, e and f. Thank you!
Dr. Wright, a researcher at the Young County Botany Institute, reported the following correlations. The correlation between pH level of soil and tomato weight is r₁ = 0.8. The correlation between hours of sunlight and tomato weight is r2 = 0.7. According to this information, which of the following statements are true? Select all that apply. ✓Larger tomatoes result from more daily hours of sunlight. Larger tomatoes result from lower soil pH level. ✔Tomato size is related more strongly to hours of sunlight than to soil pH level. None of these are true.
Enrique wishes to determine if there is a linear correlation between the age of a driver and the death rate for car crashes. The following table represents the age of a driver and the death rate of drivers for car crashes in the same age category per 100 Million Miles Driven. Use a significance level of a = 0.05. Do not round between calculation steps; only round final answers. Driver's Age (x) 17 21 30 32 35 36 47 63 74 Death Rate (y) 5.6 6.6 5.9 5.1 5 5.6 4.9 4.1 3.7 10 10 20 30 40 60 70 90 100 50 Driver Age 80 Death Rate
This question has 6 parts, Thank you.

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