One professor who teaches statistics gave studentsone homework assignment. He asked students to finda two-variable data set and compute the Pearsoncorrelation coefficient. One student found a data set:one variable is students' midterm test score in anintroductory microeconomics class and totalobservations are 45 students; while the other onevariable is also students' midterm test score in anotherintroductory microeconomics class and totalobservations are 57 students. Both of these twoclasses were taught by the same instructor in spring2018. Does this student's data set make sense? Why orwhy not? Discuss and explain your reasons. You mustprovide your statistical analysis and reasons.

Correlation:Correlation determines the size and direction of the relationship between the two…

Answered: One professor who teaches statistics…

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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Over the course of a year, you find a strong, positive correlation between ice cream sales and pool drownings in a medium-sized city. The mayor decides that to prevent drownings, ice cream will be banned within the city limits. However, you show the mayor that after controlling for the high temperature of each day, the correlation between ice cream sales and number of drownings drops to zero, because that relationship was actually: Group of answer choices direct. interactive. mediating. spurious.
If it was found that two variables have a statistically significant relationship, we conclude that one variable affects the changes in the other variable without further information. This statement is (select one) True False
ab! ourses The accompanying technology output was obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of a sample of 40 people. Along with the paired sample data, the technology was also given a foot length of 13.6 cm to be used for predicting height. The technology found that there is a linear correlation between height and foot length. If someone has a foot length of 13.6 cm, what is the single value that is the best predicted height for that person? "se Hom E Click the icon to view the technology output. abus The single value that is the best predicted height is cm. endar (Round to the nearest whole number as needed.) entation ktbook a-F on unouncem ssignment: cudy Plan radebook Hydrogen Report.pdf Enter your answer in the answer box. Screen Shot 20-11...9.53 P 5,981 10 tv MacBook Pro (5
A polling organization is checking its database to see if the data sources it used sampled the same ZIP codes. The variable Datasource = 1 if the data source is MetroMedia, 2 if the data source is DataQwest, and 3 if it's RollingPoll. The organization finds that the correlation between five-digit ZIP code and DATAsource is - 0.0229. It concludes that the correlation is low enough to state that there is no dependency between ZIP code and Source of Data. Comment. Choose the correct answer below. O A. A correlation of -0.0229 is very close to zero, which implies that there is a very strong relation between the variables O B. A correlation must be between 0 and 1, so the correlation of -0.0229 must have been calculated incorrectly. O C. The source of the data is categorical, which will almost always result in very low correlation values. These types of correlations can only be interpreted in the rare instances when the correlation is close to -1 or 1. O D. The source of the data is…
Researchers Holdgate et al. (2016) studied walking behavior of elephants in North American zoos to see if there is a difference in average distance traveled by African and Asian elephants. They put GPS loggers on 33 African elephants and 23 Asian elephants and measured the distance (in kilometers) the elephants walked per day. The data in the file below Elephants contains results that are consistent with what the researchers found: Species Distance: African 6.12 African 3.65 African 4.26 African 3.8 African 5.23 African 5.02 African 5.17 African 5.37 African 4.89 African 6.4 African 6.42 African 6.85 African 3.38 African 7.71 African 4.02 African 3.52 African 5.81 African 5.83 African 7.02 African 6.11 African 4.62 African 5.54 African 3.2 African 5.49 African 5.47 African 6.97 African 3.74 African 3.04 African 7.84 African 8.62 African 7.63 African 5.25 African 4.19 Asian 1.39 Asian 2.59 Asian 8.03 Asian 7.93 Asian 0.33 Asian 8.22 Asian 6.95 Asian 2.39 Asian 3.89 Asian 10.53 Asian…
Kris works for the MESA Air Pollution Study at UW, and studies the correlation be- tween air pollution and the disease atherosclerosis. Nationally, 40% of adults suffer from atherosclerosis. Kris suspects that the proportion of people with atherosclerosis in high- pollution areas is higher. In a random sample of 600 residents of high-pollution areas, he finds that 270 (45%) subjects have atherosclerosis. At the 1% level (α = .01), is this good evidence that people in high-pollution areas are more likely to have atherosclerosis? (a) Which of the following is the Ha ? (research claim or alternate) A. Ha : p ≥ 0.40 B. Ha : pb ≥ 0.40 C. Ha : p > 0.40 D. Ha : p > b 0.40 E. Ha : p > b 0.45 F. Ha : p > 0.45 G. Ha : pb ≥ 0.45 H. Ha : p ≥ 0.45 I. None of these Hint: First read the problem and using my notes (or Hawkes) for 9.1, set up H0 and Ha . Then pick the right Ha from the above list. Dont try to guess the answer from the above list. (b) Which of the…
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The accompanying technology output was obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of a sample of 40 people. Along with the paired sample data, the technologgy was also given a foot length of 10.8 cm to be used for predicting height. The technology found that there is a linear correlation between height and foot length. If someone has a foot length of 10.8 cm, what is the single value that is the best predicted height for that person? H Click the icon to view the technology output. The single value that is the best predicted height is cm. Technology Output (Round to the nearest whole number as needed.) The regression equation is Height - 67.5 +5.15 Foot Length Predictor Coef SE Coef Constant 67.52 11.07 6.10 0.000 Foot Length 5.1508 0.4817 10.69 0.000 S-5.50271 R-Sq = 73.18 R-Sq (adj) = 72.44 Predicted Values for New Observations New Obs Fit SE Fit 95 CI 954 PI 123.149 1.605 (119.732, 126.566) (111.996, 134.302) Values of Predictors for New…
Find the line of best fit for the ordered pairs 11, 52 and13, 82. What is the correlation coefficient for these data?Why is this result reasonable?
A nutritionist collects data from 25 popular breakfast cereals. For each cereal, the number of calories per serving is plotted on the x-axis against the number of milligrams of sodium on the y-axis. The value of r for the resulting scatterplot is 0.83. How would the value of the correlation coefficient, r, change if sodium was plotted on the x-axis and calories plotted on the y-axis? The value of r would increase. The value of r would not change. The value of r would change to –0.83. The value of r could increase or decrease, depending of the strength of the new relationship.
Given two sets of data X and Y, what does a Spearman's Correlation coefficient of 1 indicate about the relationship between X and Y?
The accompanying technology output was obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of a sample of 40 people. Along with the paired sample data, the technology was also given a foot length of 17.8 cm to be used for predicting height. The technology found that there is a linear correlation between height and foot length. If someone has a foot length of 17.8 cm, what is the single value that is the best predicted height for that person? Click the icon to view the technology output. The single value that is the best predicted height is (Round to the nearest whole number as needed.) cm. Technology Output The regression equation is Height = 53.3+4.25 Foot Length Predictor Constant Coef SE Coef 53.28 11.44 Foot Length 4.2537 0.4699 S = 5.50739 R-Sq=72.3% R-Sq (adj) = 71.6% T 4.66 9.05 Predicted Values for New Observations New Obs 1 Fit SE Fit 128.996 1.733 (124.309, 133.683) 95% CI Foot New Obs Length 1 17.8 0.000 0.000 Values of Predictors for New…

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