The image features a scatter plot graph representing the correlation between "Chocolate consumption (kg/yr per person)" on the x-axis and "Nobel laureates (per 10 million people)" on the y-axis. The graph shows data points for various countries, each represented by a blue dot and labeled with the country's name. The correlation coefficient \( r = 0.791 \) is indicated at the top left of the graph, suggesting a strong positive correlation between chocolate consumption and the number of Nobel laureates.Countries generally follow a trend that suggests higher chocolate consumption is associated with a higher number of Nobel laureates, though with some variation. Switzerland is positioned as an outlier with notably high values for both chocolate consumption and Nobel laureates, compared to other countries.**Analysis Question:**What effect does Switzerland have on the correlation? Explain.**Explanation:**Switzerland, as an outlier, likely increases the correlation coefficient due to its high values in both variables, reinforcing the positive trend. Removing or altering its values could potentially lower the correlation, reflecting less association between chocolate consumption and Nobel laureates.

Correlation is a statistical term describing the degree to which two variables move in coordination…

Answered: What effect does Switzerland have on…

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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Fully explain the issues and problems with the below correlational data. Focus on the data in the highlighted box versus the rest of the data. Do not try to explain the data, but rather focus on the statistical issues and problems. IF YOU CAN'T SEE THE IMAGE HERE. PLEASE GO TO THIS LINK Linke 10 6. 8. 7. 5. 4. 10 20 30 40 50 60 70 80 90 100 Age Enjoyment of Hip-Hop
What is another possible explanation for this correlational relationship? Since this is just a correlation, we can’t be sure if age causes changes in your field goal percentage. So, what is one possible other explanation that you can come up with for the correlation that you calculated (hint: think about possible "third variable" explanations for this correlation---what other variables or factors might be causing changes in both x and y that could explain this correlation?).
Write a research question that can be explained with a correlation a. Do you have an IV?b. Do you have a DV?
What is another possible explanation for this correlational relationship? Since this is just a correlation, we can’t be sure if age causes changes in your field goal percentage. So, what is one possible other explanation that you can come up with for the correlation that you calculated (hint: think about possible "third variable" explanations for this correlation---what other variables or factors might be causing changes in both x and y that could explain this correlation?).
What is a reason why correlation does not imply causation? O Because correlations are not based on data. O Because you do not know if X or Y occurred first. O There could be a third variable that explains both X and Y. O Both b and c
You have data on the incidence of three types of malaria (A, B, and C) in three tropical regions (Africa, Asia, South America) . Is there a relationship between location and type of malaria? What is the appropriate test to answer this question? A Paired Samples t test B Correlation C Chi Square test D Independent Samples t test
According to multiple research, there is a -0.697 correlation between happiness and loneliness. This means that _________. a. People who are happier tend to be less lonely. b. People who are happier tend to be more lonely. c. There is no link between happiness and loneliness. d. There is a causal relationship between happiness and loneliness.
Which of the following is an appropriate research question for a correlation? Group of answer choices Is there a relationship between weather and mood? Does cold weather impact mood? Does drinking milkshakes make children happy? Does exercising reduce weight?
Find a best fit line for ice cream consumption and murders. This is a classic example of "spurious" correlation. Ice Cream 2,1,2,3,2,4,5,3,2,1,2,1 Murders 8,21,16,18,22,25,22,30,20,10,14,9
When can correlation evidence help answer a casual question?

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