Example 13: Stock TATA and BIRLA display the following returns over the past three years: Year Return ТАТА BIRLA 1994 14 12 1995 16 18 1996 20 15
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- Reconsider the partial & part correlations for this scenario: SEE IMG_9788.jpg Which of the following options provides the best interpretation of the part correlation for Anxiety Score? A) Anxiety Score explains an additional 5.7% (rpart2 = .2392 = .057) of the variation in depression score, over and above that explained by the other predictors B) Anxiety Score explains an additional 23.9% (rpart = .239) of the variation in depression score, over and above that explained by the other predictors C) When all the other predictors (age, gender and anxiety score) are statistically controlled, there is a moderate, positive, linear relationship between Anxiety Score and depression score (rpart = .239) D) When all the other predictors (age, gender and anxiety score) are statistically controlled, there is a very weak, positive, linear relationship between Anxiety Score and depression score (rpart = .239)A researchers says that 50% of the variance in blood pressure can be predicted from HR and that blood pressure is postively associated with HR. What is the correlation between blood pressure and HR?One professor who teaches statistics gave students one homework assignment. He asked students to find a two-variable data set and compute the Pearson correlation coefficient. One student found a data set: one variable is students' midterm test score in an introductory microeconomics class and total observations are 45 students; while the other one variable is also students' midterm test score in another introductory microeconomics class and total observations are 57 students. Both of these two classes were taught by the same instructor in spring 2018. Does this student's data set make sense? Why or why not? Discuss and explain your reasons. You must provide your statistical analysis and reasons.
- discuss the importance in business decision making-making within an organisation of identifying potential correlations between two different business variableAn Economics instructor assigns a class to investigate factors associated with the gross domestic product (GDP) of nations. Each student examines a different factor (such as life expectancy, literacy rate, etc.) for a few countries and reports to the class. Apparently, some of the classmates do not understand Statistics very well because several of their conclusions are incorrect. Explain the mistakes in comments a and b below. a) Explain the mistake in the statement "There was a very strong correlation of 1.22 between Life Expectancy and GDP" Choose the correct answer below O A. A correlation cannot be greater than 1. O B. A correlation that is greater than 1 implies that the variables are not quantitative, so the correlation cannot be interpreted. OC. A correlation that is close to 1 implies a very weak correlation. The correlation must be close to 10 for it to be interpreted as a very strong correlation. O D. A correlation that is greater than 1 implies a weak correlation, not a…Natural selection predicts that two species that came from a common ancestor should have a high degree of correlation in their genomes. What aspect (use) of correlations am I using when apply it for this purpose?
- Since the chi-square does not indicate the strength of the association, a researcher must then conduct a separate test for the measure of association. True FalseThis is an exercise. Can we use Serial Correlation (Breusch-Godfrey Test) Test as a method/technique to measure the relationship between the variables of education and income inequality in order to analyze the impact of education level on income inequality? Explain.