A researcher has a large number of data pairs (age, height) of humans from birth to 70 years. She computes a correlation coefficient, r. a. Would you expect it to be positive or negative? Why? b. What would you suggest to be a major problem with this approach? In other words, would you trust the correlation coefficient? c. The researcher now decides to use data only for adults ages 21 to 60 to compute a correlation coefficient. What value of r should she expect now?
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
A researcher has a large number of data pairs (age, height) of humans from birth to 70
years. She computes a
a. Would you expect it to be positive or negative? Why?
b. What would you suggest to be a major problem with this approach? In other words,
would you trust the correlation coefficient?
c. The researcher now decides to use data only for adults ages 21 to 60 to compute a
correlation coefficient. What value of r should she expect now?
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