oe has learned how to use in R, but hasn’t really bothered to learn much about statistics. He measures 1) gender (male or female), 2) GPA, 3) number of close friends, 4) number of hours worked a week, and 5) dollar amount of student loans. He uses R to calculate bivariate correlations between all 5 measures (Pearson’s r). He is excited to discover a number of interesting correlations. You need to break some bad news to him, however: some of his ‘findings’ don’t make any sense. Which of Joe’s results is an improper use of statistics? (a)For number of close friends and hours worked a week, Pearson’s r = -0.65 (b)For GPA and amount of student loans, Pearson’s r = -0.75 (c)For GPA and number of close friends, Pearson’s r = 0.60 (d)For amount of student loans and hours worked a week, Pearson’s r = 0.90 (e)For gender and hours worked a week, Pearson’s r = 0.80
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.
Joe has learned how to use in R, but hasn’t really bothered to learn much about statistics. He measures 1) gender (male or female), 2) GPA, 3) number of close friends, 4) number of hours worked a week, and 5) dollar amount of student loans. He uses R to calculate bivariate
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