he following data relate to the age of ten employees and the number of days they reported sick in a month Employee age 20 30 32 35 40 46 52 55 58 62 Number of days absent: 11 12 10 13 14 16 15 17 18 19 i. Compute the Pearson Correlation coefficient between Employee age and number of days absent ii. Test the statistical significance of the correlation coefficient computed in (i) above
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.
The following data relate to the age of ten employees and the number of days they reported sick in a month
Employee age 20 30 32 35 40 46 52 55 58 62
Number of days absent: 11 12 10 13 14 16 15 17 18 19
i. Compute the Pearson
ii. Test the statistical significance of the correlation coefficient computed in (i) above
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