Correlations Descriptive Statistics Mean Std. Deviation Overall quality as an 4.1670 .59731 50 instructor Overall course quality 3.9310 .64664 50 Number of publications 8.40 11.348 50 Number of times cited 49.52 57.272 50 by other authors Corre lations Overall Number of quality as an Overall course quality .638** Number of times cited by other authors instructor publications .232 Overall quality as an instructor Pearson Correlation Sig. (2-tailed) .312* .000 .105 .028 50 50 50 50 Overall course quality Pearson Correlation Sig. (2-tailed) .638** .347* .372** .000 .014 .008 50 50 50 50 Number of publications Pearson Correlation .232 .347* .828** Sig. (2-tailed) .105 .014 .000 50 50 50 50 Number of times cited Pearson Correlation .312* .372** .828** by other authors Sig. (2-tailed) .028 .008 .000 50 50 50 50 **. Correlation is significant at the 0.01 level (2-tailed). *. Correla tion is significant at the 0.05 level (2-tailed).
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.
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