1. Regression coefficient: this is a term that is yielded by a regression analysis which indicates the sensitivity of the dependent variable to the independent variable. The regression coefficient represents the net effect the variable on the dependent variable, holding the remaining variables in the equation constant
2. Regression line: a line fit to a set of data points using least-squares regression. The regression line is a line of best fit or a line that represents a linear relationship between two variables.
3. Z score: represents the position of the original score relative to its mean and standard deviation.
4. Outlier: this is a data point (or multiple points), which are found far outside most of the rest of the data points.
5. t-test for regression coefficients: the t test for a regression coefficient an be used to test the null hypothesis that the population regression coefficient equals zero.
6. t-test for correlation coefficients: the t test for a population correlation coefficient an be used to test the null hypothesis that the population correlation coefficient equals zero.
7. Descriptive statistics: descriptive statistics describe data by organizing and summarizing data with tables and graphs. Descriptive statistics describe data with averages, variability, normal distributions and standard scores, measures of relationships (correlation) and prediction.
8. Inferential statistics: inferential statistics are used to imply relationships when examining data.
9. Data sets: a collection of data that is related.
1. Descriptive statistics differs from inferential statistics in that it simply describes data, while inferential statistics are used to imply relationships when examining data. Descriptive statistics provide a description related to the sample only and inferential statistics allow for findings from samples to be generalized to populations and allow for the testing of hypotheses.
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