Applied Probability and Statistics - C955 - Module 6 Correlation & Regression with 100% correct answers

lurking variable A variable that is not included in an analysis but that is related to two (or more) other associated variables which were analyzed. observational study The researcher observes if there is an association between variables. There is no treatment or control group. sampling method The technique used to select people within the sampling frame. correlation An observed relationship between two quantitative variables. While this is most commonly a linear relationship, it does not need to be. Note that observing a relationship does NOT imply that there is a meaningful causal link between the variables. coordinate plane A tool for graphing consisting of a horizontal x-axis and a vertical y-axis. correlation coefficient A measure of the linear relationship between two attributes. The numerical value demonstrates how closely the attributes vary together. Correlation coefficients near -1 and +1 have strong linear correlation, while a correlation coefficient near 0 has weak (or no) linear correlation. linear interpolation Estimation using the linear regression equation in between known data points. least squares A technique for finding the regression line. voluntary sample Researchers invite everyone in the sampling frame to participate. Individuals who voluntarily respond comprise the study sample. scatterplot A graph that uses dots on a coordinate plane to show the relationship between variables. representative sample A subset of the population with similar characteristics to the entire population. significance level The p-value cutoff for statistical significance. Any p-value below the set significance level is considered statistically significant. hypothesis test A statistical test that tells us whether a result is significant. slope-intercept form A common format for the equation of a line: y = mx + b, where m is the slope and b is the y-intercept. significant difference A measurable difference between two groups or samples that reflects a real difference, rather than the difference being by chance. Simpson's Paradox A counterintuitive situation in which a trend in different groups of data disappears or reverses when the groups are combined. negative correlation A linear relationship between two quantitative variables in which the dependent variable increases as the independent variable decreases. causation A relationship of cause and effect between two or more variables. sampling frame The list of all people or things that may be included in the statistical study. association A pattern or relationship between two variables. sample The subset of the study population that is being studied. linear extrapolation Estimation using the linear regression equation is made outside known data points. simple linear regression The prediction of one response variable's value from one or more explanatory variables' value when there is a linear relationship between the two variables. statistically significant The presumption that a given result or relationship is caused by more than just random chance. population All subjects in the study which have the characteristics being evaluated. causal relationship A relationship between two variables that can be classified as cause-and-effect. regression line The line of best fit to show the relationship between variables, the one that minimizes distance from each data point to the line. regression analysis A statistical analysis tool that quantifies the relationship between a response variable and one or more explanatory variables. experimental study The researcher applies a treatment to one group and no treatment (or placebo) to a control group, to determine if there is causation between variables.