C784 Module 6: Correlation & Regression Questions Fully Solved Guaranteed Success.

lurking variable - correct answer A variable that is not included in an analysis but that is related to two (or more) other associated variables which were analyzed. simple linear regression - correct answer the prediction of one response variable's value from one explanatory variable's value Simpson's Paradox - correct answer A counterintuitive situation in which a trend in different groups of data disappears or reverses when the groups are combined. degree - correct answer The largest exponent in a mathematical expression or equation. causation - correct answer A relationship of cause and effect between two or more variables. linear interpolation - correct answer Estimation using the linear regression equation is between known data points. association - correct answer A pattern or relationship between two variables. coordinate plane - correct answer A tool for graphing consisting of a horizontal x-axis and a vertical y-axis. regression equation - correct answer An equation used to model the relationship between two quantitative dependent and independent variables. scatterplot - correct answer A graph that uses dots on a coordinate plane to show the relationship between variables. Regression Analysis - correct answer a statistical tool that quantifies the relationship betwn a response variable and one or more explanatory variables least squares - correct answer A technique for finding the regression line. slope-intercept form - correct answer A common format for the equation of a line: y = mx + b, where m is the slope and b is the y-intercept. regression line - correct answer The line of best fit to show the relationship between variables, the one that minimizes distance from each data point to the line. A linear regression equation takes the following form: y = mx^2 + b. True or False? - correct answer false. This is not the form that a linear regression equation takes. Linear regression is always of degree 1, so the exponent of 2 associated with the x makes this a non-linear equation. A linear regression "best-fit-line" can be estimated using least squares. True or False? - correct answer true. Least squares estimation is the most common technique used to estimate the best-fit-line in linear regression. Linear extrapolation is always a reliable method of prediction. True or False? - correct answer false. Extrapolation assumes that the linear pattern of the data will continue outside of the range of data points. This may not always be the case and therefore may not always be a reliable method of prediction. Linear interpolation is a technique used to make a prediction that falls between known data points. True or False? - correct answer true. Linear interpolation is a technique used to make a prediction that falls between known data points, using the linear regression equation. Least squares estimation is a technique for predicting future data values. True or False? - correct answer false. Least squares estimation is a technique used to estimate the best-fit-line in linear regression. EXTRAPOLATE - correct answer Using information from a data set to make predictions about data outside of the original set. POPULATION - correct answer An entire pool from which a sample is drawn. SAMPLE SIZE - correct answer Statistics: the number of individuals measured or observed in a study. Probability: number of possible outcomes in a trial or experiment. Extrapolation is always inappropriate. True or False? - correct answer false. There are applications of extrapolation, and times in which it is necessary. Be mindful of the situation and try to avoid inappropriate extrapolation by considering the context. Which of the following statements is most appropriate with regards to representative samples? a. The risk of non-representative sample decreases as sample size increases. b. The risk of non-representative sample size decreases as sample size decreases. c. The risk of non-representative sample size increases as sample size increases. d. The sample size has no bearing on whether or not the sample size is representative - correct answer a. In general, the risk of non-representative sample decreases as sample size increases. Which of the following qualities of a sample help ensure the accuracy of any analysis, including a regression analysis? a. a large sample b. a representative sample c. Both a and b - correct answer c. When conducting a study, it is important to use a large, representative sample. Which of the following improves a study's reliability as it increases? a. Correlation coefficient b. Regression equation slope c. Sample size d. Simpson's Paradox - correct answer c. Small study populations can impact the reliability of regression analysis. Nurses need to be aware of the study size when attempting to perform a regression analysis or interpret a study based on small study size. Analysis of the scatterplot below suggests that as testosterone levels increased, blood pressure decreased. What problem in regression is evident in this analysis? - correct answer The Association is Not Causation This analysis is obviously missing a lurking variable which, in this case, is obesity. It is nonsense to try to estimate a patient's blood pressure based on testosterone level. Therefore, the association is not a causation. From the scatterplot below, if the trend line would be extended indefinitely, it would correspond with a patient's systolic blood pressure in excess of 250mmHg. What pitfall in regression analysis is evident in this chart? -