PPT-9.2: Scatterplots , Association, and Correlation

Objective To look for relationships between two quantitative variables Scatterplots Scatterplots may be the most common and most effective display for data In a scatterplot you can see patterns trends relationships and even the occasional extraordinary value sitting apart from the others. Correlation Objectives i Calculate correlations i Calculate correlations for subgroups using split file i Create scatterplots with lines of best fit for subgroups and multiple correlations Correlation The first infer Correlation Objectives i Calculate correlations i Calculate correlations for subgroups using split file i Create scatterplots with lines of best fit for subgroups and multiple correlations Correlation The first infer What is an association between variables?. Explanatory and response variables. Key characteristics of a data set. 1. Association between a pair of variables. Association:. Some values of one variable tend to occur more often with certain values of the other variable. Scatterplots, Association, and Correlation. Objective. : To look for relationships between two quantitative variables. Scatterplots. Scatterplots. . may be the most common and most effective display for data. . Dr. Kari Lock Morgan. Describing Data:. Two Variables. SECTIONS 2.4, 2.5. One quantitative variable (2.4). One quantitative and one categorical (2.4). Two quantitative (2.5). z-score. Which is better, an ACT score of 28 or a combined SAT score of 2100?. and correlation. The Practice of Statistics in the Life Sciences. Third Edition. © . 2014 . W.H. Freeman and Company. Objectives (. PSLS . Chapter . 3). Relationships: . Scatterplots. and . correlation. Correlation and regression are powerful tools, but have limitations.. Correlation and regression describe only linear relationship.. Correlation r and the least-squares regression are not resistant. . Correlation and Regression: The Basics. Finding the relationship between two variables . without being able to infer causal relationships. Correlation is a . statistical technique. used to determine the degree to which two variables are related. a measure of the extent to which two variables change together.. How well does A predict B?. The correlation may be positive, negative, or have no relationship.. Correlation. A . positive correlation . 4 - 5. Correlation. Definitions: . Correlation . A measure of association between two numerical variables.. 4 - 5. Scatter Plots show a . positive trend (correlation) . if as y increases, x increases.. Form: There is a somewhat linear pattern in the scatterplot. . Strength: Since the points do not closely conform to a linear pattern, the association is not very strong. . Outliers: There is one possible outlier—the student who took 8.09 seconds for the sprint but jumped 151 inches.. Fourth Edition. Chapter . 3: . Relationships:. . Scatterplots . and correlation. Copyright © 2018 W. H. Freeman and . Company. Objectives. Relationships: Scatterplots and . correlation. Bivariate data. Simple Linear Regression. April 17, 2018. Correlation . analysis* . M. easuring the degree . of association between two . continuous variables. , x and . y. We . have a . linear relationship. between x and y . Correlation, Agreement, and Diagnostic Measures. Denis Desmond. Research Statistician. nQuery. Webinar. Host. Agenda. Correlation Methods and Sample Size. Agreement Methods and Sample Size. Diagnostic Testing Methods and Sample Size.