(a) Draw a scatter dagram of the data. Choose the correct answer below. OA. OB. OC. OD. 4- 24 2- 24 Compute the linear correlation coefficient The linear correlation coefficient for the four pieces of data is (Round to three decimal places as needed.) (b) Draw a scatter dagram of the data with the addisonal data point (10.3.0.3). Choose the correct answer below . OA. OB. Oc. OD. 12 124 124 4 . 4 ... Compute the linear correlation coefficient with the additional data point. The linear corelation coeffcient for the fve pieces of data is (Round to three decimal places as needed.) Comment on the effect the additional data point has on the linear correlation coeffcient. . A. The additional data peint weakens the appearance of a inear association between the data points . OB. The additional data point does not affect the linear correlation coefficient. Oc. The additional data point strengthens the appearance of a linear association between the data points. Explain why comrelations should always be reported with seatter diagrams. O A. The scatter diagram is needed to determine if the correlation is positive or negative. O B. The scatter diagram can be used to distinguish between assooiation and causation. OC. The scatser diagram is needed to see f the correlation coecient is being affected by the presence of outiers
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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