Question

Use the following scenario to respond to items 10 and 11 : The Garavan Insthute collected data en different hocmone levels for patents with thyroid disease. The data prowided are the TT 4 levels and FTi levels for indhiduai patients. Cick the liek belaw 10 douniload the data in Crunchiti Coufichin Create a scatterplot of the FTt levels by the TT levels. Dased on the scafterplot. what words can be used to fein the blanks: The direction of the scatherplot is The form and strength of the asseciation between the TTd levels and FTI laverls of patients is A poskive, inoderately strong linest B. poskive; whak Inear C. negative: weak inear D. poskive, strong norilhad E. negatlve; stiong nsolnear F. negatve; moderately steong Enear QUESTION 11 Use Cruncllit is calculate the correlaties cseffient. What is the value of th (Pound your anseer is 3 plates afler the decimal)

Answer 1

To analyze the relationship between TT4 and FTI levels in patients with thyroid disease, draw a scatter plot with TT4 as the independent variable and FTI as the dependent variable, calculate the least-squares line, assess the line's fit, and compute the correlation coefficient to determine the strength and direction of the relationship.

Step-by-step explanation:

To analyze the relationship between two variables, you first need to determine which variable should be the independent variable and which should be the dependent variable. For hormone levels and patients with thyroid disease, TT4 levels can be considered independent, and FTI levels the dependent variable.

To visualize the relationship, you draw a scatter plot of the data. Inspection of the scatter plot can indicate whether there is a relationship—points that cluster in a discernable pattern suggest a correlation.

The least-squares line can be calculated from the data points, providing an equation in the form ý = a + bx. Plotting this line on the scatter plot helps assess if a linear model fits the data well.

The correlation coefficient quantifies the strength and direction of the relationship between the variables. A significant coefficient implies a reliable relationship that is not due to random chance. The scatter plot provides additional context, such as the presence of outliers or if a non-linear model, like a curve, might be more appropriate.