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Observational units response variable type

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Observational units: Response variable: Type:

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Chance/Rossman, 2015 ISCAM III Investigation 5.6 355 (b) Open the CatJumping.txt data file and produce numerical and graphical summaries of the takeoff velocity variable. Describe the distribution of takeoff velocities in this sample (shape, center, variability, unusual observations). (c) Based on your analysis in (b), if you were going to randomly select a domestic cat, what is your best prediction of its takeoff velocity? (d) Do you think there will be a relationship between a cat’s take off velocity and its body mass? If so, do you think heavier cats will tend to have larger or smaller takeoff velocities than lighter cats? We will need a new graphical summary to visually explore the relationship between two quantitative variables, the scatterplot . Technology Detour Scatterplots In R > plot(bodymass, velocity) or > plot(velocity~bodymass) > scatterplot(bodymass, velocity) the scatterplot function is in the package car In Minitab x Choose Graph > Scatterplot , with the Simple option. Click OK . x Double click on velocity to enter this as the Y variable and then double click on bodymass to enter this as the X variable. x Click OK . x [Or type MTB> plot 'velocity'*'bodymass' ] (e) Describe the relationship between a cat’s takeoff velocity and its body mass, as displayed in this scatterplot. Does this pattern confirm your expectation in (d)?
Chance/Rossman, 2015 ISCAM III Investigation 5.6 356 (f) Do any of these cats appear to be outliers in the sense that its pair of values (body mass, takeoff velocity) does not fit the pattern of the majority of cats? If so, identify the ID for that cat and describe what’s different about this cat (in context). Terminology Detour Scatterplots are useful for displaying the relationship between two quantitative variables. If one variable has been defined as the response variable and the other as the explanatory variable, we will put the response variable on the vertical axis and the explanatory variable along the horizontal axis. In describing scatterplots you will describe the overall pattern between the two variables focusing primarily on three things: x Direction : Is there a positive association (small values of y tend to occur with small values of x and large values of y tend to occur with large values of x ) or a negative association (small values of y tend to occur at large values of x and vice versa)? x Linearity : Is the overall pattern in the scatterplot linear or not? x Strength : How closely are the observations following the observed pattern? The above scatterplot reveals a fairly strong, negative association between body mass and takeoff velocity, meaning that heavier cats tend to have a smaller takeoff velocity than larger cats. The relationship is somewhat linear but has a bit of a curved pattern. There is one outlier cat (cat C) with a very high takeoff velocity despite having a very large body mass.

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