Simple linear regression model-scatter plot


Complete following in regard to footlength and armspan categories of data set:

a. In the region to right, produce the scatterplot of armspan versus footlength data (remember this means footlength runs along horizontal axis as the independent variable and armspan along vertical axis as the dependent variable.) Based on your scatterplot, briefly describe below your thoughts on whether the "visual" trend between individuals' armspan and footlength appears linear, curvilinear, or has no discernable trend at all. 

b. Complete the following:

i) Comprise the trend line's graph and equation on scatterplot created in part a.  Provide the line's equation below and describe in this context what the "x" and "y" variables represent in equation.

ii) Below, explicitly describe the slope of your trend line and discuss what the value of slope signifies in terms of this context. 

c. Find out the value of correlation coefficient for this paired data. Describe what this value tells you and find out if it implies that there is/isn't statistically significant correlation between two variables of armspan and footlength. (Recall the need to employ table A:6 from text in answering the last portion of this question.)

d. Using predicition equation from part bi. above, predict armspan of individual whose footlength is 26.5 cm.

e. Finally, critique statement "since the correlation coefficient is statistically significant" then this means that "having large foot causes one to have long armspan,"  Specifically, address issue of "causation" in relation to significant statistical correlation.

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Basic Statistics: Simple linear regression model-scatter plot
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