Q34.7-4ITD.

Question

(a) Use your calculated value of r to calculate the slope (m) and the y-intercept (b) of a regression line for this data set. (b) Graph the regression line for the mean brain volume of hominin species versus the mean age of the species. Be careful to select and label your axes correctly. (c) Plot the data from the table on the same graph that shows the regression line. Does the regression line appear to provide a reasonable fit to the data?

Step-by-Step Solution

Verified
Answer



(a) m=110.89 and  b=1062.00


(b) 




(c) 



1Step 1: Calculation of slope (m) and y-intercept ( b )

The slope (m) is calculated by:  m=rsysx, where r is the coefficient correlation and sx and sy are the standard deviations.

Given:  r=0.407,  sx=1.57 and  sy=427.77.

 

Substituting the values in the equation,

 m=0.407427.771.57m=110.89

 

 

The y-intercept (b) is calculated as  b=y¯-mx¯.

Given,  x¯=-1.63 and  y¯=881.25

Substituting values in the equation,

 b=881.25-[110.89×(-1.63)]b=881.25-(-180.75)b=1062.00

2Step 2: Graphing the regression line

The equation for a straight line between x and y variables is , where m is the slope of the line and b is the y-intercept.

The following data is used to graph the regression line.

Hominin Species

Mean age

(millions of years; xi)

Mean Brain Volume 

(cm2; yi)

 y=mx+b

Ardipithecus ramidus

-4.4

325

574.08

Australopithecusafarensis

-3.4

375

684.94

Homo habilis

-1.9

550

851.31

Homo ergaster

-1.6

850

884.6

Homo erectus

-1.2

1,000

928.93

Homo heidelbergensis

-0.5

1,200

1006.6

Homo neanderthalensis

-0.1

1,400

1050.92

Homo sapiens

0.0

1,350

1062

 

The mean age of the species is an independent variable, so it would be plotted on the x-axis, whereas the mean brain volume is a dependent variable and would be plotted on the y-axis.

3Step 3: Regression line fits the data

The straight line suggests the linear relationship between the two variables analyzed: mean brain volume and the mean age of the hominin species. Thus, the regression line best fits the data because the value of y increases as the value of x increases.