A random sample of 20 observations from iris species versicolor was obtained to determine the association between sepal length (cm) and sepal width (cm). The collected data are presented below: length (x): 7.0 6.4 6.9 5.5 6.5 5.7 6.3 4.9 6.6 5.2 5.0 5.9 6.0 6.1 5.6 6.7 5.6 5.8 6.2 5.6 width (y): 3.2 3.2 3.1 2.3 2.8 2.8 3.3 2.4 2.9 2.7 2.0 3.0 2.2 2.9 2.9 3.1 3.0 2.7 2.2 2.5 a)* Obtain an appropriate graph to display the data. Does a simple linear regression model appear to be an appropriate model? Explain. T = 5.975, j= 2.76, E1 T:Y; = 332.51, 1 o? = 720.93, E1 Y? = 155.06, SSE = 1.66 ri=1 i=1 b) Calculate the least squares estimates for the regression coefficients and provide the fitted regression equation. c) Interpret the estimated regression coefficients.

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Use the Statistical Software R for problems with (*).
A random sample of 20 observations from iris species versicolor was obtained to
determine the association between sepal length (cm) and sepal width (cm). The collected
data are presented below:
length (x): 7.0 6.4 6.9 5.5 6.5 5.7 6.3 4.9 6.6 5.2 5.0 5.9 6.0 6.1 5.6 6.7 5.6 5.8 6.2 5.6
width (y): 3.2 3.2 3.1 2.3 2.8 2.8 3.3 2.4 2.9 2.7 2.0 3.0 2.2 2.9 2.9 3.1 3.0 2.7 2.2 2.5
a)* Obtain an appropriate graph to display the data. Does a simple linear regression model
appear to be an appropriate model? Explain.
I = 5.975, j = 2.76, E-1 T:Yi
155.06, SSE = 1.66
=D1
b) Calculate the least squares estimates for the regression coefficients and
provide the fitted regression equation.
c) Interpret the estimated regression coefficients.
d) Calculate the least squares estimate for o².
Transcribed Image Text:Use the Statistical Software R for problems with (*). A random sample of 20 observations from iris species versicolor was obtained to determine the association between sepal length (cm) and sepal width (cm). The collected data are presented below: length (x): 7.0 6.4 6.9 5.5 6.5 5.7 6.3 4.9 6.6 5.2 5.0 5.9 6.0 6.1 5.6 6.7 5.6 5.8 6.2 5.6 width (y): 3.2 3.2 3.1 2.3 2.8 2.8 3.3 2.4 2.9 2.7 2.0 3.0 2.2 2.9 2.9 3.1 3.0 2.7 2.2 2.5 a)* Obtain an appropriate graph to display the data. Does a simple linear regression model appear to be an appropriate model? Explain. I = 5.975, j = 2.76, E-1 T:Yi 155.06, SSE = 1.66 =D1 b) Calculate the least squares estimates for the regression coefficients and provide the fitted regression equation. c) Interpret the estimated regression coefficients. d) Calculate the least squares estimate for o².
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