Use Minitab for this question. In Minitab, correlation is found under Stat/Basic
ID: 3064395 • Letter: U
Question
Use Minitab for this question. In Minitab, correlation is found under Stat/Basic. Remeber that a Spearman correlation is the correlation of the ranks. To calculate the natural logarithms of the data contained in, say, column 2 and put the results in, say, column 3, do the following. Under Editor, click Enble Commands, then type Let C3 log(C2) at the MTB prompt. Dry weights (Y) of 11 chick embryos ranging in age from 6 to 16 days (X) are given below. 10 11 12 13 14 15 16 Y 0.029 0.052 0.079 0.125 0.181 0.261 0.425 0.738 1.32 1.52 2.893 Determine the value of the Pearson correlation coefficient between Y and X. [2 pt(s)] Submit Answer Tries 0/3 Determine the value of the Spearman correlation coefficient between Y and X [2 pt(s)) Submit Answer Tries 0/3 Compute the values for the slope and intercept of the regression of Y on X. What is [2 pt(s)] Submit Answer Tries 0/3 What is 0? [2 pt(s)] Submit Answer Tries 0/3 Transform the weight data by taking the natural logarithm. Determine the value of the Pearson correlation coefficient between transformed Y and X, [2 pt(s)] Submit AnswerTries 0/3 Determine the value of the Spearman correlation coefficient between transformed Y and X. [2 pt(s)] Submit Answer Tries 0/3 Compute the values for the slope and intercept of the regression of transformed Y on X What is ,? [2 pt(s)] Submit Answer Tries 0/3 What is [2 pt(s)] Submit Answer Tries 0/3 Post Discussion Send FeedbackExplanation / Answer
Minitab Commands-
Welcome to Minitab, press F1 for help.
MTB > Correlation 'x' 'y'.
Correlation: x, y
Pearson correlation of x and y = 0.890
P-Value = 0.000
MTB > let c3=log(c2)
MTB > Correlation 'x' 'y^'.
Correlation: x, y^
Pearson correlation of x and y^ = 0.880
P-Value = 0.000
MTB > Regress;
SUBC> Response 'y';
SUBC> Nodefault;
SUBC> Continuous 'x';
SUBC> Terms x;
SUBC> Constant;
SUBC> Unstandardized;
SUBC> Tmethod;
SUBC> Tcoefficients;
SUBC> Tequation.
Regression Analysis: y versus x
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant -2.992 0.641 -4.67 0.001
x 0.3142 0.0535 5.87 0.000 1.00
Regression Equation
y = -2.992 + 0.3142 x
Slope = 0.3142
Intercept = -2.992
MTB > Regress;
SUBC> Response 'y^';
SUBC> Nodefault;
SUBC> Continuous 'x';
SUBC> Terms x;
SUBC> Constant;
SUBC> Unstandardized;
SUBC> Tmethod;
SUBC> Tcoefficients;
SUBC> Tequation.
Regression Analysis: y^ versus x
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant -7.31 1.12 -6.55 0.000
x 0.5180 0.0932 5.56 0.000 1.00
Regression Equation
y^ = -7.31 + 0.5180 * x
Slope = 0.5180
Intercept = -7.31
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