Correctional Institution - Applied Regression Analysis - Assignment, Exercises of Mathematical Statistics

These are the important key points of Assignment of Applied Regression Analysis are: Correctional Institution, Sociologist, Relationship, Intelligence and Delinquency, Delinquency Index, Formulated, Delinquency Index, Convicted Minors, Scatter Diagram, Regression Line

Typology: Exercises

2012/2013

Uploaded on 01/11/2013

m-alam
m-alam 🇮🇳

4.7

(12)

54 documents

1 / 2

Toggle sidebar

This page cannot be seen from the preview

Don't miss anything!

bg1
1. A sociologist assigned to a correctional institution was interested in studying
the relationship between intelligence and delinquency. A delinquency index
(ranging from 0 to 50) was formulated to account for both the severity and
the frequency of crimes committed, while intelligence was measured by IQ. The
following table displays the delinquency index (DI) and IQ of a sample of 18
convicted minors.
DI 26.2 33.0 17.5 25.25 20.3 31.9 21.1 22.7 10.7
IQ 110 89 102 98 110 98 122 119 120
DI 22.1 18.6 35.5 38.0 30.0 19.7 41.1 39.6 25.15
IQ 92 116 85 73 90 104 82 134 114
(a) Plot a scatter diagram for DI versus IQ. Determine the least-square estimate
of the regression line when DI regressed on IQ. Sketch the estimated line on the
scatter plot.
(b) Notice that the convicted minor with IQ=134 and DI=39.6 appears to be
quite out of place in the data. Determine the least-square estimate of the
regression line when the outlier is removed. Sketch the estimated line on the
scatter plot. By looking at the graph for the fitted line obtained when the
outlier is omitted, Decide whether this outlier has any effect on your estimation
of IQ-DI relationship.
(c) For these data, would you conclude that the delinquency index decreases as
IQ increases?
(d) Is it justifiable to predict DI for IQ=0 from the fitted regression line?(Note
that the delinquency index goes no higher than 50.)
2. The accompanying table gives the dry weights (Y) of 11 chick embryos
ranging in age from 6 to 16 days (X).
Age (X)(days) 6 7 8 9 10 11
Dry Weight (Y) 0.029 0.052 0.079 0.125 0.181 0.261
Age (X)(days) 12 13 14 15 16
Dry Weight (Y) 0.425 0.738 1.13 1.882 2.812
1
Docsity.com
pf2

Partial preview of the text

Download Correctional Institution - Applied Regression Analysis - Assignment and more Exercises Mathematical Statistics in PDF only on Docsity!

  1. A sociologist assigned to a correctional institution was interested in studying the relationship between intelligence and delinquency. A delinquency index (ranging from 0 to 50) was formulated to account for both the severity and the frequency of crimes committed, while intelligence was measured by IQ. The following table displays the delinquency index (DI) and IQ of a sample of 18 convicted minors.

DI 26.2 33.0 17.5 25.25 20.3 31.9 21.1 22.7 10.

IQ 110 89 102 98 110 98 122 119 120

DI 22.1 18.6 35.5 38.0 30.0 19.7 41.1 39.6 25.

IQ 92 116 85 73 90 104 82 134 114

(a) Plot a scatter diagram for DI versus IQ. Determine the least-square estimate of the regression line when DI regressed on IQ. Sketch the estimated line on the scatter plot.

(b) Notice that the convicted minor with IQ=134 and DI=39.6 appears to be quite out of place in the data. Determine the least-square estimate of the regression line when the outlier is removed. Sketch the estimated line on the scatter plot. By looking at the graph for the fitted line obtained when the outlier is omitted, Decide whether this outlier has any effect on your estimation of IQ-DI relationship.

(c) For these data, would you conclude that the delinquency index decreases as IQ increases?

(d) Is it justifiable to predict DI for IQ=0 from the fitted regression line?(Note that the delinquency index goes no higher than 50.)

  1. The accompanying table gives the dry weights (Y ) of 11 chick embryos ranging in age from 6 to 16 days (X).

Age (X)(days) 6 7 8 9 10 11 Dry Weight (Y ) 0.029 0.052 0.079 0.125 0.181 0. Age (X)(days) 12 13 14 15 16 Dry Weight (Y ) 0.425 0.738 1.13 1.882 2.

Docsity.com

(a) Plot a scatter diagram for Y versus X. Describe the relationships between Y and X. State the simple linear regression model when Y regressed on X. Determine the least-square estimate of the regression line. Sketch the estimated line on the scatter plot. Is it appropriate to run a linear regression of Y on X?

(b) Let Y 1 = log 10 (Y ). Repeat part (a) for using Y 1 instead of Y.

(c) Based on your answer to parts (a) and (b), is it more appropriate to run a linear regression of Y on X, or Y 1 on X? Explain.

  1. The following table gives the vapor pressure (Pv ) of water for various tem- peratures.

Temperature (T ) 273 283 293 303 313 323 Vapor Pressure (mm Hg) 4.6 9.2 17.5 31.8 55.3 92. Temperature (T ) 333 343 353 363 373 Vapor Pressure (mm Hg) 149.4 233.7 355.1 525.8 760.

(a) Plot a scatter diagram for Pv versus T. Determine the least-square estimate of the regression line. Does it seem likely that a straight-line model will be adequate?

(b) From physical chemistry the Clausius-Clapeyron equation states that

ln(Pv ) ∝ −

T

Repeat part (a) using the appropriate transformation based on this information.

Docsity.com