16 Does the constant error variance assumption hold Residuals vs Predicted Values The UNIVARIATE Procedure Variable ToddlerWtGain Moments N 122 Sum Weights 122 Mean 16 6467213 Sum Observations 2030 9 Std Deviation 3 44170471 Variance 11 8453313 Skewness 2 8159955 Kurtosis 21 247275 Uncorrected SS 35241 1114 Corrected SS 1433 28509 Coeff Variation 20 6749704 Std Error Mean 0 3115973 Basic Statistical Measures Location Variability Mean 16 64672 Std Deviation 3 44170 Median 16 68500 Variance 11 84533 Mode 15 12000 Range 31 91000 Interquartile Range 3 28000 Note The mode displayed is the smallest of 4 modes with a count of 2 TestsforLocation Mu0 0 Test Statistic p Value Student's t t 53 42383 Pr t Sign M 60 Pr M Signed Rank S 3750 5 Pr S Quantiles(Definition5) Level Quantile 100 Max 23 810 99 23 590 95 22 190 90 20 010 75 Q3 18 430 50 Median 16 685 25 Q1 15 150 10 13 700 5 13 070 1 10 660 0 Min 8 100 Extreme Observations Lowest Highest Value Obs Value Obs 8 10 102 22 58 85 10 66 11 22 75 26 11 83 87 22 99 59 12 59 65 23 59 60 12 61 99 23 81 112 Missing Values Missing Value Count Percent Of All Obs Missing Obs 19 13 48 100 00 Residuals vs Predicted Values The UNIVARIATE Procedure Residuals vs Predicted Values The UNIVARIATE Procedure Fitted Normal Distribution for ToddlerWtGain Parameters for Normal Distribution Parameter Symbol Estimate Mean Mu 16 64672 Std Dev Sigma 3 441705 Goodness of Fit Tests for Normal Distribution Test Statistic p Value Kolmogorov Smirnov D 0 10498252 Pr D Cramer von Mises W Sq 0 36108444 Pr W Sq Anderson Darling A Sq 2 70319046 Pr A Sq Quantiles for Normal Distribution Percent Quantile Observed Estimated 1 0 10 6600 8 64012 5 0 13 0700 10 98562 10 0 13 7000 12 23600 25 0 15 1500 14 32533 50 0 16 6850 16 64672 75 0 18 4300 18 96812 90 0 20 0100 21 05744 95 0 22 1900 22 30782 99 0 23 5900 24 65332 Residuals vs Predicted Values The UNIVARIATE Procedure Residuals vs Predicted Values The UNIVARIATE Procedure Variable residual Missing Values Missing Value Count Percent Of All Obs Missing Obs 2 100 00 100 00 f f f f

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Question: /*16. Does the constant error variance assumption hold? Residuals vs Predicted Values The UNIVARIATE Procedure Variable: ToddlerWtGain Moments N 122 Sum Weights 122 Mean 16.6467213

/*16. Does the constant error variance assumption hold?

Residuals vs Predicted Values

The UNIVARIATE Procedure

Variable: ToddlerWtGain

Moments
N	122	Sum Weights	122
Mean	16.6467213	Sum Observations	2030.9
Std Deviation	3.44170471	Variance	11.8453313
Skewness	-2.8159955	Kurtosis	21.247275
Uncorrected SS	35241.1114	Corrected SS	1433.28509
Coeff Variation	20.6749704	Std Error Mean	0.3115973

Basic Statistical Measures
Location	Variability
Mean	16.64672	Std Deviation	3.44170
Median	16.68500	Variance	11.84533
Mode	15.12000	Range	31.91000
		Interquartile Range	3.28000

Note: The mode displayed is the smallest of 4 modes with a count of 2.

TestsforLocation:Mu0=0
Test	Statistic	p Value
Student's t	t	53.42383	Pr > \|t\|	<.0001>
Sign	M	60	Pr >= \|M\|	<.0001>
Signed Rank	S	3750.5	Pr >= \|S\|	<.0001>

Quantiles(Definition5)
Level	Quantile
100% Max	23.810
99%	23.590
95%	22.190
90%	20.010
75% Q3	18.430
50% Median	16.685
25% Q1	15.150
10%	13.700
5%	13.070
1%	10.660
0% Min	-8.100

Extreme Observations
Lowest	Highest
Value	Obs	Value	Obs
-8.10	102	22.58	85
10.66	11	22.75	26
11.83	87	22.99	59
12.59	65	23.59	60
12.61	99	23.81	112

Missing Values
Missing Value	Count	Percent Of
All Obs	Missing Obs
.	19	13.48	100.00

Residuals vs Predicted Values

The UNIVARIATE Procedure

Residuals vs Predicted Values

The UNIVARIATE Procedure

Fitted Normal Distribution for ToddlerWtGain

Parameters for Normal Distribution
Parameter	Symbol	Estimate
Mean	Mu	16.64672
Std Dev	Sigma	3.441705

Goodness-of-Fit Tests for Normal Distribution
Test	Statistic	p Value
Kolmogorov-Smirnov	D	0.10498252	Pr > D
Cramer-von Mises	W-Sq	0.36108444	Pr > W-Sq
Anderson-Darling	A-Sq	2.70319046	Pr > A-Sq

Quantiles for Normal Distribution
Percent	Quantile
Observed	Estimated
1.0	10.6600	8.64012
5.0	13.0700	10.98562
10.0	13.7000	12.23600
25.0	15.1500	14.32533
50.0	16.6850	16.64672
75.0	18.4300	18.96812
90.0	20.0100	21.05744
95.0	22.1900	22.30782
99.0	23.5900	24.65332

Residuals vs Predicted Values

The UNIVARIATE Procedure

Residuals vs Predicted Values

The UNIVARIATE Procedure

Variable: residual

Missing Values
Missing Value	Count	Percent Of
All Obs	Missing Obs
.	2	100.00	100.00

/*16. Does the constant error variance assumption hold?Residuals vs Predicted Values The

UNIVARIATE ProcedureVariable: ToddlerWtGainMomentsN122Sum Weights122Mean16.6467213Sum Observations2030.9Std Deviation3.44170471Variance11.8453313Skewness-2.8159955Kurtosis21.247275Uncorrected SS35241.1114Corrected SS1433.28509Coeff Variation20.6749704Std Error Mean0.3115973 Basic

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