Checking validity for the model “peso.altura.lm” by way of standardised residuals, leverages, and Cook's distances

Prepared by BrailleR

Basic summary measures

Counts

12 values in all, made up of 12 unique values, 12 observed, and 0 missing values.

Measures of location

Data	all	5% trimmed	10% trimmed
Mean	0.0323199	0.0323199	0.0323199

Quantiles

	Quantile	Value
0%	Minimum	-1.3726
25%	Lower Quartile	-0.8200
50%	Median	-0.2133
75%	Upper Quartile	0.5739
100%	Maximum	2.3101

Measures of spread

Measure	IQR	Standard deviation	Variance
Value	1.3939319	1.1063873	1.2240928

Basic univariate graphs

Histogram

The histogram

This is a histogram, with the title: Histogram of Residuals
"Residuals" is marked on the x-axis.
Tick marks for the x-axis are at: -2, -1, 0, 1, 2, and 3 
There are a total of 12 elements for this variable.
Tick marks for the y-axis are at: 0, 1, 2, 3, 4, and 5 
It has 5 bins with equal widths, starting at -2 and ending at 3 .
The mids and counts for the bins are:
mid = -1.5  count = 2 
mid = -0.5  count = 5 
mid = 0.5  count = 2 
mid = 1.5  count = 2 
mid = 2.5  count = 1

Boxplot

The boxplot

This graph has a boxplot printed horizontally
with the title: 
"" appears on the x-axis.
"" appears on the y-axis.
Tick marks for the x-axis are at: -1, 0, 1, and 2 
This variable  has 12 values.
There are no outliers marked for this variable 
The whiskers extend to -1.372594 and 2.310133 from the ends of the box, 
which are at -0.8422101 and 0.7534516 
The median, -0.2133455 is 39 % from the left end of the box to the right end.
The right whisker is 2.94 times the length of the left whisker.

Assessing normality

Formal tests for normality

	Statistic	P Value
Shapiro-Wilk	0.9377	0.4683
Anderson-Darling	0.3299	0.4589
Cramer-von Mises	0.0549	0.4115
Lilliefors (Kolmogorov-Smirnov)	0.1673	0.4665
Pearson chi-square	3.0000	0.3916
Shapiro-Francia	0.9416	0.4385

Normality plot

The normality plot

Formal tests of moments

	Statistic	Z	P Value
D'Agostino skewness	0.6938	1.279	0.201
Anscombe-Glynn kurtosis	2.5686	0.256	0.798

Regression diagnostic plots

Standardised residuals

Standardised residuals plotted against fitted values

    1 2 3 4 Sum
4   2 1 0 0   3
3   0 0 1 1   2
2   0 2 0 1   3
1   3 1 0 0   4
Sum 5 4 1 2  12

Standardised residuals plotted against order

    1 2 3 4 Sum
4   1 1 0 1   3
3   1 0 1 0   2
2   0 1 2 0   3
1   1 1 0 2   4
Sum 3 3 3 3  12

standardised residuals plotted against lagged residuals

    1 2 3 4 Sum
4   2 0 0 0   2
3   0 1 0 1   2
2   1 1 1 1   4
1   0 2 0 1   3
Sum 3 4 1 3  11

The lag 1 autocorrelation of the standardised residuals is -0.3628521.

Influence

Standardised residuals plotted against leverages

    1 2 3 4 Sum
4   3 0 0 0   3
3   1 0 0 1   2
2   2 1 0 0   3
1   3 0 1 0   4
Sum 9 1 1 1  12

1 points have excessive leverage. 0 points have Cook's distances greater than one.

Outliers and influential observations

	peso	altura	Fit	St.residual	Leverage	Cooks.distance
2	92	196	91.67509	0.0737318	0.4368231	0.0023412
6	78	169	67.99539	2.3101333	0.1340349	0.2880791