Antiochos XIII

Founded 5-Sep-2004
Last update 5-Sep-2004

Antioch Mint References


Antioch Mint

1. Examined type

Denomination: AR Tetradrachm
Period: 69 - 64 BC
Obverse: Diademed head of Antiochos XIII right; fillet border
Reverse: ‘ΒΑΣΙΛΕΩΣ ΑΝΤΙΟΧΟΥ’ right, ‘ΦΙΛΟΠΑΤΟΡΟΣ’ left; Zeus Nikephoros seated on throne left holding Nike in right hand and scepter in left hand; ‘ΔΙ’ monogram under throne; all within laurel wreath

2. Acceptable weight range

Lower exclusion limit: 14.50 grams
Upper exclusion limit: 16.50 grams

Each coin is a priori excluded from the data sample if its weight is lesser than the lower exclusion limit or greater than the upper exclusion limit.

3. Data

Sorted data (weights in grams):
14.79, 15.10, 15.17, 15.23, 15.25, 15.33, 15.33, 15.35, 15.35, 15.43, 15.46, 15.52, 15.54, 15.59

Note: The following coins were included into the analysis:

  • Classical Numismatic Group, Inc.: Auction 63 (May 2003), Lot No. 665; Triton VII (Jan 2004), Lot No. 354; Auction 66 (May 2004), Lots No. 697, 698 and 699
  • Fritz Rudolf Künker Müzenhandlung: Auction 94 (Sep 2004), Lot No. 1436
  • Gorny & Mosch Giessener Münzhandlung: Auction 117 (Oct 2002), Lot No. 329; Auction 125 (Oct 2003), Lot No. 255; Auction 126 (Oct 2003), Lot No. 1445; Auction 130 (Mar 2004), Lot No. 1297; Auction 134 (Oct 2004), Lots No. 1567 and 1568
  • Jean Elsen s.a.: Auction 76 (Sep 2003), Lot No. 186
  • Sylloge Nummorum Graecorum: Vol. VII 1364 Manchester University Museum (SNG_0700_1364)

4. Descriptive statistics

No. of observations: 14  
Mean: 15.32 (95% confidence interval: 15.20 ≤ mean ≤ 15.44)
Standard deviation: 0.21  
Interquartile range: 0.23  
Skewness: -1.04  
Kurtosis: 4.03  
Minimum: 14.79  
25th percentile: 15.23 (94.4% confidence interval: 14.79 ≤ 25th percentile ≤ 15.33)
Median: 15.34 (94.3% confidence interval: 15.23 ≤ median ≤ 15.46)
75th percentile: 15.46 (94.4% confidence interval: 15.35 ≤ 75th percentile ≤ 15.59)
Maximum: 15.59  

Notes: The unbiased estimation of the variance was used for the computation of the standard deviation (i.e. the number of observations minus one was used as a divisor). The sample skewness was computed without sample corrections (i.e. the skewness was computed as the square root of the number of observations times the sum of the third powers of deviations from the mean divided by the 3/2 power of the sum of the squares of deviations from the mean). Similarly, the sample kurtosis was computed as the number of observations times the sum of the fourth powers of deviations from the mean divided by the second power of the sum of the squares of deviations from the mean.

The confidence interval for mean was computed by using the Student t-distribution. The confidence intervals for median and percentiles were computed nonparametrically by using the binomial distribution (see, e.g., Conover, Practical Nonparametric Statistics, pp. 143 - 148).

5. Estimation of proportion of coins with weights within the observed range

At the 95% level of confidence, at least 70.3% of issued coins of the examined type have a weight between the smallest observation and the largest observation, i.e. between 14.79 g and 15.59 g, and at least 53.4% of issued coins of the examined type have a weight between the second smallest observation and the second largest observation, i.e. between 15.10 g and 15.54 g.

Note: These estimations are computed as tolerance limits based on the binomial distribution. See, e.g., Conover, Practical Nonparametric Statistics, pp. 150 - 155.

6. Histogram and probability density function

Histogram of the sample is presented in Figure 1. Kernel estimations of the probability density function are shown in Figure 2 (two kernel estimations were used: Epanechnikov kernel with a bandwidth of 0.113 and Gaussian kernel with a bandwidth of 0.091). The dotted curve in Figure 2 is a probability density function of a normal distribution estimated by the maximum likelihood method.

Note: The bandwidth of the Gaussian kernel was computed as hGauss = 0.9 × min(σ, SIQR) × n-1/5, where σ is the standard deviation, SIQR is the standardised interquartile range (i.e. the interquartile range of the data sample divided by the interquartile range of the standard normal density) and n is the number of observations; see Silverman, Density Estimation for Statistics and Data Analysis, p. 48, formula (3.31). The bandwidth of the Epanechnikov kernel was chosen subjectively in the range from 0.75×hGauss to 1.25×hGauss.

Fig. 1: Histogram

Fig. 1: Histogram

Fig. 2: Probability density estimations

Fig. 2: Probability density estimations

7. Test of normality

The Lilliefors test of normality was used. The test statistic of 0.168 is less than the cutoff value of 0.227 for a 95% level test. Thus we cannot reject the hypothesis of normality at the 95% level of significance. Normal probability plot of the sample is presented in Figure 3.

Fig. 3: Normal probability plot

Fig. 3: Normal probability plot

 


References:

Conover, W. J.:Practical Nonparametric Statistics, Third Edition. John Wiley & Sons, Inc., New York - Chichester - Weinheim - Brisbane - Singapore - Toronto, 1999.
Silverman, B.W.:Density Estimation for Statistics and Data Analysis. Chapman and Hall, London - New York - Tokyo - Melbourne - Madras, 1993 (reprint of the first edition published in 1986).