dataset

Al      Fe    Mg   Ca   Na   Site
14.4 7.00 4.30 0.15 0.51 L
13.8 7.08 3.43 0.12 0.17 L
14.6 7.09 3.88 0.13 0.20 L
11.5 6.37 5.64 0.16 0.14 L
13.8 7.06 5.34 0.20 0.20 L
10.9 6.26 3.47 0.17 0.22 L
10.1 4.26 4.26 0.20 0.18 L
11.6 5.78 5.91 0.18 0.16 L
11.1 5.49 4.52 0.29 0.30 L
13.4 6.92 7.23 0.28 0.20 L
12.4 6.13 5.69 0.22 0.54 L
13.1 6.64 5.51 0.31 0.24 L
12.7 6.69 4.45 0.20 0.22 L
12.5 6.44 3.94 0.22 0.23 L
11.8 5.44 3.94 0.30 0.04 C
11.6 5.39 3.77 0.29 0.06 C
18.3 1.28 0.67 0.03 0.03 I
15.8 2.39 0.63 0.01 0.04 I
18.0 1.50 0.67 0.01 0.06 I
18.0 1.88 0.68 0.01 0.04 I
20.8 1.51 0.72 0.07 0.10 I
17.7 1.12 0.56 0.06 0.06 A
18.3 1.14 0.67 0.06 0.05 A
16.7 0.92 0.53 0.01 0.05 A
14.8 2.74 0.67 0.03 0.05 A
19.1 1.64 0.60 0.10 0.03 A

Transcribed Image Text:

4. Romano-British Pottery. Samples from Romano-British pottery were taken at four sites in the United Kingdom. The dataset is available on Canvas at pottery.dat. Twenty-six samples of Romano-British pottery were found at four different kiln sites in Wales, Gwent and the New Forest. The sites are Llanederyn (L), Caldicot (C), Island Thorns (I), and Ashley Rails (A). The other variables are the percentage of oxides of various metals measured by atomic absorption spectro-photometry. The data were collected to see if different sites contained pottery of different chemical compositions. A chemical analysis of the pottery was performed to measure the percentage of five metal oxides present in each sample. 1. Al: Percentage of aluminum oxide in sample 2. Fe: Percentage of iron oxide in sample 3. Mg: Percentage of magnesium oxide in sample 4. Ca: Percentage of calcium oxide in sample 5. Na: Percentage of sodium oxide in sample 6. Site: Site where pottery sample was collected (a) Read in the dataset into R. [2 points] (b) For each site, provide summaries of chemical content using means, medians, standard deviations and in- terquartile ranges (if applicable). [8 points] (c) Use the function boxplot to provide boxplot displays of the site-wise composition of each chemical. Hand in these plots, all on one page. (To do this, use the graphical function par before plotting. The function > par (mfrow=c(2,3)) divides the plotting region into 2 rows and three columns. Thus, successive calls to a plot would fill the region one by one. [10 points] (d) Discuss the characteristics of the distributions of the percentages of different metal oxides, as provided by the above boxplots and summary measures. [2 points] 4. Romano-British Pottery. Samples from Romano-British pottery were taken at four sites in the United Kingdom. The dataset is available on Canvas at pottery.dat. Twenty-six samples of Romano-British pottery were found at four different kiln sites in Wales, Gwent and the New Forest. The sites are Llanederyn (L), Caldicot (C), Island Thorns (I), and Ashley Rails (A). The other variables are the percentage of oxides of various metals measured by atomic absorption spectro-photometry. The data were collected to see if different sites contained pottery of different chemical compositions. A chemical analysis of the pottery was performed to measure the percentage of five metal oxides present in each sample. 1. Al: Percentage of aluminum oxide in sample 2. Fe: Percentage of iron oxide in sample 3. Mg: Percentage of magnesium oxide in sample 4. Ca: Percentage of calcium oxide in sample 5. Na: Percentage of sodium oxide in sample 6. Site: Site where pottery sample was collected (a) Read in the dataset into R. [2 points] (b) For each site, provide summaries of chemical content using means, medians, standard deviations and in- terquartile ranges (if applicable). [8 points] (c) Use the function boxplot to provide boxplot displays of the site-wise composition of each chemical. Hand in these plots, all on one page. (To do this, use the graphical function par before plotting. The function > par (mfrow=c(2,3)) divides the plotting region into 2 rows and three columns. Thus, successive calls to a plot would fill the region one by one. [10 points] (d) Discuss the characteristics of the distributions of the percentages of different metal oxides, as provided by the above boxplots and summary measures. [2 points]

Answer rating: 100% (QA)

a To read in the dataset into R we can use the readtable function as follows b To provide summaries ... View the full answer