Flipped Assingment #11
(“Juan Carlos Soto,Nicholas Rojas,Mason Barret”)
2023-06-20
Descriptive Statistics using R
Problem #1
#1. Consider the following 20 samples drawn from a population:
| 24.7 23.5 14.7 13.4 24.2 | 25.4 12.1 15.0 19.6 22.9 | 21.2 18.4 25.0 14.5 14.2 | 21.8 21.2 15.7 22.6 21.2 | |||||
data <- c(24.7, 23.5, 14.7, 13.4, 24.2, 25.4, 12.1, 15.0, 19.6, 22.9, 21.2, 18.4, 25.0, 14.5, 14.2, 21.8, 21.2, 15.7, 22.6, 21.2)a)Calculate the sample mean
mean_value <- mean(data)
mean_value## [1] 19.565b)Calculate the median
median_value <- median(data)
median_value## [1] 21.2- Calculate the sample variance
var_value <- var(data)
var_value## [1] 19.43397d)Calculate the sample standard deviation
sd_value <- sd(data)
sd_value## [1] 4.408398- Calculate the quartiles
quartiles <- quantile(data, probs = c(0.25, 0.5, 0.75))
quartiles## 25% 50% 75%
## 14.925 21.200 23.050- Draw a histogram with 4 bins (change both the fill and border color)
hist(data, breaks = 4,main="Histogram", col = "lightblue", border = "darkblue")
- Draw a boxplot
boxplot(data,main="Boxplot of 20 samples")
Problem #2
1.Consider a random sample of n=50 resistors from suppliers A and B contained in the datafile
https://raw.githubusercontent.com/tmatis12/datafiles/main/resistors.csv
data2 <- read.csv("https://raw.githubusercontent.com/tmatis12/datafiles/main/resistors.csv")
data2## SupplierA SupplierB
## 1 29.36279 30.62987
## 2 29.51027 29.13114
## 3 29.92811 29.81491
## 4 29.78606 29.46583
## 5 29.15107 29.59829
## 6 30.15748 29.12295
## 7 30.46553 30.13564
## 8 29.85992 29.23834
## 9 29.51514 28.69545
## 10 31.16777 29.46590
## 11 31.44440 29.84616
## 12 30.13799 29.27476
## 13 30.22418 29.89007
## 14 30.40154 30.11324
## 15 28.72853 29.17337
## 16 29.69430 29.87823
## 17 29.57491 30.07623
## 18 29.55289 29.75243
## 19 28.70514 29.29905
## 20 30.59459 29.19695
## 21 29.93642 29.95769
## 22 30.19725 29.50674
## 23 30.61088 29.85518
## 24 29.31532 29.00272
## 25 30.24217 29.21925
## 26 30.33630 29.33216
## 27 30.12932 30.27084
## 28 29.51702 28.85486
## 29 30.55834 29.67763
## 30 30.22333 30.02513
## 31 29.69312 29.58264
## 32 28.95343 30.35831
## 33 29.42375 28.79259
## 34 29.78290 29.59960
## 35 30.29367 28.66135
## 36 29.89087 29.81375
## 37 29.89336 29.23564
## 38 29.65950 30.17648
## 39 30.89342 29.82198
## 40 29.89125 29.44741
## 41 30.42494 29.21079
## 42 30.99763 29.30069
## 43 29.87300 29.26611
## 44 29.17079 29.83650
## 45 30.61960 30.05269
## 46 29.86612 29.66683
## 47 29.50220 28.98090
## 48 30.04817 30.31552
## 49 29.16770 29.58166
## 50 28.91839 29.96312a)Calculate a summary (min, max, quartiles, mean, median) of the descriptive statistics for Supplier A (using the summary() command)
summary(data2$SupplierA)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 28.71 29.52 29.89 29.92 30.28 31.44b)Calculate a histogram of the sample from supplier A (create a unique title and axes label). Does the data "look" Normally distributed?
hist(data2$SupplierA, main = "Histogram of Resistors (Supplier A)", xlab = "Resistance Value",col = "green",border = "yellow")
c)Calculate side by side box plots
boxplot(data2$SupplierA,data2$SupplierB, main = "Box Plot of Resistors by Supplier", names= c("Supplier A","Supplier B"),xlab = "Supplier", ylab = "Resistance Value")
Problem #3
1.Consider a sample of body temperature and heartbeat for n=65 males (1) and females (2) contained in the datafile
https://raw.githubusercontent.com/tmatis12/datafiles/main/normtemp.csv
url <- "https://raw.githubusercontent.com/tmatis12/datafiles/main/normtemp.csv"
data <- read.csv(url)df3<-read.csv('https://raw.githubusercontent.com/tmatis12/datafiles/main/normtemp.csv')
males<-df3[df3$Sex==1,]
males## Temp Sex Beats
## 1 96.3 1 70
## 2 96.7 1 71
## 3 96.9 1 74
## 4 97.0 1 80
## 5 97.1 1 73
## 6 97.1 1 75
## 7 97.1 1 82
## 8 97.2 1 64
## 9 97.3 1 69
## 10 97.4 1 70
## 11 97.4 1 68
## 12 97.4 1 72
## 13 97.4 1 78
## 14 97.5 1 70
## 15 97.5 1 75
## 16 97.6 1 74
## 17 97.6 1 69
## 18 97.6 1 73
## 19 97.7 1 77
## 20 97.8 1 58
## 21 97.8 1 73
## 22 97.8 1 65
## 23 97.8 1 74
## 24 97.9 1 76
## 25 97.9 1 72
## 26 98.0 1 78
## 27 98.0 1 71
## 28 98.0 1 74
## 29 98.0 1 67
## 30 98.0 1 64
## 31 98.0 1 78
## 32 98.1 1 73
## 33 98.1 1 67
## 34 98.2 1 66
## 35 98.2 1 64
## 36 98.2 1 71
## 37 98.2 1 72
## 38 98.3 1 86
## 39 98.3 1 72
## 40 98.4 1 68
## 41 98.4 1 70
## 42 98.4 1 82
## 43 98.4 1 84
## 44 98.5 1 68
## 45 98.5 1 71
## 46 98.6 1 77
## 47 98.6 1 78
## 48 98.6 1 83
## 49 98.6 1 66
## 50 98.6 1 70
## 51 98.6 1 82
## 52 98.7 1 73
## 53 98.7 1 78
## 54 98.8 1 78
## 55 98.8 1 81
## 56 98.8 1 78
## 57 98.9 1 80
## 58 99.0 1 75
## 59 99.0 1 79
## 60 99.0 1 81
## 61 99.1 1 71
## 62 99.2 1 83
## 63 99.3 1 63
## 64 99.4 1 70
## 65 99.5 1 75females<-df3[df3$Sex==2,]
females## Temp Sex Beats
## 66 96.4 2 69
## 67 96.7 2 62
## 68 96.8 2 75
## 69 97.2 2 66
## 70 97.2 2 68
## 71 97.4 2 57
## 72 97.6 2 61
## 73 97.7 2 84
## 74 97.7 2 61
## 75 97.8 2 77
## 76 97.8 2 62
## 77 97.8 2 71
## 78 97.9 2 68
## 79 97.9 2 69
## 80 97.9 2 79
## 81 98.0 2 76
## 82 98.0 2 87
## 83 98.0 2 78
## 84 98.0 2 73
## 85 98.0 2 89
## 86 98.1 2 81
## 87 98.2 2 73
## 88 98.2 2 64
## 89 98.2 2 65
## 90 98.2 2 73
## 91 98.2 2 69
## 92 98.2 2 57
## 93 98.3 2 79
## 94 98.3 2 78
## 95 98.3 2 80
## 96 98.4 2 79
## 97 98.4 2 81
## 98 98.4 2 73
## 99 98.4 2 74
## 100 98.4 2 84
## 101 98.5 2 83
## 102 98.6 2 82
## 103 98.6 2 85
## 104 98.6 2 86
## 105 98.6 2 77
## 106 98.7 2 72
## 107 98.7 2 79
## 108 98.7 2 59
## 109 98.7 2 64
## 110 98.7 2 65
## 111 98.7 2 82
## 112 98.8 2 64
## 113 98.8 2 70
## 114 98.8 2 83
## 115 98.8 2 89
## 116 98.8 2 69
## 117 98.8 2 73
## 118 98.8 2 84
## 119 98.9 2 76
## 120 99.0 2 79
## 121 99.0 2 81
## 122 99.1 2 80
## 123 99.1 2 74
## 124 99.2 2 77
## 125 99.2 2 66
## 126 99.3 2 68
## 127 99.4 2 77
## 128 99.9 2 79
## 129 100.0 2 78
## 130 100.8 2 77a)Calculate a summary of the descriptive statistics of heartbeat and body temperature for both males and females.
summary(males$Temp,males$Beats)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 96.3 97.6 98.1 98.1 98.6 99.5summary(females$Temp,females$Beats)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 96.40 98.00 98.40 98.39 98.80 100.80b)Calculate a histogram of heartbeat for females (create a unique title and axes label, change the color to pink).
hist(females$Beat, main = "Histogram of Heartbeat (Females)", xlab = "Heartbeat", col = "pink")
c)Calculate a histogram of heartbeat for males (create a unique title and axes label, change the color to blue).
hist(males$Beat, main = "Histogram of Heartbeat (Males)", xlab = "Heartbeat", col = "blue")
d)Across both males and females, what is the sample correlation coefficient between heartbeat and body temperature?
cor(df3$Beat, df3$Temp)## [1] 0.2536564