Flipped Assignment 11
Emilio Rios Serna & Marquise Crooks
2023-06-20
- 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
- Calculate the sample mean
df<-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)
mean(df)## [1] 19.565- Calculate the median
median(df)## [1] 21.2- Calculate the sample variance
sd(df)^2## [1] 19.43397- Calculate the sample standard deviation
sd(df)## [1] 4.408398- Calculate the quartiles
quantile(df)## 0% 25% 50% 75% 100%
## 12.100 14.925 21.200 23.050 25.400- Draw a histogram with 4 bins (change both the fill and border color)
hist(df,breaks = 4,col = "yellow", border = "blue")
- Draw a boxplot
boxplot(df)
- 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
df2<-read.csv("https://raw.githubusercontent.com/tmatis12/datafiles/main/resistors.csv")
head(df2)## 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- Calculate a summary (min, max, quartiles, mean, median) of the descriptive statistics for Supplier A (using the summary() command)
summary(df2$SupplierA)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 28.71 29.52 29.89 29.92 30.28 31.44- Calculate a histogram of the sample from supplier A (create a unique title and axes label). Does the data “look” Normally distributed?
hist(df2$SupplierA, main = "Histogram of Supplier A", xlab="xlabel", ylabel="frecuency")## Warning in plot.window(xlim, ylim, "", ...): "ylabel" is not a graphical
## parameter## Warning in title(main = main, sub = sub, xlab = xlab, ylab = ylab, ...):
## "ylabel" is not a graphical parameter## Warning in axis(1, ...): "ylabel" is not a graphical parameter## Warning in axis(2, at = yt, ...): "ylabel" is not a graphical parameter
The data looks kind of Normally distributed with that number of bins due to the bell shape and peak at x = 30. c) Calculate side by side box plot
boxplot(df2)
- 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
df3 <- read.csv("https://raw.githubusercontent.com/tmatis12/datafiles/main/normtemp.csv")
df3## 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 75
## 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 77- Calculate a summary of the descriptive statistics of heartbeat and body temperature for both males and females.
summary(df3$Temp)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 96.30 97.80 98.30 98.25 98.70 100.80summary(df3$Beats)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 57.00 69.00 74.00 73.76 79.00 89.00- Calculate a histogram of heartbeat for females (create a unique title and axes label, change the color to pink).
fem<-df3[df3$Sex==2,]
fem## Temp Sex Beats
## 66 96.4 2 69
## 67 96.7 2 62
## 68 96.8 2 75
## 69 97.2 2 66
## 70 97.2 2 68
## 71 97.4 2 57
## 72 97.6 2 61
## 73 97.7 2 84
## 74 97.7 2 61
## 75 97.8 2 77
## 76 97.8 2 62
## 77 97.8 2 71
## 78 97.9 2 68
## 79 97.9 2 69
## 80 97.9 2 79
## 81 98.0 2 76
## 82 98.0 2 87
## 83 98.0 2 78
## 84 98.0 2 73
## 85 98.0 2 89
## 86 98.1 2 81
## 87 98.2 2 73
## 88 98.2 2 64
## 89 98.2 2 65
## 90 98.2 2 73
## 91 98.2 2 69
## 92 98.2 2 57
## 93 98.3 2 79
## 94 98.3 2 78
## 95 98.3 2 80
## 96 98.4 2 79
## 97 98.4 2 81
## 98 98.4 2 73
## 99 98.4 2 74
## 100 98.4 2 84
## 101 98.5 2 83
## 102 98.6 2 82
## 103 98.6 2 85
## 104 98.6 2 86
## 105 98.6 2 77
## 106 98.7 2 72
## 107 98.7 2 79
## 108 98.7 2 59
## 109 98.7 2 64
## 110 98.7 2 65
## 111 98.7 2 82
## 112 98.8 2 64
## 113 98.8 2 70
## 114 98.8 2 83
## 115 98.8 2 89
## 116 98.8 2 69
## 117 98.8 2 73
## 118 98.8 2 84
## 119 98.9 2 76
## 120 99.0 2 79
## 121 99.0 2 81
## 122 99.1 2 80
## 123 99.1 2 74
## 124 99.2 2 77
## 125 99.2 2 66
## 126 99.3 2 68
## 127 99.4 2 77
## 128 99.9 2 79
## 129 100.0 2 78
## 130 100.8 2 77hist(fem$Beats,main = "Histogram of Female Heartbeats", xlab = "Number of beats", ylab="Frecuency", col = "pink")
- Calculate a histogram of heartbeat for males (create a unique title and axes label, change the color to blue).
mal<-df3[df3$Sex==1,]
hist(mal$Beats,main = "Histogram of Male Heartbeats", xlab = "Number of beats", ylab="Frecuency", col = "blue")
- Across both males and females, what is the sample correlation coefficient between heartbeat and body temperature?
cor(df3$Temp,df3$Beats)## [1] 0.2536564