#setwd("C:/Users/Nolan/Documents/USF Assignment Archive/Intro to data science")
#install.packages("ISwR")
library(ISwR)## Warning: package 'ISwR' was built under R version 4.2.2data("cystfibr")
cystfibr## age sex height weight bmp fev1 rv frc tlc pemax
## 1 7 0 109 13.1 68 32 258 183 137 95
## 2 7 1 112 12.9 65 19 449 245 134 85
## 3 8 0 124 14.1 64 22 441 268 147 100
## 4 8 1 125 16.2 67 41 234 146 124 85
## 5 8 0 127 21.5 93 52 202 131 104 95
## 6 9 0 130 17.5 68 44 308 155 118 80
## 7 11 1 139 30.7 89 28 305 179 119 65
## 8 12 1 150 28.4 69 18 369 198 103 110
## 9 12 0 146 25.1 67 24 312 194 128 70
## 10 13 1 155 31.5 68 23 413 225 136 95
## 11 13 0 156 39.9 89 39 206 142 95 110
## 12 14 1 153 42.1 90 26 253 191 121 90
## 13 14 0 160 45.6 93 45 174 139 108 100
## 14 15 1 158 51.2 93 45 158 124 90 80
## 15 16 1 160 35.9 66 31 302 133 101 134
## 16 17 1 153 34.8 70 29 204 118 120 134
## 17 17 0 174 44.7 70 49 187 104 103 165
## 18 17 1 176 60.1 92 29 188 129 130 120
## 19 17 0 171 42.6 69 38 172 130 103 130
## 20 19 1 156 37.2 72 21 216 119 81 85
## 21 19 0 174 54.6 86 37 184 118 101 85
## 22 20 0 178 64.0 86 34 225 148 135 160
## 23 23 0 180 73.8 97 57 171 108 98 165
## 24 23 0 175 51.1 71 33 224 131 113 95
## 25 23 0 179 71.5 95 52 225 127 101 195str(cystfibr)## 'data.frame': 25 obs. of 10 variables:
## $ age : int 7 7 8 8 8 9 11 12 12 13 ...
## $ sex : int 0 1 0 1 0 0 1 1 0 1 ...
## $ height: int 109 112 124 125 127 130 139 150 146 155 ...
## $ weight: num 13.1 12.9 14.1 16.2 21.5 17.5 30.7 28.4 25.1 31.5 ...
## $ bmp : int 68 65 64 67 93 68 89 69 67 68 ...
## $ fev1 : int 32 19 22 41 52 44 28 18 24 23 ...
## $ rv : int 258 449 441 234 202 308 305 369 312 413 ...
## $ frc : int 183 245 268 146 131 155 179 198 194 225 ...
## $ tlc : int 137 134 147 124 104 118 119 103 128 136 ...
## $ pemax : int 95 85 100 85 95 80 65 110 70 95 ...attach(cystfibr)## The following object is masked from package:ISwR:
##
## tlcx <- lm(pemax ~ age + weight + bmp + fev1, data = cystfibr)
summary(x)##
## Call:
## lm(formula = pemax ~ age + weight + bmp + fev1, data = cystfibr)
##
## Residuals:
## Min 1Q Median 3Q Max
## -42.521 -10.885 3.003 15.488 41.767
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 179.2957 61.8855 2.897 0.00891 **
## age -3.4181 3.3086 -1.033 0.31389
## weight 2.6882 1.1727 2.292 0.03287 *
## bmp -2.0657 0.8198 -2.520 0.02036 *
## fev1 1.0882 0.5139 2.117 0.04695 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 23.4 on 20 degrees of freedom
## Multiple R-squared: 0.5918, Adjusted R-squared: 0.5101
## F-statistic: 7.248 on 4 and 20 DF, p-value: 0.0008891anova.x<-anova(x)
anova.x## Analysis of Variance Table
##
## Response: pemax
## Df Sum Sq Mean Sq F value Pr(>F)
## age 1 10098.5 10098.5 18.4385 0.0003538 ***
## weight 1 945.2 945.2 1.7258 0.2038195
## bmp 1 2379.7 2379.7 4.3450 0.0501483 .
## fev1 1 2455.6 2455.6 4.4836 0.0469468 *
## Residuals 20 10953.7 547.7
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(anova.x)## Df Sum Sq Mean Sq F value
## Min. : 1.0 Min. : 945.2 Min. : 547.7 Min. : 1.726
## 1st Qu.: 1.0 1st Qu.: 2379.7 1st Qu.: 945.2 1st Qu.: 3.690
## Median : 1.0 Median : 2455.6 Median : 2379.7 Median : 4.414
## Mean : 4.8 Mean : 5366.5 Mean : 3285.3 Mean : 7.248
## 3rd Qu.: 1.0 3rd Qu.:10098.5 3rd Qu.: 2455.6 3rd Qu.: 7.972
## Max. :20.0 Max. :10953.7 Max. :10098.5 Max. :18.439
## NA's :1
## Pr(>F)
## Min. :0.0003538
## 1st Qu.:0.0352985
## Median :0.0485476
## Mean :0.0753171
## 3rd Qu.:0.0885661
## Max. :0.2038195
## NA's :1Both models shows that there is statistic significance
with the P value being quite a bit under the usual .05 mark.
This gives us significant evidence to then reject the null hypothesis.
DFser<-secher anaSer1 <-lm((log(bwt))~I(log(bpd)), data=DFser) summary(anaSer1)## ## Call: ## lm(formula = (log(bwt)) ~ I(log(bpd)), data = DFser) ## ## Residuals: ## Min 1Q Median 3Q Max ## -0.36478 -0.09725 0.01251 0.07703 0.51154 ## ## Coefficients: ## Estimate Std. Error t value Pr(>|t|) ## (Intercept) -7.0862 0.9062 -7.819 4.35e-12 *** ## I(log(bpd)) 3.3320 0.2017 16.516 < 2e-16 *** ## --- ## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 ## ## Residual standard error: 0.1488 on 105 degrees of freedom ## Multiple R-squared: 0.7221, Adjusted R-squared: 0.7194 ## F-statistic: 272.8 on 1 and 105 DF, p-value: < 2.2e-16anaSer2 <- lm((log(bwt))~I(log(ad)), data=DFser) summary(anaSer2)## ## Call: ## lm(formula = (log(bwt)) ~ I(log(ad)), data = DFser) ## ## Residuals: ## Min 1Q Median 3Q Max ## -0.58560 -0.06609 0.00184 0.07479 0.48435 ## ## Coefficients: ## Estimate Std. Error t value Pr(>|t|) ## (Intercept) -2.4446 0.5103 -4.791 5.49e-06 *** ## I(log(ad)) 2.2365 0.1105 20.238 < 2e-16 *** ## --- ## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 ## ## Residual standard error: 0.1275 on 105 degrees of freedom ## Multiple R-squared: 0.7959, Adjusted R-squared: 0.794 ## F-statistic: 409.6 on 1h and 105 DF, p-value: < 2.2e-16anaSer3 <- lm(log(bwt) ~ I(log(ad)) + I(log(bpd)) , data = DFser) summary(anaSer3)## ## Call: ## lm(formula = log(bwt) ~ I(log(ad)) + I(log(bpd)), data = DFser) ## ## Residuals: ## Min 1Q Median 3Q Max ## -0.35074 -0.06741 -0.00792 0.05750 0.36360 ## ## Coefficients: ## Estimate Std. Error t value Pr(>|t|) ## (Intercept) -5.8615 0.6617 -8.859 2.36e-14 *** ## I(log(ad)) 1.4667 0.1467 9.998 < 2e-16 *** ## I(log(bpd)) 1.5519 0.2294 6.764 8.09e-10 *** ## --- ## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 ## ## Residual standard error: 0.1068 on 104 degrees of freedom ## Multiple R-squared: 0.8583, Adjusted R-squared: 0.8556 ## F-statistic: 314.9 on 2 and 104 DF, p-value: < 2.2e-16
- 1% increase in the abdominal diameter may result in a 1.4667% birth weight increase. 1% increase in the bi-parietal diameter may result in a 1.5519% birth weight increase.
Comments
Post a Comment