library(readxl)
Statistic_analyse_final_result <- read_excel("C:/Users/Admin/Desktop/Statistic analyse final result.xlsx",
sheet = "Treated data", range = "A1:I14", col_types = c("text",
"text", "numeric", "numeric", "numeric",
"numeric", "numeric", "numeric",
"numeric"))
attach(Statistic_analyse_final_result)
Production
Production=t.test(Statistic_analyse_final_result$`Production (kg)` ~ Statistic_analyse_final_result$Vaccination, data = Statistic_analyse_final_result, var.equal=TRUE)
Production
##
## Two Sample t-test
##
## data: Statistic_analyse_final_result$`Production (kg)` by Statistic_analyse_final_result$Vaccination
## t = -2.4771, df = 11, p-value = 0.03073
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -111241.713 -6564.843
## sample estimates:
## mean in group Control mean in group Vaccinated
## 297374.5 356277.8
FCR
FCR=t.test(Statistic_analyse_final_result$`FCR (regardless of seeds)` ~ Statistic_analyse_final_result$Vaccination, data = Statistic_analyse_final_result, var.equal=TRUE)
FCR
##
## Two Sample t-test
##
## data: Statistic_analyse_final_result$`FCR (regardless of seeds)` by Statistic_analyse_final_result$Vaccination
## t = 0.39944, df = 11, p-value = 0.6972
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.05136644 0.07414422
## sample estimates:
## mean in group Control mean in group Vaccinated
## 1.552500 1.541111
Culture period
Period=t.test(Statistic_analyse_final_result$`Culture period (day)` ~ Statistic_analyse_final_result$Vaccination, data = Statistic_analyse_final_result, var.equal=TRUE)
Period
##
## Two Sample t-test
##
## data: Statistic_analyse_final_result$`Culture period (day)` by Statistic_analyse_final_result$Vaccination
## t = 2.0926, df = 11, p-value = 0.06037
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -1.922983 76.145205
## sample estimates:
## mean in group Control mean in group Vaccinated
## 356.0000 318.8889
Survival rate
SR=t.test(Statistic_analyse_final_result$`Survival rate (%) (included unexplainable deads)` ~ Statistic_analyse_final_result$Vaccination, data = Statistic_analyse_final_result, var.equal=TRUE)
SR
##
## Two Sample t-test
##
## data: Statistic_analyse_final_result$`Survival rate (%) (included unexplainable deads)` by Statistic_analyse_final_result$Vaccination
## t = -2.1386, df = 11, p-value = 0.05574
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.215315390 0.003093168
## sample estimates:
## mean in group Control mean in group Vaccinated
## 0.5150000 0.6211111
Size 700-900g
Size_700 =t.test(Statistic_analyse_final_result$`Fish size (%) (700-900g)` ~ Statistic_analyse_final_result$Vaccination, data = Statistic_analyse_final_result, var.equal=TRUE)
Size_700
##
## Two Sample t-test
##
## data: Statistic_analyse_final_result$`Fish size (%) (700-900g)` by Statistic_analyse_final_result$Vaccination
## t = -1.9454, df = 10, p-value = 0.08036
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.116800887 0.007911998
## sample estimates:
## mean in group Control mean in group Vaccinated
## 0.1733333 0.2277778
Size 900-1200g
Size_900 =t.test(Statistic_analyse_final_result$`Fish size (%) (900-1200g)` ~ Statistic_analyse_final_result$Vaccination, data = Statistic_analyse_final_result, var.equal=TRUE)
Size_900
##
## Two Sample t-test
##
## data: Statistic_analyse_final_result$`Fish size (%) (900-1200g)` by Statistic_analyse_final_result$Vaccination
## t = -1.4371, df = 10, p-value = 0.1812
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.1558632 0.0336410
## sample estimates:
## mean in group Control mean in group Vaccinated
## 0.1600000 0.2211111
Size 700-1200g
Size_900 =t.test(Statistic_analyse_final_result$`Fish size (%) (700-1200g)` ~ Statistic_analyse_final_result$Vaccination, data = Statistic_analyse_final_result, var.equal=TRUE)
Size_900
##
## Two Sample t-test
##
## data: Statistic_analyse_final_result$`Fish size (%) (700-1200g)` by Statistic_analyse_final_result$Vaccination
## t = -1.7585, df = 10, p-value = 0.1092
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.26197030 0.03085919
## sample estimates:
## mean in group Control mean in group Vaccinated
## 0.3333333 0.4488889
Analysis of Linear regression
Production
production=lm(Statistic_analyse_final_result$`Production (kg)`~Statistic_analyse_final_result$Vaccination)
summary(production)
##
## Call:
## lm(formula = Statistic_analyse_final_result$`Production (kg)` ~
## Statistic_analyse_final_result$Vaccination)
##
## Residuals:
## Min 1Q Median 3Q Max
## -78060 -9915 -2878 10244 76744
##
## Coefficients:
## Estimate Std. Error
## (Intercept) 297375 19786
## Statistic_analyse_final_result$VaccinationVaccinated 58903 23780
## t value Pr(>|t|)
## (Intercept) 15.030 1.12e-08 ***
## Statistic_analyse_final_result$VaccinationVaccinated 2.477 0.0307 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 39570 on 11 degrees of freedom
## Multiple R-squared: 0.3581, Adjusted R-squared: 0.2997
## F-statistic: 6.136 on 1 and 11 DF, p-value: 0.03073
(confint(production)[,2]-confint(production)[,1])/2
## (Intercept)
## 43548.21
## Statistic_analyse_final_result$VaccinationVaccinated
## 52338.43
FCR
fcr=lm(Statistic_analyse_final_result$`FCR (regardless of seeds)`~Statistic_analyse_final_result$Vaccination)
summary(fcr)
##
## Call:
## lm(formula = Statistic_analyse_final_result$`FCR (regardless of seeds)` ~
## Statistic_analyse_final_result$Vaccination)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.06111 -0.02250 -0.01111 0.01889 0.09889
##
## Coefficients:
## Estimate Std. Error
## (Intercept) 1.55250 0.02372
## Statistic_analyse_final_result$VaccinationVaccinated -0.01139 0.02851
## t value Pr(>|t|)
## (Intercept) 65.441 1.32e-15 ***
## Statistic_analyse_final_result$VaccinationVaccinated -0.399 0.697
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.04745 on 11 degrees of freedom
## Multiple R-squared: 0.0143, Adjusted R-squared: -0.07531
## F-statistic: 0.1595 on 1 and 11 DF, p-value: 0.6972
(confint(fcr)[,2]-confint(fcr)[,1])/2
## (Intercept)
## 0.05221559
## Statistic_analyse_final_result$VaccinationVaccinated
## 0.06275533
Culture periods
day=lm(Statistic_analyse_final_result$`Culture period (day)`~Statistic_analyse_final_result$Vaccination)
summary(day)
##
## Call:
## lm(formula = Statistic_analyse_final_result$`Culture period (day)` ~
## Statistic_analyse_final_result$Vaccination)
##
## Residuals:
## Min 1Q Median 3Q Max
## -54.889 -11.000 3.111 9.000 53.111
##
## Coefficients:
## Estimate Std. Error
## (Intercept) 356.00 14.76
## Statistic_analyse_final_result$VaccinationVaccinated -37.11 17.73
## t value Pr(>|t|)
## (Intercept) 24.125 7.09e-11 ***
## Statistic_analyse_final_result$VaccinationVaccinated -2.093 0.0604 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 29.51 on 11 degrees of freedom
## Multiple R-squared: 0.2847, Adjusted R-squared: 0.2197
## F-statistic: 4.379 on 1 and 11 DF, p-value: 0.06037
(confint(day)[,2]-confint(day)[,1])/2
## (Intercept)
## 32.47833
## Statistic_analyse_final_result$VaccinationVaccinated
## 39.03409
Survival rate
SR=lm(Statistic_analyse_final_result$`Survival rate (%) (included unexplainable deads)`~Statistic_analyse_final_result$Vaccination)
summary(SR)
##
## Call:
## lm(formula = Statistic_analyse_final_result$`Survival rate (%) (included unexplainable deads)` ~
## Statistic_analyse_final_result$Vaccination)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.11500 -0.05500 0.01889 0.07500 0.10889
##
## Coefficients:
## Estimate Std. Error
## (Intercept) 0.51500 0.04128
## Statistic_analyse_final_result$VaccinationVaccinated 0.10611 0.04962
## t value Pr(>|t|)
## (Intercept) 12.475 7.8e-08 ***
## Statistic_analyse_final_result$VaccinationVaccinated 2.139 0.0557 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.08257 on 11 degrees of freedom
## Multiple R-squared: 0.2937, Adjusted R-squared: 0.2295
## F-statistic: 4.574 on 1 and 11 DF, p-value: 0.05574
(confint(SR)[,2]-confint(SR)[,1])/2
## (Intercept)
## 0.09086345
## Statistic_analyse_final_result$VaccinationVaccinated
## 0.10920428
Size 700-900
Size1=lm(Statistic_analyse_final_result$`Fish size (%) (700-900g)`~Statistic_analyse_final_result$Vaccination)
summary(Size1)
##
## Call:
## lm(formula = Statistic_analyse_final_result$`Fish size (%) (700-900g)` ~
## Statistic_analyse_final_result$Vaccination)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.057778 -0.029167 0.002222 0.023333 0.082222
##
## Coefficients:
## Estimate Std. Error
## (Intercept) 0.17333 0.02424
## Statistic_analyse_final_result$VaccinationVaccinated 0.05444 0.02799
## t value Pr(>|t|)
## (Intercept) 7.152 3.1e-05 ***
## Statistic_analyse_final_result$VaccinationVaccinated 1.945 0.0804 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.04198 on 10 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.2746, Adjusted R-squared: 0.202
## F-statistic: 3.785 on 1 and 10 DF, p-value: 0.08036
(confint(Size1)[,2]-confint(Size1)[,1])/2
## (Intercept)
## 0.05400226
## Statistic_analyse_final_result$VaccinationVaccinated
## 0.06235644
Size 900-1200
Size2=lm(Statistic_analyse_final_result$`Fish size (%) (900-1200g)`~Statistic_analyse_final_result$Vaccination)
summary(Size2)
##
## Call:
## lm(formula = Statistic_analyse_final_result$`Fish size (%) (900-1200g)` ~
## Statistic_analyse_final_result$Vaccination)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.12111 -0.02361 0.00500 0.04889 0.07889
##
## Coefficients:
## Estimate Std. Error
## (Intercept) 0.16000 0.03683
## Statistic_analyse_final_result$VaccinationVaccinated 0.06111 0.04253
## t value Pr(>|t|)
## (Intercept) 4.345 0.00146 **
## Statistic_analyse_final_result$VaccinationVaccinated 1.437 0.18124
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06379 on 10 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.1712, Adjusted R-squared: 0.08828
## F-statistic: 2.065 on 1 and 10 DF, p-value: 0.1812
(confint(Size2)[,2]-confint(Size2)[,1])/2
## (Intercept)
## 0.08205774
## Statistic_analyse_final_result$VaccinationVaccinated
## 0.09475211
Size 700-1200
Size3=lm(Statistic_analyse_final_result$`Fish size (%) (700-1200g)`~Statistic_analyse_final_result$Vaccination)
summary(Size3)
##
## Call:
## lm(formula = Statistic_analyse_final_result$`Fish size (%) (700-1200g)` ~
## Statistic_analyse_final_result$Vaccination)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.168889 -0.033889 0.003889 0.063611 0.131111
##
## Coefficients:
## Estimate Std. Error
## (Intercept) 0.33333 0.05691
## Statistic_analyse_final_result$VaccinationVaccinated 0.11556 0.06571
## t value Pr(>|t|)
## (Intercept) 5.857 0.00016 ***
## Statistic_analyse_final_result$VaccinationVaccinated 1.759 0.10916
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.09857 on 10 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.2362, Adjusted R-squared: 0.1598
## F-statistic: 3.092 on 1 and 10 DF, p-value: 0.1092
(confint(Size3)[,2]-confint(Size3)[,1])/2
## (Intercept)
## 0.1267989
## Statistic_analyse_final_result$VaccinationVaccinated
## 0.1464147