Question

The table below gives the birth weights in pounds of piglets in 8 randomly selected litters from large number of litters in a state.

Litter

1            2             3              4            5            6             7            8

2.0          3.5          3.3          3.2          2.6          3.1          2.6          2.5

2.8          2.8          1.6          3.3          2.6          2.9          2.2          2.4

3.3          3.2          3.6          3.2          2.9          3.1          2.2          3.0

3.2          3.5          3.1          1.9          2.0          2.5          2.5          1.5

4.4          2.3          3.2          3.3          2.0                        1.2

3.6          2.4          3.3          2.5          2.1                        1.2

1.9          2.0          2.9          3.6

3.3          1.6          3.4          2.8

2.2                        3.2

1.1                        4.2

Create an ANOVA table for this set of data using R and provide the script used

Answer 1

The code and explanation is given below

library (dplyr) ## Warning: package 'dpłyr' was built under R ve rsion 3.5.3 ## Attaching package: 'dplyr' ## The following objects are masked from "package :stats": filter, lag ## The following objects are masked from 'package:base": intersect, setdiff, setequal, union library (tidyr) rawdata <- read.csv ("rawdata.csv", headerT, stringsAsFactorsF) head (rawdata) ##12.0 3.5 ##22.8 2.8 ##33.3 3.2 ##43.2 3.5 ##54.4 2.3 ##63.6 2.4 3.3 3.2 2.6 3.1 2.6 2.5 1.6 3.3 2.6 2.9 2.2 2.4 3.6 3.2 2.93.1 2.2 3.0 3.1 1.9 2.0 2.5 2.5 1.5 3.2 3.3 2.0 1.2 NA NA 3.3 2.5 2.1 1.2 NA NA Transforming the data to be used for anova colnaes (rawdata) <- as.character (c (1:8)) rawdata%>%gather (group, value, 1 : 8 ) %>% filter ( ! is. na (value))->anova-data str (anova data)

Transforming the data to be used for anova colnames (rawdata) <- as.character (c (1:8)) rawdata紗%gather (group, value, 1 : 8) %片filter ( ! is .na (value)) →anova-data str (anova_data) # # ## ' data, frame' : 56 obs. of 2 variables: "1" S value: num 2 2.8 3.3 3.2 4.4 3.61.9 3.3 2.2 1.1 . . . $ group : chr "1" ,"1" "1" head (anova data,10) ## 1 ## 2 ## 3 ## 4 ## 5 ## 6 ## 7 ## 8 ## 9 ## 10 group value 1 2. 1 2.8 1 3.3 1 3.2 1 4.4 1 3.6 1 1.9 1 3.3 1 2.2 1 1.1 Anova model <- aov (value group, data-anova_data) summary (model) Df Sum Sq Mean Sq F value Pr >F) 7 4.317 0.6168 1.175 0.335 ## group ##Residuals 48 25.196 0.5249

Hypotheis Ho: The mean value across the groups is equal H1: The mean value across the groups is not equal We look at the Pvalue of the F test and see that Pvalue 0.3347, which is greater than 0.05, hence we fail to reject the null hypothesis. Conclusion: The mean value across the groups is not equal