Chapter 2 data analysis - practical
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DATA ANALYSIS - PRACTICAL
Analysis of Variance (ANOVA) using SPSS 14 Computer programme
Prof Dr. Md. Ruhul Amin
Problem No. 1
Litter weight(kg) in first kidding in three different breeds of goats were as follows. Performing ANOVA, test whether any difference exists among the breeds. Compare each pair of means. Jamnapari 3.1 4.2 5.2 4.8 4.0 3.9 4.2 4.6 3.5 3.8
Kambing katjang
2.2 1.9 2.0 2.1 2.0 1.5 2.2 2.3 1.5
Sirohi 2.3 2.0 2.5 3.8 2.7 2.8 2.6 2.5 2.9
ANOVA….
1. Go to SPSS 14 spread sheet2. Click on the Variable view at the bottom3. Define each of your variables i)Breed: label =3 ii) Breed: 1=jam, 2=kam, 3=sir (values) iii) Litter wt. iv) For typing data go to Data view sheet
SPSS spread sheet
Typing databreed Lwt
jam 3.1
jam 4.2
… …
kam 2.2
kam 1.9
… ….
sir 2.3
sir 2.0
… …
Data file
Analysis…
1. Go to “Analyze” button2. Select “compare means”3. Select “One-way ANOVA”4. Bring lwt as dependent variable5. Select “Post hoc”6. Click “OK”
ANOVA
Sum of squares
df Means squares
F Sig.
Between groups
23.172 2 11.586 49.084 .000
Within groups 5.901 25 .236
Total 29.072 27
ANOVA
Value of F is significant (p<0.001)There is significant difference (p<0.001) between
litter wt. of goats in 3 different breeds.
Post hoc Test (Duncan’s test)
LwtDuncan a,b
3 N Subset for alpha = .o51 2 3
kam 9 1.9667
sir 9 2.7000
jam 10 4.1300
sig 1.000 1.000 1.000 1.000
Kam 1.97c
Sir 2.70b
Jam 4.13a
Interpretation of post hoc test
Significantly (p<0.05) highest lwt. was observed in Jamnapari, lowest was in Kambing Katjang and the Sirohi ranked intermediate.
Interaction effect
Suppose records on litter weight of goats shown in Problem 1 were obtained randomly from 3 flock located on 3 states of Malaysia. Obviously “FLOCK” may have an effect like “BREED”. Again different combination of BREEDxFLOCK may behave differently. This is called interaction effect. Total no. of interaction will be 3x3 = 9.
Data file for 2-way (breedxherd) analysis
Two-way ANOVASV SS df MS F
Between breedsBetween flocks
BreedxFlock
Total
F value for interaction effect