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ONE WAYANOVA
WHAT IS ANOVA?
ANALYSIS OF VARIANCE ABBREVIATED ASANOVA
STATISTICAL TECHNIQUE
DEVELOPED BY R.A. FISHER
USED IN THE AREAS OF BUSINESS,INDUSTRIES,ECONOMICS,PSYCHOLOGY,ETC
PREFERRED WHEN THERE IS MORE THAN ONE SAMPLE
STATISTICAL TECHNIQUE USED TO MEASURE THE MEANS OF TWO VARIABLES
IT INVOLVES ONE INDEPENDENT VARIABLE AND ONE DEPENDENT VARIABLE
What does this test do?
The one-way ANOVA compares the means between the groups you are
interested in and determines whether any of those means are statistically
significantly different from each other. Specifically, it tests the null
hypothesis:
where µ = group mean and k = number of groups. If, however, the one-way
ANOVA returns a statistically significant result, we accept the alternative
hypothesis (HA), which is that there are at least two group means that are
statistically significantly different from each other.
ASSUMPTIONS
1) The values in each group are normally distributed.
2) The variance within each group should be equal for all groups.
3) The error (variation of each value around its own group mean) should be
independent for each value.
STEPS TO CARRY OUT THE TEST
1. STATE NULL AND ALTERNATIVE HYPOTHESIS
H0 : all sample means are equal
At least one sample has different mean
H0  1  2...  i
H1  not all of thei are
equal
2. STATE ALPHA
 = 0.05
3.CALCULATE DEGREE OF FREEDOM
K-1 & n-1
k= No of Samples,
n= Total No of observations
4. STATE DECISION RULE
If calculated value of F > table value of F
,reject Ho
5. CALCULATE TEST STATISTIC
-Calculate variance between samples
-Calculate variance within the samples
-Calculate F statistic
-If F is significant perform post hoc test
6. STATE RESULTS AND CONCLUSION
X1 (X1) 2 X2 (X2 )2 X3 (X3 )2
10 100 9 81 14 196
10 100 5 25 9 81
16 256 18 324 13 169
9 81 4 16 14 196
15 225 6 36 5 25
Total 60 762 42 482 55 667
Total sum of all observations = 60 + 42 + 55 = 157
Correction factor = T2 / N=(157)2 /15= 24649/15=1643.26667
Total sum of squares (SST)= 762 + 482 + 667 – 1643.26667 =
267.73333
Sum of square b/w samples (SSB)=(60)2/5 + (42)2 /5 + (55) 2 /5
– 1643.26667=34.5333
Sum of squares within samples= (SST) – (SSB)
=267.73333 – 34.5333= 233.20003
Formulas for shortcut method
Total sum of all observation = X1 + X2 + X3 + … + Xn
Correction factor = T2 / N
Total sum of squares (SST) = X12 + X22 + X32 + … + Xn2 - T2 / N
Sum of squares between samples (SSB)
= (X1)2 /n1 + (X2)2 /n2 + (X3)2 /n3 + … + (Xn)2 /n - T2 / N
Sum of squares within samples (SSW) = (SST) – (SSB)
ONE WAY ANOVA IN SPSS
Click Analyze > Compare Means > One-Way ANOVA... on the top menu, as shown below.
You will be presented with the One-Way ANOVA dialogue box:
e
Click th Button. Tick the Descriptive checkbox in the –Statistics– area, as shown below:
THANKYOU!

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one way anova.pptx

  • 2. WHAT IS ANOVA? ANALYSIS OF VARIANCE ABBREVIATED ASANOVA STATISTICAL TECHNIQUE DEVELOPED BY R.A. FISHER USED IN THE AREAS OF BUSINESS,INDUSTRIES,ECONOMICS,PSYCHOLOGY,ETC PREFERRED WHEN THERE IS MORE THAN ONE SAMPLE STATISTICAL TECHNIQUE USED TO MEASURE THE MEANS OF TWO VARIABLES IT INVOLVES ONE INDEPENDENT VARIABLE AND ONE DEPENDENT VARIABLE
  • 3.
  • 4. What does this test do? The one-way ANOVA compares the means between the groups you are interested in and determines whether any of those means are statistically significantly different from each other. Specifically, it tests the null hypothesis: where µ = group mean and k = number of groups. If, however, the one-way ANOVA returns a statistically significant result, we accept the alternative hypothesis (HA), which is that there are at least two group means that are statistically significantly different from each other.
  • 5. ASSUMPTIONS 1) The values in each group are normally distributed. 2) The variance within each group should be equal for all groups. 3) The error (variation of each value around its own group mean) should be independent for each value.
  • 6. STEPS TO CARRY OUT THE TEST 1. STATE NULL AND ALTERNATIVE HYPOTHESIS H0 : all sample means are equal At least one sample has different mean H0  1  2...  i H1  not all of thei are equal
  • 7. 2. STATE ALPHA  = 0.05 3.CALCULATE DEGREE OF FREEDOM K-1 & n-1 k= No of Samples, n= Total No of observations
  • 8. 4. STATE DECISION RULE If calculated value of F > table value of F ,reject Ho 5. CALCULATE TEST STATISTIC -Calculate variance between samples -Calculate variance within the samples -Calculate F statistic -If F is significant perform post hoc test 6. STATE RESULTS AND CONCLUSION
  • 9. X1 (X1) 2 X2 (X2 )2 X3 (X3 )2 10 100 9 81 14 196 10 100 5 25 9 81 16 256 18 324 13 169 9 81 4 16 14 196 15 225 6 36 5 25 Total 60 762 42 482 55 667 Total sum of all observations = 60 + 42 + 55 = 157 Correction factor = T2 / N=(157)2 /15= 24649/15=1643.26667 Total sum of squares (SST)= 762 + 482 + 667 – 1643.26667 = 267.73333 Sum of square b/w samples (SSB)=(60)2/5 + (42)2 /5 + (55) 2 /5 – 1643.26667=34.5333 Sum of squares within samples= (SST) – (SSB) =267.73333 – 34.5333= 233.20003
  • 10. Formulas for shortcut method Total sum of all observation = X1 + X2 + X3 + … + Xn Correction factor = T2 / N Total sum of squares (SST) = X12 + X22 + X32 + … + Xn2 - T2 / N Sum of squares between samples (SSB) = (X1)2 /n1 + (X2)2 /n2 + (X3)2 /n3 + … + (Xn)2 /n - T2 / N Sum of squares within samples (SSW) = (SST) – (SSB)
  • 11. ONE WAY ANOVA IN SPSS
  • 12. Click Analyze > Compare Means > One-Way ANOVA... on the top menu, as shown below.
  • 13. You will be presented with the One-Way ANOVA dialogue box:
  • 14.
  • 15.
  • 16. e Click th Button. Tick the Descriptive checkbox in the –Statistics– area, as shown below: