Module V: Statistical Techniques – III – All Important Formulas
1. Sampling Theory
Sample Mean & Variance
xˉ=n∑xi,s2=n−11∑(xi−xˉ)2
Standard Error of Mean
SE(xˉ)=n
SE(xˉ)=n
2. Hypothesis Testing – Basic Concepts
- Null Hypothesis: H0
- Alternative Hypothesis: H1
- Level of Significance: α (usually 0.05 or 0.01)
- Critical Region / Rejection Region
- p-value approach: Reject if p-value
Confidence Limits (for mean)
xˉ±Zα/2n
xˉ±tα/2,n−1
3. Tests of Significance
Test for Difference of Means (Large Samples)
Z=n
t-Test (Small Samples)
One-sample t-test
t=s/n
Two-sample t-test (equal variance)
t=sp
where pooled variance
sp2=n
Paired t-test
t=sd/n
F-Test (Equality of Two Variances)
F=s22
Chi-Square Test
Goodness of Fit / Independence
χ2=∑Ei(
Test for Variance
χ2=σ2(n−1)
4. One-Way Analysis of Variance (ANOVA)
Total Sum of Squares
SST=i=1∑kj
Between Sum of Squares
SSB=i=1∑kni
Within Sum of Squares
SSW=SST−SSB
Mean Squares
MSB=k−1SSB,MSW=
F-Statistic
F=MSWMSB∼F(k−
5. Statistical Quality Control (SQC) – Control Charts
Control Charts for Variables
Xˉ-Chart (Process Mean)
UCL=Xˉˉ+A
R-Chart (Process Range)
UCL=D4Rˉ,CL=
(A2, D3, D are control chart constants depending on subgroup size)
Control Charts for Attributes
p-Chart (Fraction Defective)
UCL=pˉ+3
np-Chart (Number Defective)
UCL=npˉ+3
c-Chart (Number of Defects)
UCL=cˉ+3c