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analysis.txt
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119 lines (80 loc) · 3.25 KB
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Cutlet problem --
Shapiro-Wilk normality test
data: Unit.A
W = 0.96495, p-value = 0.32
Shapiro-Wilk normality test
data: Unit.B
W = 0.97273, p-value = 0.5225
> var.test(Unit.A,Unit.B)
F test to compare two variances
data: Unit.A and Unit.B
F = 0.70536, num df = 34, denom df = 34, p-value = 0.3136
alternative hypothesis: true ratio of variances is not equal to 1
95 percent confidence interval:
0.3560436 1.3974120
sample estimates:
ratio of variances
0.7053649
> t.test(Unit.A,Unit.B,alternative = 'two.sided',correct = TRUE, conf.level = 0.95)
Welch Two Sample t-test
data: Unit.A and Unit.B
t = 0.72287, df = 66.029, p-value = 0.4723
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-0.09654633 0.20613490
sample estimates:
mean of x mean of y
7.019091 6.964297
===================================================================================================================================================
LabTat hypothysis problem
Shapiro-Wilk normality test
data: Laboratory.1
W = 0.99018, p-value = 0.5508
> shapiro.test(Laboratory.2) ## p-value = 0.5508 it is normalized
Shapiro-Wilk normality test
data: Laboratory.2
W = 0.99363, p-value = 0.8637
> shapiro.test(Laboratory.3) ## p-value = 0.5508 it is normalized
Shapiro-Wilk normality test
data: Laboratory.3
W = 0.98863, p-value = 0.4205
> shapiro.test(Laboratory.4) ## p-value = 0.5508 it is normalized
Shapiro-Wilk normality test
data: Laboratory.4
W = 0.99138, p-value = 0.6619
================================================Bartlett test
Bartlett test of homogeneity of variances
data: values by ind
Bartlett's K-squared = 6.0995, df = 3, p-value = 0.1069
================================================aov result
Df Sum Sq Mean Sq F value Pr(>F)
ind 3 79979 26660 118.7 <2e-16 ***
Residuals 476 106905 225
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
===================================================================================================================================================
Buyer ratio problem
Pearson's Chi-squared test
data: BuyerRatio_chop
X-squared = 1.5959, df = 3, p-value = 0.6603
===================================================================================================================================================
Telecall defetive testing
Phillippines Indonesia Malta India
1 271 271 269 280
2 271 271 269 280
3 29 29 20 20
Pearson's Chi-squared test
data: total_result
X-squared = 3.859, df = 3, p-value = 0.2771
===================================================================================================================================================
Fantaloons hypothesis testing
2-sample test for equality of proportions without continuity correction
data: c(113, 167) out of c(400, 400)
X-squared = 16.022, df = 1, p-value = 6.261e-05
alternative hypothesis: two.sided
95 percent confidence interval:
-0.20043811 -0.06956189
sample estimates:
prop 1 prop 2
0.2825 0.4175
===================================================================================================================================================