
How would Interpret the following data using two sample t-testing if unequal variances? Each of these columns of data represent a different soda bottling line, with the values representing the amount of soda per bottle in ounces. The business question being asked for each of the three comparisons is "do the two bottling lines bottle the same volume of soda on average, bearing in mind that the sample difference that you may observe could just be coincidence."
Need help intrepreting Data using excel :
Change number to 11 decimal places for correct intrepretation of data
t-Test: Two-Sample Assuming Unequal Variances | ||
C7 | C3 | |
20.01679499870 | 20.19595999995 | |
Variance | 0.01032479977 | 0.06511791311 |
Observations | 50.00000000000 | 80.00000000000 |
Hypothesized Mean Difference | 0.00000000000 | |
df | 112.00000000000 | |
t Stat | 5.60858201974 | |
P(T<=t) one-tail | 0.00000007449 | |
t Critical one-tail | 1.65857262879 | |
P(T<=t) two-tail | 0.00000014898 | |
t Critical two-tail | 1.98137181488 |
Two Tail P and t -(Excel)
Two -Sample Assuming UnEqual Variances (Excel)
Need difference between means
Est. Error difference
Degree of freedom
Hypothesis
Null Hypothesis
Aternative Hypothesis
P value
0.05 (alpha )
Is it significant ?

From the given Excel output, the t test statistic is 5.6086 and the p-value for the two tail is 0.00000.
Estimated mean difference:0
Degrees of freedom:112
Null hypothesis:
H0: µ1=µ2.
That is, two means are not significant.
Alternative hypothesis:
H1: µ1≠µ2.
That is, two means are significant.
p-vallue:0.0000
alpha=0.05
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