Optimizing Your One Sample T-Test For Population Mean (Matched Pairs) – Meeting The Conditions For Accurate Results

One Sample T-Test for Population Mean (Matched Pairs) CONDITIONS

1. Two random samples or two random groups in an experiment2. ONLY FOR SAMPLE: 10% Condition n1, n2 ≤ 1/10 (N1, N2) 3. Large Counts: n1(p̂1), n1(1-p̂1), n2(p̂2), n2(1-p̂2) ≥ 10

To perform a One Sample T-Test for Population Mean (Matched Pairs), there are certain conditions that need to be met:

1. Independent Observations: The observations should be independent of each other. In this case, we have matched pairs, so the observations are not independent, but rather dependent.

2. Normality: The differences between the two related groups should be normally distributed. You can check for normality by creating a histogram or a normal probability plot. If the data is not normally distributed, a non-parametric test such as the Wilcoxon Signed Rank test should be used.

3. Random Sampling: The sample should be randomly selected from the population to ensure that it is representative of the population.

4. Equal Variances: The variance of the population should be equal between the two related groups. You can check for equal variances by performing a variance test such as the Levene’s test or the F test.

If these conditions are met, then a One Sample T-Test for Population Mean (Matched Pairs) can be performed to compare the means of the two related groups.

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