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Sheet1 contains data on specific gravity and ºBrix, while Sheet2 has data on pH and total titratable acidity. Sheet3 is empty. To analyze if there's a significant difference in pH and total titratable acidity, we'll focus on Sheet2.

Next, we'll perform statistical tests to check for significant differences in pH and total titratable acidity across the samples.

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**pH Normality Test (Shapiro-Wilk):**p-value = 0.31, indicating the pH data is normally distributed.**Total Titratable Acidity Normality Test (Shapiro-Wilk):**p-value = 0.037, suggesting the acidity data may not be normally distributed as the p-value is less than 0.05.**Levene's Test for Equal Variances:**p-value = 0.57, indicating equal variances between pH and acidity data.

Given the acidity data does not appear to be normally distributed, we conclude that the data does not meet the assumptions for a t-test. This means we cannot definitively say if there is a significant difference in pH and total titratable acidity based on the t-test criteria.

Since the data doesn't meet the assumptions for a t-test, we'll use a non-parametric test. The Mann-Whitney U test is a good alternative for comparing two independent samples when the data is not normally distributed. This test will help us determine if there's a significant difference in pH and total titratable acidity without assuming normal distribution of the data.

Let's proceed with the Mann-Whitney U test.

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**Mann-Whitney U Test p-value:**0.00058

The Mann-Whitney U test yielded a p-value of 0.00058, indicating a significant difference between the pH and total titratable acidity of the samples. This suggests that the distributions of pH and acidity values are significantly different from each other.

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The correlation between pH and total titratable acidity is approximately 0.49. This indicates a moderate positive correlation, suggesting that as the pH increases, the total titratable acidity tends to increase as well, but not strongly.

To further investigate the relationship between pH and total titratable acidity, we'll create a scatter plot. This visual representation will help us see how these two variables relate to each other in the dataset.

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The scatter plot shows a moderate positive correlation between pH and total titratable acidity, consistent with the correlation coefficient of approximately 0.49. The plot suggests that as pH increases, total titratable acidity tends to increase as well, but the relationship is not strongly linear, indicating variability in how these two variables are related across different samples.

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**Mann-Whitney U Test p-value:**0.0021

The Mann-Whitney U test yielded a p-value of 0.0021, indicating a significant difference between the specific gravity and ºBrix of the samples. This suggests that the distributions of specific gravity and ºBrix values are significantly different from each other.

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The correlation coefficient between specific gravity and ºBrix is approximately 0.45, indicating a moderate positive correlation. This suggests that as specific gravity increases, ºBrix tends to increase as well, but the relationship is not strongly linear.

To proceed with additional non-parametric tests, we need to know which specific variables you're interested in comparing. Could you specify the variables or pairs of variables you'd like to compare using non-parametric tests?

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