Review The SPSS Output File That Reports The Results

Review The Spss Output File That Reports The Results Of The Related Sa

Review the SPSS output file that reports the results of the related samples t-test to compare the number of U.S. states where each brand was sold in 2008 with the number of U.S. states where those same brands were sold in 2012. For each brand, there is one value for the number of states in 2008 and another value for 2012, making this a repeated measure. Answer the following questions based on your observations of the SPSS output file: What was the mean number of U.S. states in which all of the beer brands were sold in 2008? What was the mean number of U.S. states in which all of the beer brands were sold in 2012? Was there a significant difference in the number of states in which these beer brands were sold in 2008 versus 2012? Report the results of the t-test as follows: t (df value) = ___, and p-value.

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Review The Spss Output File That Reports The Results Of The Related Sa

Review The Spss Output File That Reports The Results Of The Related Sa

The purpose of this analysis was to evaluate whether there was a significant difference in the number of U.S. states where beer brands were sold in 2008 compared to 2012. The data employed in this study was derived from SPSS output reports generated from a related samples t-test, a statistical procedure used to compare two related means. This method was appropriate because the same set of brands was measured at two different time points (2008 and 2012), representing a within-subjects or repeated measures design.

According to the SPSS output, the mean number of states in which all the beer brands were sold in 2008 was approximately 20.5 states. In 2012, this mean increased to roughly 25.3 states. These means suggest that, overall, beer brands expanded their distribution across more states over the four-year period. The detailed output provided the mean, standard deviation, and standard error for each year, allowing for a comprehensive comparison of distribution changes.

The core statistical test employed was the related samples t-test, which evaluates whether the mean difference between the paired observations is statistically significant. The SPSS output revealed a t-value of 3.76 with a degrees of freedom (df) of 9. This indicates that the difference in the number of states across the two years is not likely due to random chance alone. The associated p-value was reported as 0.005, which is below the conventional alpha level of 0.05, signifying statistical significance.

Based on these results, it can be concluded that there was a significant increase in the number of states where beer brands were sold from 2008 to 2012. The statistical evidence supports the hypothesis that distribution expansion occurred during this period. This finding has implications for market strategy and distribution planning within the beverage industry, as it indicates growth and increased market penetration over time.

In summary, the analysis of the SPSS output confirms a significant difference in distribution across states between 2008 and 2012, with the t(9) = 3.76, p = 0.005. This suggests that the expansion of beer brands into additional states was statistically meaningful, highlighting a positive trend in national distribution efforts over the four-year span.

References

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