No.
In order to conduct an analysis like this one, it is essential to select a RANDOM SAMPLE from the entire POPULATION involved in the study. For instance, Pete is attempting to gauge the overall satisfaction of his customers, therefore, he should distribute the surveys to a randomly chosen group of customers rather than only targeting those who have bought the most items. Doing so will yield results that are more REPRESENTATIVE of the overall customer satisfaction. If he limits the surveys to those customers who have purchased the most, he is likely to see inflated satisfaction levels, which would not truly reflect the general sentiment of all customers.
To determine if there is evidence suggesting a change in average height, we can conduct a right-tailed test and formulate both null and alternative hypotheses.
H₀ (null hypothesis): μ = 162.5
H₁ (alternative hypothesis): μ > 162.5
With two samples to analyze, we can calculate the z-score using the formula provided below.

In this formula, Z symbolizes the z-score, Χ denotes the new sample mean, μ indicates the theoretical average, δ represents the standard deviation, and n signifies the sample size. Based on the gathered values,


Assuming a significance level of α = 0.05. With a z-score of 2.77, we can reference the z-table to ascertain the p-value. This yields P(Z > 2.77) =.0028. Since our p-value is below α, we reject the null hypothesis, indicating that the average height of female freshman students has indeed shifted.
Response:
x² + -6x = -13
Detailed breakdown:
8x² - 48x = -104
Rearranging gives us x² - 6x = -13