Problem 15 Determine whether the results ap... [FREE SOLUTION] (2024)

Short Answer

Practical Significance

Practical significance looks beyond the numbers and asks if the observed effect is large enough to be of real-world importance. For example, in the gender selection study, the method resulted in 1020 girls out of 2000 births, which is only 40 more girls than would be expected by chance.
This translates to just a 2% increase in the likelihood of having a girl. While this difference is statistically measured, it might be too small to matter in daily life.
In practice, such a small increase might not justify using the method, considering the efforts, costs, or risks involved. Therefore, while statistical significance is about whether an effect exists, practical significance questions whether that effect is meaningful or useful.

Gender Selection Study

Gender selection study investigates methods to influence the sex of a baby. In this case, the Gender Aide method was used by 2000 people trying to have a girl.
Out of these 2000 births, 980 were boys, and 1020 were girls.
The aim of such studies is to have more control over the baby's gender. However, it's crucial to examine both the statistical and practical significance of the results obtained.
For this study, while the chances of having 1020 girls were found to be 19%, which doesn't meet the typical threshold for statistical significance, it’s also essential to assess if the slight increase of 40 more girls is of practical importance.

Effect Size

Effect size is a quantitative measure of the magnitude of the experimental effect. It shows how much of a difference the method makes.
The effect size in the gender selection study can be calculated by examining the difference in the proportion of girls versus boys born.
In this case, the Gender Aide method resulted in 1020 girls and 980 boys, an excess of 40 girls. This gives us a small effect size of 2% (40 out of 2000).
An effect size gives more context to the statistical findings. Even if a study shows statistical significance, a small effect size might mean that the differences are too trivial to be of real concern in practical terms.

Probability Assessment

Probability assessment in this context checks how likely it is to observe 1020 girls out of 2000 births by chance alone.
The study found there's a 19% chance of this happening if the method had no effect, which translates to a p-value of 0.19.
In statistical practice, researchers often use a significance level of 0.05 (or 5%). If the p-value is below 0.05, the result is considered statistically significant, meaning it's unlikely to have occurred by chance.
Since 19% is much higher than 5%, we cannot conclude there's a significant effect of the Gender Aide method based on this probability assessment. Therefore, the findings don't support a statistically significant difference in gender outcomes, suggesting the method may not be effective.