We can see from Dr. Aguilera's findings that high levels of anxiety are associated with poor academic performance. However, the number of hours of sleep has little bearing on how well or poorly a student does in class.
The confounding variable is important to avoid obstacles to the measurement
<h3>How to illustrate the information?</h3>
Dr. Aguilera discovered a strong link between anxiety and academic achievement. Additionally, this number is negative, indicating a negative correlation between the two variables. According to this negative correlation, the value of the other variable decreases as the value of the first variable increases. Therefore, academic performance declines when anxiety levels rise.
The term "correlation" describes the connection between two variables. In other words, if the correction equals 0, there is no correlation between the two variables. The relationship between sleep duration and academic performance was zero. This indicates that these factors are unrelated and have no bearing on one another.
The Cohort effect is crucial to avoid obstacles to the measurement and research methodologies used, nevertheless.
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The answer to whether the data is convincing is; Yes, it is true that the data is convincing
<h3>How to create hypothesis?</h3>
We are given;
Population Proportion; p = 17.6% = 0.176
Sample size; n = 300
Sample proportion; p^ = 45/300 = 0.15 = 15%
Formula for standard deviation here is;
σ = √(pq/n)
σ = √(p(1 - p)/n)
σ = √(0.15 * 0.85/300)
σ = 0.0206
Formula for z-score is;
z = (p^ - p)/σ
z = (0.176 - 0.15)/0.0206
z = 1
From online p-value from z-score at significance level of 0.05, we have;
p = 0.1587
The p-value is greater than the significance value and so we fail to reject the null hypothesis and conclude that the proportion of underemployed residents in Thicksburg is lower than elsewhere in the country.
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