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Find the sample proportion \(\hat{p}\). The math SAT score is higher than the verbal SAT score for 205 of the 355 students who answered the questions about SAT scores. Find \(\hat{p},\) the proportion for whom the math SAT score is higher.

Short Answer

Expert verified
The sample proportion \(\hat{p}\) is approximately 0.577 or 57.7%.

Step by step solution

01

Calculation of Sample Proportion

The sample proportion \(\hat{p}\) can be calculated by dividing the number of successful outcomes (students for whom the math SAT score is higher than the verbal SAT score, which is 205) by the total number of outcomes (total number of students who answered the questions about SAT scores, which is 355). \nHence, \(\hat{p} = 205 / 355\)

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Statistics and Sample Proportion
Statistics is a branch of mathematics that deals with the collection, analysis, interpretation, and presentation of masses of numerical data. A critical concept in statistics is the sample proportion, which represents a fraction of the sample with a particular characteristic. It's denoted by \( \hat{p} \) and is a point estimate of the true proportion in the entire population. For instance, if you want to understand the performance of students in SAT scores, looking at the proportion that scores higher in a particular section can give insights into their strengths and weaknesses.

Calculating the sample proportion involves two essential pieces of information: the count of 'successes' within the sample (in our case, students who scored higher on math than verbal) and the total sample size. The formula for the sample proportion is: \( \hat{p} = \frac{\text{Number of successes}}{\text{Total sample size}} \). The calculation is simple, yet it provides valuable insights into the characteristics of the sample.
SAT Scores
The Scholastic Assessment Test (SAT) is a standardized test widely used for college admissions in the United States. It assesses a student's readiness for college and provides colleges with a common data point that can be used to compare all applicants. SAT scores are often broken down into different sections, primarily Math and Evidence-Based Reading and Writing, commonly referred to as verbal.

Understanding SAT Score Trends

When educators and researchers analyze SAT scores, they often look for patterns or trends, such as whether students tend to perform better on math or verbal sections. This analysis helps in identifying areas where students might need additional help or resources. It can also inform curriculum development and teaching strategies to bolster students' performance in weaker areas. The exercise given specifically explores the proportion of students that perform better on the math section, which is a statistic that could have implications for educational focus and support.
Proportion Calculation
Proportion calculation is a fundamental concept in both statistics and everyday life. It allows us to express how large one quantity is in relation to another. In the context of our exercise, calculating the proportion of students whose math SAT scores are higher than their verbal scores provides us with a specific example of how proportion calculations are used in educational settings.

A proportion is usually expressed as a decimal or a percentage, and calculating it is simple division. After getting the value from dividing the number of successes by the total number of attempts, one might convert it to a percentage to make it more intuitive to understand. To convert a decimal to a percentage, we multiply it by 100. Thus, if a student group had a sample proportion of \( \hat{p} = 0.577 \text{(rounded)} \), it would be equivalent to saying that approximately 57.7% of the students scored higher in the math section of the SAT compared to the verbal. This quantified insight helps educators gauge relative performance and identify areas for improvement or further investigation.

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Most popular questions from this chapter

Draw any scatterplot satisfying the following conditions: (a) \(n=10\) and \(r=1\) (b) \(n=8\) and \(r=-1\) (c) \(n=5\) and \(r=0\)

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Create Your Own: Bubble Plot Using any of the datasets that come with this text that include at least three quantitative variables (or any other dataset that you find interesting and that meets this condition), use statistical software to create a bubble plot of the data. Indicate the dataset, the cases, and the variables that you use. Specify which variable represents the size of the bubble. Comment (in context) about any interesting features revealed in your plot.

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