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According to The Chronicle for Higher Education Almanac (2016), there were 1,003,329 Associate degrees awarded by U.S. community colleges in the \(2013-2014\) academic year. A total of 613,034 of these degrees were awarded to women. a. If a person who received an Associate degree in \(2013-\) 2014 is selected at random, what is the probability that the selected person will be female? b. What is the probability that the selected person will be male?

Short Answer

Expert verified
a. The probability that a randomly selected person who received an Associate degree in the \(2013-2014\) academic year will be female is approximately \(0.61073\) or \(61.073\%\). b. The probability that a randomly selected person who received an Associate degree in the \(2013-2014\) academic year will be male is approximately \(0.38927\) or \(38.927\%\).

Step by step solution

01

Understand the given data

We've been given the following data: 1. Total number of Associate degrees awarded in the \(2013-2014\) academic year: \(1,003,329\). 2. Number of degrees awarded to women: \(613,034\).
02

Calculate the number of degrees awarded to men

To calculate the number of degrees awarded to men, we can subtract the number of degrees awarded to women from the total number of Associate degrees. Number of degrees awarded to men: \(1,003,329 - 613,034 = 390,295\)
03

Calculate the probability of a randomly chosen person being female

To find the probability of a randomly chosen person being female, we can divide the number of degrees awarded to women by the total number of Associate degrees. Probability (female) = \(\frac{613,034}{1,003,329}\) = \(0.61073\) Approximately, the probability that the selected person will be female is \(0.61073\) or \(61.073\%\).
04

Calculate the probability of a randomly chosen person being male

Similarly, to find the probability of a randomly chosen person being male, we can divide the number of degrees awarded to men by the total number of Associate degrees. Probability (male) = \(\frac{390,295}{1,003,329}\) = \(0.38927\) Approximately, the probability that the selected person will be male is \(0.38927\) or \(38.927\%\).
05

Conclusion

a. The probability that a person randomly selected among those who received an Associate degree in the \(2013-2014\) academic year will be female is approximately \(0.61073\) or \(61.073\%\). b. The probability that a person randomly selected among those who received an Associate degree in the \(2013-2014\) academic year will be male is approximately \(0.38927\) or \(38.927\%\).

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Key Concepts

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

Associate Degree Statistics
Understanding the landscape of higher education and the trends in degree attainment is critical for educational institutions, policymakers, and students alike. Associate degrees, often awarded by community colleges, represent an important educational milestone for many individuals. The statistics regarding these degrees can reveal a great deal about the demographics of students achieving this level of education.

For example, within the context of the exercise, the 1,003,329 Associate degrees conferred in the 2013-2014 academic year provide insight into the education pipeline at that time. This data, disaggregated by gender, shows that a majority, approximately 61.07%, of these degrees were awarded to women. This statistic may point to a broader trend of increasing female participation in higher education, which can have significant implications for workforce development, economic growth, and gender equality policies.

Furthermore, understanding these statistics helps in setting a baseline for measuring the success of educational programs, addressing gender disparities, and shaping future educational strategies to ensure that everyone has equal access to higher educational opportunities.
Gender Distribution in Education
Gender distribution in education is a topic that has received a considerable amount of attention, as it aligns with broader discussions about equality and representation. Amidst the data portraying the educational landscape, the disparities in gender distribution often prompt discussions on societal norms, cultural influences, and policies aimed at supporting equal access to education for all genders.

Historical data, such as that from the 2013-2014 academic year in our exercise, can shine a light on systemic changes over time, potential biases in educational offerings, and the effectiveness of interventions designed to promote gender balance. It is important to continue monitoring these trends, as they serve as barometers for the inclusivity and progressiveness of education systems. By dissecting these numbers and looking beyond the surface, educators, administrators, and policymakers can develop targeted approaches to achieve a more balanced and fair educational environment for students of all genders.
Probability Theory
Probability theory is a mathematical framework that deals with the likelihood of occurrence for different events. In the context of our exercise, it helps quantify the chance that a randomly selected individual from the group of students who earned an Associate degree is female or male. This field of mathematics is foundational not only in statistics but also in various disciplines like finance, science, and philosophy, where making decisions under uncertainty is common.

The calculation clearly demonstrates how probability is applied: by dividing the number of degrees earned by one group (either male or female) by the total number of degrees awarded. These computations yield the respective probabilities (0.61073 for females and 0.38927 for males). It's interesting to note how these probabilities offer succinct numerical values that have broader implications, informing us about gender trends in higher education at a given time.

Understanding probability theory is essential for interpreting data, predicting future trends, and making informed decisions. It's a powerful tool that, when applied correctly, provides valuable insights into various aspects of academic and professional disciplines.

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Most popular questions from this chapter

The report "Improving Undergraduate Learning" (Social Science Research Council, 2011) summarizes data from a survey of several thousand college students. These students were thought to be representative of the population of all U.S. college students. When asked about a typical semester, \(68 \%\) said they would be taking a class that is reading intensive (requires more than 40 pages of reading per week). Only \(50 \%\) said they would be taking a class that is writing intensive (requires more than 20 pages of writing over the course of the semester). The percentage who said that they would be taking both a reading intensive course and a writing intensive course in a typical semester was \(42 \% .\) In Exercise \(5.40,\) you constructed a hypothetical 1000 table to calculate the following probabilities. Now use the probability formulas of this section to find these probabilities. a. The probability that a randomly selected student would be taking at least one reading intensive or writing intensive course. b. The probability that a randomly selected student would be taking a reading intensive course or a writing intensive course, but not both. c. The probability that a randomly selected student is taking neither a reading intensive nor a writing intensive course.

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Suppose that \(20 \%\) of all teenage drivers in a certain county received a citation for a moving violation within the past year. Assume in addition that \(80 \%\) of those receiving such a citation attended traffic school so that the citation would not appear on their permanent driving record. Consider the chance experiment that consists of randomly selecting a teenage driver from this county. a. One of the percentages given in the problem specifies an unconditional probability, and the other percentage specifies a conditional probability. Which one is the conditional probability, and how can you tell? b. Suppose that two events \(E\) and \(F\) are defined as follows: \(E=\) selected driver attended traffic school \(F=\) selected driver received such a citation Use probability notation to translate the given information into two probability statements of the form \(P(\underline{C})=\) probability value.

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