The National Survey Of Student Engagement (NSSE) Surveys Fre

224 The National Survey Of Student Engagement Nsse Surveys Freshmen

2.24 The National Survey of Student Engagement (NSSE) surveys freshmen and seniors about their level of engagement in campus and classroom activities that enhance learning. Hundreds of thousands of students from over 1,200 schools have completed surveys since 1999, the first year that the NSSE was administered. Among the many questions on the NSSE, students were asked how often they were assigned a paper of 20 pages or more during the academic year. For a sample of 19 institutions classified as national universities that made their data publicly available through the U.S. News & World ReportWeb site, here are the percentages of students who said they were assigned between 5 and 10 20-page papers: a. Create a frequency table for these data. Include a third column for percentages. b. For what percentage of these schools did exactly 4% of their students report that they wrote between 2.26 Refer to the data in Exercise 2.24. a. Create a histogram of grouped data using 5 intervals. b. How many schools had 6% or more of their students reporting that they wrote between 5 and 10 20-page papers that year? c. How are the data distributed? 2.28 A university’s associate directors for whom a statistician was consulting were interested in alumni donations, as are many schools, not only because they want the money but also because it is one of the criteria by which U.S. News & World Report ranks U.S. institutions of higher learning. U.S. News includes this criterion because higher rates of alumni giving are seen as indicative of the satisfaction of former students. An increase in a school’s overall ranking by this magazine has been demonstrated to translate into an increase in applications— and all schools want that—even though there is controversy about the validity of these rankings. One set of rankings is for the best national universities: institutions that offer undergraduate, master’s, and doctoral degrees and have an emphasis on research. (Harvard tops the list that was published in 2005.) Here are the alumni giving rates that were reported in 2005; the rates are the percentages of alumni who donated to each of the top 70 national universities in the year prior to publication of these data. a. How was the variable of alumni giving operationalized? What is another way that this variable could be operationalized? b. Create a grouped frequency table for these data. c. The data have quite a range, with the lowest scores belonging to Boston University, the University of California at Irvine, and the University of California at San Diego, and the highest belonging to Princeton University. What research hypotheses come to mind when you examine these data? State at least one research question that these data suggest to you. 2.30 Consider these three variables: finishing times in a marathon, number of university dining hall meals eaten in a semester on a three-meal-a-day plan, and scores on a scale of extroversion. a. Which of these variables is most likely to have a normal distribution? Explain your answer. b. Which of these variables is most likely to have a positively skewed distribution? Explain your answer, stating the possible contribution of a floor effect. c. Which of these variables is most likely to have a negatively skewed distribution? Explain your answer, stating the possible contribution of a ceiling effect. 2.32 The Centers for Disease Control and other organizations are interested in the health benefits of breastfeeding for infants. The National Immunization Survey includes questions about breast-feeding practices, including the question: “How long was [your child] breast- fed or fed breast milk?†The data for duration of breast-feeding in months for 20 hypothetical mothers are presented below. a. Create a frequency table for these data. Include a third column for percentages. b. Create a grouped frequency table for these data with three groups (create groupings around the midpoints of 2.5 months, 7.5 months, and 12.5 months). 2.34 Refer to the data in Exercise 2.32. a. Create a frequency polygon of the original data. b. Create a frequency polygon of the grouped data. c. If you wanted the data to be normally distributed around 12 months, how would the data have to shift to fit that goal? How could you use knowledge about the current distribution to target certain women? 2.36 For each of the types of data described below, would you present individual data values or grouped data when creating a frequency distribution? Explain your answer clearly. a. Eye color observed for 87 people b. Minutes used on a cell phone by 240 teenagers c. Time to complete the Boston Marathon for the nearly 22,000 runners who participate d. Number of siblings for 64 college students d. Number of siblings for 64 college students 2.38 The director of career services at a large university is offering training on résumé construction. In an effort to present up-to-date information, using 23 résumés he just reviewed for a receptionist position in his office, he counts the total number of words used. Here are the data: a. Create a grouped frequency table with 4 intervals. b. What does this information tell people who come to his training on résumé construction?

Paper For Above instruction

The data provided across multiple exercises reflect significant aspects of statistical analysis concerning survey results, university performance metrics, and personal attributes. To explore these comprehensively, this paper will extract relevant insights, methodologies, and interpretive strategies. The focus will be on understanding data collection procedures, data distribution characteristics, and the implications of the data in real-world educational and health contexts.

Analysis of the National Survey of Student Engagement (NSSE) Data

The NSSE data on freshmen's engagement, particularly regarding assignments of lengthy papers, serves as an important indicator of academic involvement. Creating a frequency table involves tallying the number of institutions reporting specific percentages of students tasked with writing between 5 and 10 twenty-page papers. The table should include three columns: the percentage interval, the number of institutions (frequency), and the percentage of total institutions (percentage). For example, if three institutions report that 10% of students wrote between 5 and 10 twenty-page papers, this would be recorded accordingly in the frequency column, and the percentage would be calculated as (3/19) * 100 ≈ 15.8%. Such tabulation provides a clear overview of the distribution of these academic assignments across institutions.

To visualize the data, a histogram with five intervals could be constructed based on the grouped data, which helps to identify patterns such as skewness or symmetry in the distribution. The analysis of how many schools had 6% or more of their students reporting that they wrote between 5 and 10 twenty-page papers reveals the extent of engagement or workload among institutions. A higher percentage might suggest rigorous academic demands, influencing institutional policies and student perceptions.

The distribution pattern of these data points can be explored by examining the skewness and kurtosis of the histogram. A symmetric distribution might indicate uniform academic practices, while skewness could suggest variations in institutional policies or student workloads.

University Alumni Giving Rates and Their Implications

Moving to alumni donation data, the operationalization of the variable involves considering the proportion of alumni who contributed financially within a specific period, here the year prior to 2005. This proportional measure captures the giving rate, which indicates alumni satisfaction and institutional quality. An alternative operationalization could involve the total monetary amount donated or the number of donors relative to the total alumni population. The grouped frequency table for these data would categorize the universities into intervals based on their giving rates, revealing the distribution pattern—whether skewed, normal, or uniform.

Analyzing the range of giving rates across universities like Boston University, UC Irvine, UC San Diego, and Princeton, suggests hypotheses about factors influencing alumni generosity. For instance, one might question whether higher-ranking universities show higher alumni engagement, or whether certain institutional characteristics, such as endowment size or alumni network strength, correlate with donation rates. A pertinent research question could be: “Does the university’s research emphasis influence alumni donation rates?” These hypotheses are vital for strategic planning in development offices and for understanding alumni behaviors in relation to institutional prestige and student experiences.

Distribution Characteristics of Various Variables

Considering marathon finishing times, dining hall meal counts, and extroversion scores, we can hypothesize about their distribution shapes. Marathon finishing times are typically normally distributed because most runners cluster around a mean time, with fewer runners finishing significantly faster or slower. This makes it the most likely candidate for a normal distribution, assuming no external disruptions or unusual participation patterns.

Conversely, the number of meals eaten in a semester is often positively skewed. Many students eat three meals daily, with some eating less (floor effect at zero or near-zero meals if applicable in some contexts). This creates a concentration at the lower end and a tail extending towards higher values, indicating positive skewness. Such a distribution occurs because of the floor effect (minimum possible meals—zero or one), which constrains lower values but allows variability at higher levels.

Extroversion scores are most likely negatively skewed if most individuals exhibit moderate to high extroversion, with fewer scoring at the high end due to a ceiling effect. The clustering at higher scores suggests that a negative skewness could be present; however, if many respondents are at the lower end, a positive skew might be observed. In this scenario, a ceiling effect limits the maximum score achievable, resulting in a negative skew.

Breastfeeding Duration Data and Its Analysis

The hypothetical data on breastfeeding duration illustrate how frequency and grouped data provide insights into health behaviors. A frequency table summarizes how many mothers breastfed for specific durations, which can be grouped into intervals such as less than 2.5 months, 2.5 to 7.5 months, and more than 7.5 months, centered around the midpoints of these ranges for better clarity. Creating frequency polygons from these tables visually demonstrates the distribution shape, revealing whether most mothers breastfed for shorter or longer durations. This information can inform public health strategies aimed at promoting longer breastfeeding where beneficial.

Implications for Data Representation and Distribution

Deciding whether to present individual or grouped data depends on the data's granularity and the analysis's purpose. For example, eye color observed in 87 people can be grouped into categories such as blue, brown, green, etc., because eye color is categorical. Minutes used on a cell phone by teenagers, being continuous but with potentially many decimal points, are well-suited to grouped data to visualize distribution patterns. Marathon times have many data points and are continuous; individual data might be too unwieldy, favoring grouped data for clarity. The number of siblings, a discrete variable, can be presented both ways but often benefits from grouping, especially if the data set is large and spread out.

Résumé Word Count Data and Its Presentation

The résumé word count data from 23 résumés are best presented using grouped frequency tables with four intervals, such as 0-50, 51-100, 101-150, and 151-200 words, providing a clearer picture of typical résumé lengths. This aids résumé builders by highlighting common practices, allowing for adjustments to optimize readability and impact. Such analysis can also uncover outliers—résumés that are unusually short or long—and guide best practices in résumé writing.

Conclusion

Overall, the analysis of these diverse datasets emphasizes the importance of appropriate data summarization techniques, understanding distribution shapes, operationalizing variables effectively, and interpreting data within real-world contexts. Making informed decisions regarding data presentation and analysis depends on recognizing the nature of variables—whether categorical or continuous—and their expected distribution patterns. These skills are crucial in educational research, health studies, marketing, and beyond, contributing to more accurate, insightful interpretations that can guide policy and strategic initiatives.

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