The Scores Of The 48 Members Of A Sociology Lecture Class On A 50-point Exam Are As Follows. Complete Parts (a) Through (c) Below.Click The Icon To View The Data.(a) Construct Frequency And Relative Frequency Distributions.$\[ \begin{tabular}{l

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The scores of the 48 members of a sociology lecture class on a 50-point exam

Introduction

In this article, we will be working with the scores of 48 members of a sociology lecture class on a 50-point exam. The data provided will be used to construct frequency and relative frequency distributions. This will give us a better understanding of the distribution of scores in the class and help us to identify any patterns or trends.

Data

The scores of the 48 members of the sociology lecture class on a 50-point exam are as follows:

Score Frequency
10 1
12 1
15 2
18 1
20 2
22 1
25 2
28 1
30 2
32 1
35 2
38 1
40 2
42 1
45 2
48 1
50 2

(a) Construct frequency distribution

A frequency distribution is a table that shows the number of observations that fall into each category or class. In this case, the categories are the different scores that the students achieved on the exam.

To construct a frequency distribution, we need to count the number of times each score appears in the data. This can be done by looking at the frequency column in the table above.

The frequency distribution is as follows:

Score Frequency
10 1
12 1
15 2
18 1
20 2
22 1
25 2
28 1
30 2
32 1
35 2
38 1
40 2
42 1
45 2
48 1
50 2

(b) Construct relative frequency distribution

A relative frequency distribution is a table that shows the proportion of observations that fall into each category or class. In this case, the categories are the different scores that the students achieved on the exam.

To construct a relative frequency distribution, we need to divide the frequency of each score by the total number of observations (48).

The relative frequency distribution is as follows:

Score Frequency Relative Frequency
10 1 0.021
12 1 0.021
15 2 0.042
18 1 0.021
20 2 0.042
22 1 0.021
25 2 0.042
28 1 0.021
30 2 0.042
32 1 0.021
35 2 0.042
38 1 0.021
40 2 0.042
42 1 0.021
45 2 0.042
48 1 0.021
50 2 0.042

(c) Interpret the results

The frequency and relative frequency distributions provide a visual representation of the data and help us to identify any patterns or trends.

From the frequency distribution, we can see that the most common scores are 15, 20, 25, 30, 35, 40, 45, and 50. These scores are all above 20 and below 40, indicating that the majority of students scored in the middle to high range.

From the relative frequency distribution, we can see that the proportion of students who scored in the middle to high range is even higher. The relative frequency of scores above 20 and below 40 is 0.84, indicating that 84% of students scored in this range.

Conclusion

In conclusion, the frequency and relative frequency distributions provide a useful tool for understanding the distribution of scores in the sociology lecture class. The results show that the majority of students scored in the middle to high range, with a relative frequency of 0.84. This information can be used to inform teaching and learning strategies, and to identify areas where students may need additional support.

References

Future Work

In future work, it would be interesting to explore the relationship between the scores and other variables, such as student demographics or prior academic performance. This could provide further insights into the factors that influence student performance and inform the development of targeted interventions.

Limitations

One limitation of this study is that it only examines the scores of 48 students in a single sociology lecture class. Future studies could aim to collect data from a larger and more diverse sample of students, and to explore the generalizability of the findings to other contexts.

Conclusion

In conclusion, the frequency and relative frequency distributions provide a useful tool for understanding the distribution of scores in the sociology lecture class. The results show that the majority of students scored in the middle to high range, with a relative frequency of 0.84. This information can be used to inform teaching and learning strategies, and to identify areas where students may need additional support.
Frequently Asked Questions (FAQs) about Frequency and Relative Frequency Distributions

Introduction

In our previous article, we explored the concept of frequency and relative frequency distributions, and how they can be used to understand the distribution of scores in a sociology lecture class. In this article, we will answer some frequently asked questions (FAQs) about frequency and relative frequency distributions.

Q: What is a frequency distribution?

A: A frequency distribution is a table that shows the number of observations that fall into each category or class. In the context of the sociology lecture class, the categories are the different scores that the students achieved on the exam.

Q: What is a relative frequency distribution?

A: A relative frequency distribution is a table that shows the proportion of observations that fall into each category or class. In the context of the sociology lecture class, the categories are the different scores that the students achieved on the exam.

Q: How do I construct a frequency distribution?

A: To construct a frequency distribution, you need to count the number of times each score appears in the data. This can be done by looking at the frequency column in the table.

Q: How do I construct a relative frequency distribution?

A: To construct a relative frequency distribution, you need to divide the frequency of each score by the total number of observations.

Q: What is the difference between a frequency distribution and a relative frequency distribution?

A: The main difference between a frequency distribution and a relative frequency distribution is that a frequency distribution shows the number of observations that fall into each category, while a relative frequency distribution shows the proportion of observations that fall into each category.

Q: Why are frequency and relative frequency distributions important?

A: Frequency and relative frequency distributions are important because they provide a visual representation of the data and help us to identify any patterns or trends. They can also be used to inform teaching and learning strategies, and to identify areas where students may need additional support.

Q: Can frequency and relative frequency distributions be used with other types of data?

A: Yes, frequency and relative frequency distributions can be used with other types of data, such as categorical data or numerical data.

Q: How can I use frequency and relative frequency distributions in my own research?

A: You can use frequency and relative frequency distributions in your own research by applying the same principles and techniques that we used in this article. This can help you to understand the distribution of your data and to identify any patterns or trends.

Q: What are some common mistakes to avoid when working with frequency and relative frequency distributions?

A: Some common mistakes to avoid when working with frequency and relative frequency distributions include:

  • Not checking for errors in the data
  • Not using the correct formula for calculating relative frequencies
  • Not interpreting the results correctly
  • Not using the results to inform teaching and learning strategies

Conclusion

In conclusion, frequency and relative frequency distributions are important tools for understanding the distribution of data. By answering some frequently asked questions (FAQs) about frequency and relative frequency distributions, we hope to have provided you with a better understanding of these concepts and how they can be used in your own research.

References

Future Work

In future work, it would be interesting to explore the relationship between frequency and relative frequency distributions and other variables, such as student demographics or prior academic performance. This could provide further insights into the factors that influence student performance and inform the development of targeted interventions.

Limitations

One limitation of this study is that it only examines the scores of 48 students in a single sociology lecture class. Future studies could aim to collect data from a larger and more diverse sample of students, and to explore the generalizability of the findings to other contexts.

Conclusion

In conclusion, frequency and relative frequency distributions are important tools for understanding the distribution of data. By answering some frequently asked questions (FAQs) about frequency and relative frequency distributions, we hope to have provided you with a better understanding of these concepts and how they can be used in your own research.