[DATA] Dropping a Course A survey was conducted at a community college of 50 randomly selected students who dropped a course in the current semester to learn why students drop courses. “Personal” drop reasons include financial, transportation, family issues, health issues, and lack of child care. “Course” drop reasons include reducing one’s load, being unprepared for the course, the course was not what was expected, dissatisfaction with teaching, and not getting the desired grade. “Work” drop reasons include an increase in hours, a change in shift, and obtaining fulltime employment. Go to www.pearsonhighered.com/sullivanstats to obtain the data file 12_2_17 using the file format of your choice for the version of the text you are using.
a. Construct a contingency table for the two variables.

Verified step by step guidance

1. Identify the two categorical variables involved in the problem. Here, the variables are the 'Reason for Dropping a Course' (with categories: Personal, Course, Work) and the 'Specific Reasons' within each category (such as financial, transportation, etc.).
2. Collect the data from the survey of 50 students, noting how many students fall into each specific reason category under the broader categories Personal, Course, and Work.
3. Create a table with rows representing the broader categories (Personal, Course, Work) and columns representing the specific reasons within each category. Alternatively, if the problem requires, you can have one variable as rows and the other as columns depending on the data structure.
4. Fill in the table cells with the frequency counts of students who dropped the course for each specific reason. Each cell should represent the number of students corresponding to that combination of category and specific reason.
5. Sum the rows and columns to get marginal totals, which help in understanding the distribution of reasons across categories and the overall totals for each specific reason.

Key Concepts

Contingency Table

A contingency table is a matrix that displays the frequency distribution of two categorical variables. It helps summarize the relationship between variables by showing counts or percentages for each category combination. In this question, it organizes students' drop reasons by category to analyze patterns.

Categorical Variables

Categorical variables represent data sorted into distinct groups or categories without a numerical order. Here, the drop reasons are categorical, divided into 'Personal,' 'Course,' and 'Work' categories. Understanding these variables is essential for correctly grouping and analyzing the data.

Data Collection and Sampling

Data collection involves gathering information systematically, and sampling refers to selecting a subset from a population. The question uses a random sample of 50 students, which is important to ensure the data represents the broader student population dropping courses, allowing valid conclusions.