The dot plot below represents how long it takes students in a 7th grade math class to get to school every morning. COMMUTE TIME 10 15 20 25 30 35 40 45 Minutes How many students are in the class? students
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
![### Commute Time for 7th Grade Math Class
**The dot plot below represents how long it takes students in a 7th grade math class to get to school every morning.**
**Commute Time (in Minutes)**
A dot plot is shown representing the commute times, which are as follows:
- **5 minutes:** 1 student
- **10 minutes:** 5 students
- **15 minutes:** 1 student
- **20 minutes:** 1 student
- **25 minutes:** 1 student
- **30 minutes:** 1 student
- **35 minutes:** 6 students
- **40 minutes:** 1 student
- **45 minutes:** 1 student
**How many students are in the class?**
To find the total number of students, count the number of dots:
- Total dots = 1 + 5 + 1 + 1 + 1 + 1 + 6 + 1 + 1 = 18
**Submit your answer with the total number of students:**
[ ] students
Submit Answer
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**Educational Insight:**
Dot plots are a useful way to visually represent data distributions for small to moderate-sized datasets. In the given example, it is clear that most students take either 10 minutes or 35 minutes to get to school, with these times showing the highest frequency of students. This type of visualization aids in understanding the spread and central tendencies in the data.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F16d6ceff-1835-4fe6-85ee-8783c382d2be%2F90ff6fbc-38d5-4727-9e2e-b88d8b12a7ba%2F4lhe5v_processed.jpeg&w=3840&q=75)
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