Match these values of r with the accompanying scatterplots: 0.758, 1, - 0.996, - 0.758, and 0.996. W Click the icon to view the scatterplots. Match the values of r to the scatterplots. Satterplot 1, r= Scatterplot 2, r= Satterplot 3, r= Scatterplot 4, r= Satterplot 5, r=
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.

![**Correlation and Scatterplots Matching Exercise**
This interactive activity helps in understanding how correlation coefficients (r) are reflected in scatterplots. You are provided with a list of correlation values to match with corresponding scatterplots.
**Correlation Values:**
- 0.758
- 1
- -0.996
- -0.758
- 0.996
**Instructions:**
To complete the exercise, examine each scatterplot and select the correlation value that you believe best matches the pattern of the data points.
**Scatterplots Overview:**
1. **Scatterplot 1, r = [Dropdown]**
2. **Scatterplot 2, r = [Dropdown]**
3. **Scatterplot 3, r = [Dropdown]**
4. **Scatterplot 4, r = [Dropdown]**
5. **Scatterplot 5, r = [Dropdown]**
**Note:** Click the icon to view each scatterplot for further analysis. Consider the direction, strength, and form of the data in each plot to determine the correct correlation value.
This exercise aids in understanding the relationship between numerical data and their graphical representations.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fe2e363c5-2472-4cf7-839e-3830821f17e5%2F26b7f2fa-01eb-49cb-892b-d7bcc5ad62b9%2Fqsn9n9o_processed.png&w=3840&q=75)
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