Scatter plots and data analyst unit test.

1. What is a scatter plot and how is it used in data analysis?

- A scatter plot is a type of graphic representation of data points in a two-dimensional plane. It is used to show the relationship between two sets of data and to identify patterns or trends in the data.

2. What is the purpose of a data analyst in interpreting scatter plots?
- The purpose of a data analyst in interpreting scatter plots is to analyze the relationship between the variables in order to draw conclusions or make predictions based on the data.

3. How do you determine the strength of the relationship between variables in a scatter plot?
- The strength of the relationship between variables in a scatter plot can be determined by the pattern of the data points. If the points form a clear and strong line or curve, then the relationship is considered strong. If the points are more scattered and do not form a clear pattern, then the relationship is considered weak.

4. What are some common patterns found in scatter plots and what do they signify?
- Common patterns found in scatter plots include positive linear relationships, negative linear relationships, clusters, outliers, and no relationship. Positive linear relationships signify that as one variable increases, the other variable also increases. Negative linear relationships signify that as one variable increases, the other variable decreases. Clusters signify groups of data points that have a similar relationship. Outliers are data points that do not fit the overall pattern. No relationship signifies that there is no clear relationship between the variables.

5. How can scatter plots be used to make predictions or draw conclusions in data analysis?
- Scatter plots can be used to make predictions or draw conclusions in data analysis by analyzing the relationship between the variables and using that information to make informed decisions. For example, if there is a strong positive linear relationship between two variables, you can predict that as one variable increases, the other variable will also increase. This can be used to make strategic decisions in business, marketing, or other areas.