Question

Unit 5 Scatter Plots and Data Analysis
Vocabulary

Key Terms
Meaning - Description - Picture
Example - All work shown
U5 L1
Data Modeling





U5 L2
Bivariate Data




U5 L2
Scatter Plot




U5 L2
Outlier




U5 L2
Clustering




U5 L5
Linear/NonLinear
Association




U5 L5
Association/
Correlation
Positive

Negative

None


U5 L5
Qualitative Variable




U5 L5
Quantitative Variable




U5 L5
Line of Best Fit




U5 L6
Interpreting key points of trend lines
The y-intercept represents the amount when x = 0.


The x-intercept represents the amount when y = 0.




U5 L6
Inference




U5 L7
Interpreting the Slope of a trend line or line of best fit




U5 L7
Extrapolate from a line of best fit




U5 L10
How do you Interpret a graph?




U5 L10
Probabilistic vs
Deterministic
Probabilistic

Deterministic

Answer 1

Sure! Here's a structured overview of Unit 5 vocabulary focused on Scatter Plots and Data Analysis, including definitions and examples for clarity.

### Unit 5 Vocabulary: Scatter Plots and Data Analysis

| **Key Terms** | **Meaning** | **Description** | **Picture/Example** |
|----------------|-------------|------------------|----------------------|
| **U5 L1: Data Modeling** | Creating a representation of data | Data modeling involves using mathematical equations or visual graphs to represent relationships between variables. |  |
| **U5 L2: Bivariate Data** | Data involving two variables | Bivariate data consists of pairs of numerical values that are analyzed to understand the relationship between the two variables. |  |
| **U5 L2: Scatter Plot** | A graph showing relationships between variables | A scatter plot uses Cartesian coordinates to display values for typically two variables, which helps in identifying correlation. |  |
| **U5 L2: Outlier** | A data point that differs significantly | An outlier is a value that lies outside the overall pattern of a distribution, potentially affecting the analysis outcome. |  |
| **U5 L2: Clustering** | Grouping of data points | Clustering refers to a trend where data points gather close together in a scatter plot, indicating a potential correlation between values. |  |
| **U5 L5: Linear/Nonlinear Association** | The type of correlation between variables | A linear association involves a straight-line relationship, while a nonlinear association suggests a curve or other form of relationship. |  |
| **U5 L5: Association/Correlation** | Relationship strength and direction | - **Positive Correlation**: Both variables increase together.<br>- **Negative Correlation**: One variable increases as the other decreases.<br>- **No Correlation**: No apparent relationship between the variables. |  |
| **U5 L5: Qualitative Variable** | Non-numerical variable | A qualitative variable represents categories or qualities (e.g., colors, names) rather than quantities. |  |
| **U5 L5: Quantitative Variable** | Numerical variable | A quantitative variable represents measurable data or amounts (e.g., height, weight). |  |
| **U5 L5: Line of Best Fit** | A line that best represents data | A line of best fit minimizes the distance of the points from the line and is used for prediction in linear data sets. |  |
| **U5 L6: Key points of trend lines** | Important features of lines | - The **y-intercept** is the point where the line crosses the y-axis, indicating the value of y when x = 0.<br>- The **x-intercept** is the point where the line crosses the x-axis, indicating the value of x when y = 0. |  |
| **U5 L6: Inference** | Drawing conclusions from data | Inference involves making predictions or generalizations about a population based on sample data analysis. |  |
| **U5 L7: Slope Interpretation** | Understanding trend steepness | The slope of a trend line indicates the rate of change between the variables; a steeper slope represents a larger change in y for a given change in x. |  |
| **U5 L7: Extrapolate** | Estimating values beyond the data range | Extrapolation involves predicting unknown values based on extending the trend line beyond the given data points. |  |
| **U5 L10: Interpreting a graph** | Analyzing graph information | To interpret a graph, one looks at trends, shapes, and relationships among plotted points to derive meaningful insights. |  |
| **U5 L10: Probabilistic vs Deterministic** | Types of outcomes | - **Probabilistic**: Outcomes that are uncertain and based on probability (e.g., rolling a die).<br>- **Deterministic**: Outcomes that are predictable and not subject to chance (e.g., mathematical equations). |  |

**Note:** Replace the URLs with actual images or illustrations relevant to the definitions as needed for enhanced understanding.