Least-Squares Regression
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Превземи
Вградување
Содржина
- Linear Regression
- Корелација
- Residuals
- Outlier
- Data
Description
Create your own scatter plot or use real-world data and try to fit a line to it! Explore how individual data points affect the correlation coefficient and best-fit line.
Примери за целите на учење
- Interpret r (the correlation coefficient) as data points are added, moved, or removed.
- Interpret the sum of the squared residuals while manually fitting a line.
- Interpret the sum of the squared residuals of a best-fit line as a data point is added, moved, or removed.
- Compare the sum of the squared residuals between a manually fitted line and the best-fit line.
- Determine if a linear fit is appropriate.
Standards Alignment
Common Core - Math
8.SP.A.1
Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association.
8.SP.A.2
Know that straight lines are widely used to model relationships between two quantitative variables. For scatter plots that suggest a linear association, informally fit a straight line, and informally assess the model fit by judging the closeness of the data points to the line.
8.SP.A.3
Use the equation of a linear model to solve problems in the context of bivariate measurement data, interpreting the slope and intercept. For example, in a linear model for a biology experiment, interpret a slope of 1.5 cm/hr as meaning that an additional hour of sunlight each day is associated with an additional 1.5 cm in mature plant height.
HSS-ID.B.6
Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.
HSS-ID.B.6a
Fit a function to the data; use functions fitted to data to solve problems in the context of the data. Use given functions or choose a function suggested by the context. Emphasize linear, quadratic, and exponential models.
HSS-ID.B.6b
Informally assess the fit of a function by plotting and analyzing residuals.
HSS-ID.B.6c
Fit a linear function for a scatter plot that suggests a linear association.
HSS-ID.C.8
Compute (using technology) and interpret the correlation coefficient of a linear fit.
Version 1.1.12
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Teacher-Submitted Activities
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Автори | Ниво | Тип | Subject |
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| Preguntas de razonamiento para todas las simulaciones HTML5 |
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Diana López | ДД-Вовед СШ Дипл K-5 ДД-Нап ВШ |
ДомР Discuss |
Астрономија Физика Хемија Математика |
| Alignment of PhET sims with NGSS |
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Trish Loeblein | ВШ | Друго | Географија Физика Биологија Хемија |
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Sarah Borenstein | СШ | Друго | Хемија Географија Биологија Физика |
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Amanda McGarry | K-5 СШ ВШ |
Друго | Математика | |
| MS and HS TEK to Sim Alignment | Elyse Zimmer | ВШ СШ |
Друго | Хемија Физика Биологија |
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| PhET Simulations Aligned for AP Physics C | Roberta Tanner | ВШ | Друго | Физика | ||
| Understanding Line of best fit and Correlation Coefficient | Rebecca Battat | ВШ | Guided | Математика | ||
| Data Detective | Kelly Findley, Mary Burr | СШ | Guided | Математика | ||
| Correlation vs Causation | Andy Braaten | ВШ ДД-Вовед |
Лаб | Математика |
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