Curtis Says That The Data In The Scatter Plot Shown Below Represents A Linear Relation But Shyenne Thinks That The Data 1 (58.1 KiB) Viewed 51 times
Curtis Says That The Data In The Scatter Plot Shown Below Represents A Linear Relation But Shyenne Thinks That The Data 2 (20.79 KiB) Viewed 51 times
Curtis says that the data in the scatter plot shown below represents a linear relation, but Shyenne thinks that the data models a non-linear relation. Who do you agree with? To justify your answer, use the table of values for selecting the regression model that best fits the data. BE 34 22 20- 1 16 141 12-1 10-1 11 61 4+ + 16 11 20 TA + 2 х х 6 8 20 0 27 2 4 6 8 10 24 20.8 19.5 17.8 19 ola 12 14 16.9 15.8 16 18 22 24 14 14.6 11.9 12.1 11.7 Y Characterize the graph: • Direction: • Strength • What model do you think would best fit this data? Measuring how well a model suits a particular set of data: The Regression coefficient, R is a measure of how well a certain models fits your data. The value ranges between and 1. If it is close to then the model doesn't fit your data at all. If it is close to 1 then the model fits your data very well. (Eg. An Rp of 0.42 means that you model doesn't fit your data too well, while an R of 0.95 means that your model fits your data very well.). Your calculator can calculate this R? value for you so that you can compare models.
Now let's use the calculators to find the following you'll want to use the yellow TI-83+ help sheets): i) A Linear Model for this data Linear Equation Regression Coefficient R2 ii) A Quadratic Model for this data Quadratic Equation Regression coefficient R iii) An Exponential Model for this data • Exponential Model Equation Regression Coefficient R?: According to your regression coefficients, what is the best model for this data?
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