Here Are Plots for Studentized Residuals Against Chest Compare the Regression with the Previous One

question 5

Essay

Here are plots for Studentized residuals against Chest. Here is the same regression with the two data points with residuals above 2 removed:
Dependent variable is: Weight
30 total bears of which 2 are missing
R-squared = 93.8% R-squared (adjusted)= 93.0%
s = 7.22 with 28 - 4 = 24 degrees of freedom $$\begin{array} { c } & \text { Sum of } & &{ \text { Mean } } \\\text { Source } & \text { Squares } & \text { DF } & \text { Square } & \text { F-ratio } \\\text { Regression } & 21671 & 3 & 7223.67 & 123.23 \\\text { Residual } & 1406.88 & 24 & 58.62 &\end{array}$$ $$\begin{array} { l r c r r } \text { Variable } & \text { Coefficient } & \text { SE(Coeff) } & \text { t-ratio } & \text { P-value } \\\text { Intercept } & - 167.52 & 7.47 & - 22.43 & < 0.0001 \\\text { Chest } & 3.01 & 2.98 & 1.01 & 0.3218 \\\text { Length } & 4.05 & 1.53 & 2.65 & 0.0135 \\\text { Sex } & - 2.03 & 2.14 & - 0.95 & 0.3509\end{array}$$ Compare the regression with the previous one.In particular,which model is likely to make the best prediction of weight? Which seems to fit the data better?

Learn methods to measure explicit and implicit memory and understand their differences.

Assess memory enhancement techniques such as hierarchies, chunking, mnemonics, and imagery.

Differentiate between neural network models and associative network models of memory.

Understand the role and influence of schemas in memory encoding and their relation to expert knowledge.

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