A researcher computes a moderated regression model and finds the following. Describe what the interaction term represents (e.g., which terms are interacting), and interpret the interaction.
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Model : 1
Y : MATH
X : SCIENCE
W : READING
Sample
Size: 1210
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OUTCOME VARIABLE:
MATH

\begin{array}{l}\text { Model Summary }\\\begin{array}{rrrrrrrr}R & R-s q & \text { MSE } & \text { F (HC4) } & \text { df1 } & \text { df2 } &P \\.7050 & .4971 & 135.7397 & 323.8703 & 3.0000 & 1206.0000 & .0000\end{array}\end{array}

\text { Model }

\begin{array}{lrrrrrr} & \text { Coeff } & \text { Se (HC4) } & t & p & \text { LLCI } & \text { ULCI } \\& & & & & & \\\text { constant } & 31.1829 & 31.4492 & .9915 & .3216 & -30.5183 & 92.8840 \\\text { SCIENCE } & .9186 & .3579 & 2.5668 & .0104 & .2165 & 1.6207 \\\text { READING } & .2803 & .1730 & 1.6205 & .1054 & -.0591 & .6197 \\\text { Int\_1 } & -.0010 & .0019 & -.5006 & .6168 & -.0048 & .0028\end{array}

Product terms key:

\text { Int\_ } 1: \text { SCIENCE } \mathrm{x} \text { READING }

\text { Test (s) of highest order unconditional interaction (s): }

\begin{array}{rrrrr}&\mathrm{R} 2-\mathrm{chng} & \mathrm{F}(\mathrm{HC} 4) & \text { df1 } & \text { df2 } & p \\\mathrm{X} * \mathrm{~W}&.0003 & .2506 & 1.0000 & 1206.0000 & .6168\end{array}

\begin{array}{r}\text { Focal predict: SCIENCE }&(X) \\\text { Mod var: READING }&(W)\end{array}

In a Mediation Model, a Negative Sign for the Direct

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