The regression below predicts the daily number of skiers who visit a small ski resort based on three explanatory variables.
The data is a random sample of 30 days from the past two ski seasons. The variables are: SKIERS the number of skiers who visit the resort on that day
SNOW the number of inches of snow on the ground
TEMP the high temperature for the day in degrees

F

.
WEEKDAY an indicator variable, weekday

= 1

, weekend

= 0

Dependent variable is Skiers

\mathrm { R }

squared

= 25.4 \% \quad \mathrm { R }

squared (adjusted)

= 16.8 \%

\mathrm { s } = 125.1

with

30 - 4 = 26

degrees of freedom

$The regression below predicts the daily number of skiers who visit a small ski resort based on three explanatory variables. The data is a random sample of 30 days from the past two ski seasons. The variables are: SKIERS the number of skiers who visit the resort on that day SNOW the number of inches of snow on the ground TEMP the high temperature for the day in degrees F . WEEKDAY an indicator variable, weekday = 1 , weekend = 0 Dependent variable is Skiers \mathrm { R } squared = 25.4 \% \quad \mathrm { R } squared (adjusted) = 16.8 \% \mathrm { s } = 125.1 with 30 - 4 = 26 degrees of freedom \begin{array}{lrrrr} \text { Variable } & \text { Coefficient } & \text { SE(Coeff) } & \text { t-ratio } & \text { p-value } \\ \text { Constant } & 559.869 & 76.78 & 7.29 & <0.0001 \\ \text { Snow } & 1.424 & 2.70 & 0.53 & 0.6019 \\ \text { Temp } & -1.604 & 2.77 & -0.58 & 0.5677 \\ \text { Weekend } & 147.349 & 51.86 & 2.84 & 0.0086 \end{array} -What is the predicted number of skiers for a Saturday with a temperature of 40° F. and a snow cover of 25 inches?$

\begin{array}{lrrrr}\text { Variable } & \text { Coefficient } & \text { SE(Coeff) } & \text { t-ratio } & \text { p-value } \\\text { Constant } & 559.869 & 76.78 & 7.29 & <0.0001 \\\text { Snow } & 1.424 & 2.70 & 0.53 & 0.6019 \\\text { Temp } & -1.604 & 2.77 & -0.58 & 0.5677 \\\text { Weekend } & 147.349 & 51.86 & 2.84 & 0.0086\end{array}

$The regression below predicts the daily number of skiers who visit a small ski resort based on three explanatory variables. The data is a random sample of 30 days from the past two ski seasons. The variables are: SKIERS the number of skiers who visit the resort on that day SNOW the number of inches of snow on the ground TEMP the high temperature for the day in degrees F . WEEKDAY an indicator variable, weekday = 1 , weekend = 0 Dependent variable is Skiers \mathrm { R } squared = 25.4 \% \quad \mathrm { R } squared (adjusted) = 16.8 \% \mathrm { s } = 125.1 with 30 - 4 = 26 degrees of freedom \begin{array}{lrrrr} \text { Variable } & \text { Coefficient } & \text { SE(Coeff) } & \text { t-ratio } & \text { p-value } \\ \text { Constant } & 559.869 & 76.78 & 7.29 & <0.0001 \\ \text { Snow } & 1.424 & 2.70 & 0.53 & 0.6019 \\ \text { Temp } & -1.604 & 2.77 & -0.58 & 0.5677 \\ \text { Weekend } & 147.349 & 51.86 & 2.84 & 0.0086 \end{array} -What is the predicted number of skiers for a Saturday with a temperature of 40° F. and a snow cover of 25 inches?$
-What is the predicted number of skiers for a Saturday with a temperature of 40° F. and a
snow cover of 25 inches?

Which of These Random Variables Has a Binomial Model

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