Question

Asked Feb 21, 2019

57 views

- The city wants to further develop the model to include the weather conditions of rainy, cloudy, or sunny.

Ice Rink Attendance |
Temperature (°F) |
Weather Condition |

140 |
45 |
Sunny |

110 |
40 |
Cloudy |

135 |
50 |
Cloudy |

120 |
40 |
Cloudy |

165 |
45 |
Sunny |

180 |
45 |
Sunny |

210 |
50 |
Sunny |

190 |
45 |
Cloudy |

170 |
40 |
Cloudy |

130 |
45 |
Rainy |

140 |
45 |
Cloudy |

80 |
35 |
Rainy |

120 |
45 |
Cloudy |

100 |
45 |
Rainy |

- What is the regression equation?
- Use the equation to forecast ice rink attendance if the temperature is 38°F and sunny.
- Should you keep weather condition in the model?

Step 1

**Introduction to linear regression analysis:**

Regression analysis is a collection of statistical procedures used to estimate the relationship among variables.

Suppose one variable is thought to be dependent on one or more other variables. Then, statistical methods can be used to form a model of this dependent variable, often called the response variable, on the independent variables, known as regressors or predictors. This procedure is called regression analysis.

Step 2

**Indicator variable:**

An indicator or a dummy variable is created for using a qualitative predictor variable in a regression model, which assigns a unique number to indicate each value or category of the qualitative predictor variable. If there are *k* categories, then (*k* – 1) indicator variables are required.

Step 3

**The given data:**

In this study, the ice rink attendance is the response variable, which depends upon temperature and weather condition.

Here, the weather condition is a categorical variable, having 3 categories- sunny, cloudy and rainy. As a result, 2 indicator variables must be used to model the weather conditi...

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