NAME: What Does It Take to Heat a New Room? TYPE: Time series SIZE: 81 observations, 13 variables DESCRIPTIVE ABSTRACT: In a residential home, energy consumption is closely related to the outdoor temperature and size of the house. In a home of a given size, temperature fluctuations and energy consumption vary fairly predictably over time. When homeowners add a room, other things being equal, utility usage should increase. This dataset permits students to estimate the energy demand and make forecasts for future months, as well as explore other relationships. The dataset contains natural gas and electricity usage data for a gas-heated single-family residence in the Boston area from September 1990 through May 1997, accompanied by monthly climatological data. The dataset is useful for illustrating the concepts and techniques of central tendency, dispersion, elementary time series analysis, correlation, simple and multiple regression, and variable transformations. SOURCES: Bay State Gas Co., Boston Edison, National Weather Service Taunton (MA) Regional Office. VARIABLE DESCRIPTIONS: Columns 1 - 7 Observation month (formatted mmm-yy) 10 - 11 Number of days in the month 14 - 15 Mean monthly temperature in Boston, in degrees Fahrenheit 17 - 20 Mean natural gas usage per day for the month, in therms 23 - 25 Total therms used for the month 28 - 29 Days in the gas company billing cycle for the month 31 - 34 Total kilowatt hours consumed in the month 36 - 39 Mean kilowatt hours per day for the month 42 - 43 Days in the electric company billing cycle for the month 46 Dummy variable for method of determining kwh for the month (0 = actual month-end meter reading, 1 = estimated reading) 48 - 51 Total heating degree days for the month 54 - 56 Total cooling degree days for the month 58 Dummy variable for the new room (0 = pre-addition, 1 = post-addition) Values are aligned and delimited by blanks. A therm is a standard measure of the heating capacity of a cubic foot of natural gas. Due to changes in air temperature during the year, the heating capacity varies from month to month. Degree days are a measure of temperature fluctuations that stimulate demand for heating or cooling. Specifically, heating degree days are sums of the absolute value of temperature deviations below a base temperature of 65 degrees Fahrenheit. For example, if the mean daily temperature were 60 degrees one day, that would represent five heating degree days. Conversely, cooling degree days sum the positive deviations from the base of 65 degrees. SPECIAL NOTES: For billing purposes, the gas utility month starts on the 18th of the month, while the electric utility month starts on the 12th. For example, the January gas bill refers to usage from December 18 through January 17 (approximately) and the electric bill for the same month refers to usage from December 12 through January 11 (approximately). The gas company calculates usage based on a monthly electronic reading of the gas meter, but the electric company meter reader visits the house every other month; in the alternate months, the electric company estimates electricity consumption. Sundays, holidays, and snowstorms can interrupt the schedule. In the summer months, the gas company issues one bill for July and August, and one for September and October. STORY BEHIND THE DATA: In our home, our furnace and water heater both use natural gas. We have a gas stove, but our clothes dryer is all-electric. In early 1996, we added a bedroom and enlarged the kitchen, and we were interested in estimating the additional consumption of natural gas attributable to the new room. The family remained the same size and did not change hot-water-use habits. The new construction improved the insulation in the affected areas, and several new lighting circuits were added. There were no other changes that would influence energy consumption. The major questions that prompted collection of the data are these: In an average month, do we use additional natural gas as a result of adding a room? If so, how much? In an average month, do we use additional electricity as a result of adding a room? If so, how much? Additional information about these data can be found in the "Datasets and Stories" article "What Does It Take to Heat a New Room? Estimating Utility Demand in a Home" in the _Journal of Statistics Education_ (Carver 1998). PEDAGOGICAL NOTES: This dataset can be useful at several points in an introductory course. The mean monthly temperature data offer a familiar example for descriptive techniques. The degree day variables can lead to very useful discussions of "what does this variable measure"? Simple time series plots of the gas and electricity consumption, as well as the various temperature measures, nicely illustrate seasonal variation. More substantially, the intent in compiling the data was causal modeling, and the relationship between outdoor temperature and energy consumption lends itself well to correlation and regression analysis. With multiple regression, the addition of the new room can be introduced into the model. Because gas consumption is theoretically flat above some high mean temperature, the dataset provides an example of the usefulness of piece-wise linear models or curvilinear transformations, and can illustrate the risks of ill-considered extrapolation. REFERENCE: A dataset including temperature and electricity consumption can be found in Chatterjee, S., Handcock, M., and Simonoff (1995), _A Casebook for a First Course in Statistics and Data Analysis_, New York: Wiley, pp. 177-184. SUBMITTED BY: Robert Carver Department of Business Administration Stonehill College 320 Washington Street Easton, MA 02357-1150