Purchase Solution

Forecasting of Time Series Data

Not what you're looking for?

Ask Custom Question

The monthly number of permits granted for building houses in a large city is seasonal (there tend to be more permits granted for construction during spring and summer months than during winter months). The following table shows the monthly seasonal indexes for building permits:

JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
0.86 0.79 0.98 1.15 1.29 1.35 1.12 1.05 0.95 0.91 0.78 0.75

Using several years of permit data, beginning in April of 1999 (i.e., corresponds to April of ), an analyst reported that the trend line that describes the monthly permit data is of the form. Assuming that a multiplicative model can be used to describe the building permit data, generate a forecast for the number of building permits that you expect will be granted in January of 2004.

Purchase this Solution
Solution Summary

The solution provides step by step method for determining the time series forecasting. Formula for the calculation and interpretations of the results are also included. This solution is provided in an attached Word and Excel document.

Purchase this Solution
Free BrainMass Quizzes
Measures of Central Tendency

This quiz evaluates the students understanding of the measures of central tendency seen in statistics. This quiz is specifically designed to incorporate the measures of central tendency as they relate to psychological research.

Terms and Definitions for Statistics

This quiz covers basic terms and definitions of statistics.

Know Your Statistical Concepts

Each question is a choice-summary multiple choice question that presents you with a statistical concept and then 4 numbered statements. You must decide which (if any) of the numbered statements is/are true as they relate to the statistical concept.

Measures of Central Tendency

Tests knowledge of the three main measures of central tendency, including some simple calculation questions.

View More Free Quizzes
Related BrainMass Solutions

  • approaches to revenue forecasting.

    This forecasting method is based on historical data. Time series data is a sequence of data points measured typically at successive time points, usually taken at time intervals.

  • Relationships between time series and forecasting

    A time series is sequence of data points measured typically at successive times, spaced at time intervals. Time series analysis forecasting can be done to predict the future events based on the known past events.

  • Appropriate quantitative forecasting methods

    TIME SERIES FORECASTING METHODS Time series forecasting methods are based on analysis of historical data (time series: a set of observations measured at successive times or over successive periods).

  • Appropriate Forecasting Technique for Aldi Foods

    The time series forecasting method makes use of assumptions of past patterns observable within data, data points from which data is derived from for the forecasting.

  • Quantitative Forecasting Explained

    If this is a reasonable assumption, than quantitative time series forecasting is appropriate. In addition, time series data (a set of data points recorded over successive periods of time in the past) must be available.

  • Compare and contrast forecasting methods

    Comparison of various forecasting methods: Time series: A time series is a set of numbers that measures the status of some activity over time.

  • Seasonal forecasting



    If the data show time series variation indicating some seasonality (retail sales often do that) some times series analysis forecasting tool is likely appropriate.

  • Forecasting Models

    Statistical time-series models use past data to forecast future data.

  • Time Series

    334996 Time Series Forecasting methods Which of the following time series forecasting methods would not be used to forecast seasonal data?

  • Production Planning and Quality Management: Forecasting Techniques for Manychip

    Time-series forecasting assumes that a time series is a combination of a pattern and some random error.

View More Related Solutions