Describe the various types of time-series and associative forecasting models. Which types of organizations are each...

Describe the various types of time-series and associative forecasting models. Which types of organizations are each of these most applicable to and why?

Expert Solution

The types of time-series models are:

Naïve approach, moving averages, exponential smoothing, and trend projection. An associativeforecasting model is linear regression. The naïve approach is the simplest technique that assumes that the next period will equal to the demand of the most recent period. Moving averages uses an average of data to forecast the upcoming period. Exponential smoothing takes little past data and is weighted by exponential formula. Trend projection uses past data history to set data point to create a trend. Using this trend you are able to project the future slope of the line. Lastly, linear regression is used to compare the relationship between a dependent and an independent variable to find a linear line through data points. I believe any type of business could use time-series forecasting. It is used just to predict the future by past data, which any business from retail to even the stock market could partake in. Associative forecasting is something that real estate and mortgage lenders could us. I currently work in the industry and we use interest rates to predict the housing market and home refinancing.

keosha answered 2 hours ago

Describe the various types of time-series and associative forecasting models. Which types of organizations are each...

Describe the various types of time-series and associative forecasting models. Which types of organizations are each of these most applicable to, and why?

If your manager asked you the differences between time series forecasting models and regression-based forecasting models,...

If your manager asked you the differences between time series forecasting models and regression-based forecasting models, what would you tell him/her?

1.A) In abut 5 lines explain how associative methods of forecasting differ from Time series methods...

1.A) In abut 5 lines explain how associative methods of forecasting differ from Time series methods of forecasting. B) Which one would you use to explain how the demand for pork might affect the demand for beef? 2. What all does Hard Rock Cafe's Point of Sale (POS) system capture? At what level is the information aggregated? 3. A) In about 5 lines, discuss the key differences between Time Series method of forecasting and Qualitative Methods of forecasting. B) Name...

Observations of any variable recorded over a sequential period of time are considered time-series. Forecasting models,...

Observations of any variable recorded over a sequential period of time are considered time-series. Forecasting models, used to estimate values for some future period, are generally classified as either qualitative or quantitative. Use the internet to research the differences between a qualitative forecasting model and a quantitative forecasting model. Assume you are an executive of a large transportation company, and your firm's profit is highly sensitive to fuel cost. The price of gasoline and diesel changes daily, however, your customers...

What do you understand by a time series forecasting approach? Describe each of the four factors...

What do you understand by a time series forecasting approach? Describe each of the four factors in this approach and indicate how they are determined

Forecasting can be classified into four basic types: Qualitative, Time series, Causal relationship, and simulation. Determine...

Forecasting can be classified into four basic types: Qualitative, Time series, Causal relationship, and simulation. Determine which one or two styles best fits an electrical distribution companies forecast needs. Why?

State the various types of business organizations that exist and explain the distinguishing characteristics of each.

List and describe the various methods of forecasting exchange rates

Describe the various budgeting approaches and the types of information each requires

A time series model is a forecasting technique that attempts to predict the future values of...

A time series model is a forecasting technique that attempts to predict the future values of a variable by using only historical data on that one variable. Here are some examples of variables you can use to forecast. You may use a different source other than the ones listed (be sure to reference the website). There are many other variables you can use, as long as you have values that are recorded at successive intervals of time. Currency price GNP...

Question

Describe the various types of time-series and associative forecasting models. Which types of organizations are each...

Solutions

Expert Solution

Related Solutions

Describe the various types of time-series and associative forecasting models. Which types of organizations are each...

If your manager asked you the differences between time series forecasting models and regression-based forecasting models,...

1.A) In abut 5 lines explain how associative methods of forecasting differ from Time series methods...

Observations of any variable recorded over a sequential period of time are considered time-series. Forecasting models,...

What do you understand by a time series forecasting approach? Describe each of the four factors...

Forecasting can be classified into four basic types: Qualitative, Time series, Causal relationship, and simulation. Determine...

State the various types of business organizations that exist and explain the distinguishing characteristics of each.

List and describe the various methods of forecasting exchange rates

Describe the various budgeting approaches and the types of information each requires

A time series model is a forecasting technique that attempts to predict the future values of...