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There are no words that create the sound of steam, steam is silent.
Some are ceramic and some are hard plastic
Many properties of electronmagnetic waves can be explained by a wave model. However, some properties can be explained by a particle model.
You and your clothes absorb some of the photons, creating the colors you see.
it might eat you
Decision variables are the variables within a model that one can control. They are not random variables. For example, a decision variable might be: whether to vaccinate a population (TRUE or FALSE); the amount of budget to spend (a continuous variable between some minimum and maximum); or how many cars to have in a car pool (a discrete variable between some minimum and maximum).
Temperature, water, growth, color.
The time of year or the natural habitat could be some.
Predetermined variables are determined by factors in the past and cannot be changed, while exogenous variables are determined by factors outside the model being analyzed. Predetermined variables are considered to be endogenous in the context of a model, while exogenous variables are considered to be exogenous.
Controlled variables are things that may effect the outcome of an experiment, like temperature are pressure or the amount of some substance used. Dependent variables are those which change due to the conditions mentioned above. These might be speed of the reaction, or the quantity of some product.
You create a statistical model using data for any variable that you think might affect room occupancy. Where direct data are not available, you could use proxies. Using these data you could carry out a multiple regression which would give you the best variables to use and an equation, using those variables, to forecast occupancy.Some variables that may be of use:SeasonNumber of hotels/room in townYour prices, offersOther hotels' pricesYour quality (star) ratingCustomer satisfaction, your reputationLocation (your and others')Amenities (your and others')Special events - eg conferences, conventionsAdvertisingTies with airlines, car rental etc.You create a statistical model using data for any variable that you think might affect room occupancy. Where direct data are not available, you could use proxies. Using these data you could carry out a multiple regression which would give you the best variables to use and an equation, using those variables, to forecast occupancy.Some variables that may be of use:SeasonNumber of hotels/room in townYour prices, offersOther hotels' pricesYour quality (star) ratingCustomer satisfaction, your reputationLocation (your and others')Amenities (your and others')Special events - eg conferences, conventionsAdvertisingTies with airlines, car rental etc.You create a statistical model using data for any variable that you think might affect room occupancy. Where direct data are not available, you could use proxies. Using these data you could carry out a multiple regression which would give you the best variables to use and an equation, using those variables, to forecast occupancy.Some variables that may be of use:SeasonNumber of hotels/room in townYour prices, offersOther hotels' pricesYour quality (star) ratingCustomer satisfaction, your reputationLocation (your and others')Amenities (your and others')Special events - eg conferences, conventionsAdvertisingTies with airlines, car rental etc.You create a statistical model using data for any variable that you think might affect room occupancy. Where direct data are not available, you could use proxies. Using these data you could carry out a multiple regression which would give you the best variables to use and an equation, using those variables, to forecast occupancy.Some variables that may be of use:SeasonNumber of hotels/room in townYour prices, offersOther hotels' pricesYour quality (star) ratingCustomer satisfaction, your reputationLocation (your and others')Amenities (your and others')Special events - eg conferences, conventionsAdvertisingTies with airlines, car rental etc.
It depends on the way that the subject is modelled as to how many and what are the variables involved. Some models are incomplete and have only a few variables. The smallest model that I know that is comnplete has 19 variables. They are all money flows which are opposite to the value of the goods, services and valuable legal documents that flow in the opposite direction between the same entities.
Pharmacists and the makers of drugs use polynomial division. They use this type of division to help create formulas to make sure that the proper amount of drug is being distributed to the patients depending on the variables involved.
Because it will perform a test of how two variables might be related. This is when you are doing a real experiment.
The idea is to work with the same variables, but it is possible that some of the variables are missing in some of the equations.
To model problems that are more complicated than data tables can handle, involving as many as 32 variables, you can use the services of the Scenario Manager in Microsoft Office Excel 2003. A scenario is a named combination of values that is assigned to one or more variable cells in a what-if model. You can use the Scenario Manager to enter variable figures in your what-if model and watch the effect on dependent computed values.Here are some of the things you can do with the Scenario Manager in Excel:Create multiple scenarios for a single what-if model, each with its own sets of variables. You can create as many scenarios as your model necessitates.Distribute a what-if model to members of your team so that they can add their own scenarios. Then you can collect the versions and merge all the scenarios onto a single worksheet.Using Scenario Summary, examine relationships between scenarios created by multiple users.
which day of the week it falls on, the age of the kids in your area, the weather, local safety issues.