In other words as a firm increases or decreases its output in the short-run, fixed factors remain constant. They are independent of output in the short-run. Machines, factory buildings, plants, permanent employees etc.
Member Deep, Two things: Ramsey and Schafer dedicated an entire chapter to the consequences of violating the assumptions for the two-sample t-test. The test assumes that the two samples are about the same size and drawn from a normal population with the same standard deviation with no skewness or kurtosis.
These conditions are almost never met. In practice, t-tests are pretty robust even if the samples are non-normal or the standard deviations are not equal. Indeed, the two-sample t-test can be run two slightly different ways depending on whether the variances of the two samples are equal or not.
The conclusions are usually the same whichever way you run the test.
Variable Factors Variable factors are those factor inputs which change with the change with the change of output in the short run. Raw materials, labour, fuel, power etc. are the examples of variable factors. The issue of fixed and random factors is currently making itself felt in an area called group randomized trials. An example of a group randomized study is a comparison of teaching methods in which randomization is achieved by randomizing classes to methods. When comparing fixed costs to variable costs, or when trying to determine whether a cost is fixed or variable, simply ask whether or not the particular cost would change if the company stopped its production or primary business activities.
The way to do this is to generate very large subsets of data with particular parameters, differences in means, standard deviations, skewness, kurtosis, etc. Ramsey and Schafer conducted these tests using subgroups with different combinations of skewness, standard deviations, and sample sizes. In general they found that if only one of the assumptions of equal sample size, kurtosis, skewness and standard deviation are violated, then the test is still valid.
If two of the assumptions are violated, then the test MAY still be valid.
If three or more assumptions are violated, then the test becomes unreliable. To be safe, making sure the number of samples in each subgroup is more than about 30 will cover a multitude of sins.
Always have a look at your residuals plots to make sure the data is not pathologically weird. If you still have doubt, see if you can combine subgroups into larger groups and run the two-sample t-test. June 9, at 4:Fixed factors can be thought of in terms of differences.
The effect of a categorical fixed factor is defined by differences from the overall mean, and the effect of a continuous fixed factor is defined by its slope–how the mean of the dependent variable differs with alternate values of the factor. It's much easier to budget for fixed expenses than a variable expense or discretionary expense.
Typical household fixed expenses are mortgage or rent payments, . When comparing fixed costs to variable costs, or when trying to determine whether a cost is fixed or variable, simply ask whether or not the particular cost would change if the company stopped its production or primary business activities.
The issue of fixed and random factors is currently making itself felt in an area called group randomized trials.
An example of a group randomized study is a comparison of teaching methods in which randomization is achieved by randomizing classes to methods. Factors can either be fixed or random. A factor is fixed when the levels under study are the only levels of interest.
A factor is random when the levels under study are a random sample from a larger population and the goal of the study is to make a statement regarding the larger population.
Jun 10, · In Doe, randomization only helps keeps the random variable from covarying with (or unduly) influencing the observed effects of the fixed factors. In traditional ANOVA or regression you merely put the variable in the non-orthogonal model to observe its potential effect.