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Would one expect more variance with a larger sample size in a chi distribution?
The larger your sample size, the less variance there will be. For instance, your information is going to be much more substantial if you took 1000 samples over 10 samples.
What is the variance of a inverse gamma distribution with alpha equals 2?
When alpha is 2 or less than 2 the variance of the inverse gamma doesn't exist. That is why when the variance is defined for the inverse gamma it always says "for α > 2". It is also the case that when alpha is 1 or less the mean of the inverse gamma doesn't exist. In order to really undertand what it means to say the variance doesn't exist (or the mean doesn't exist) you need to understand the mathematical definition of the variance (and of the mean). I don't know how to add the necessary symbols to clearly explain this. However, just briefly, mathematically both the mean and variance of the gamma density are definite integrals over the support of the density, which is 0 to infinity. In general, sometimes a definity integral over an infinite range (negative and/or positive) exists and sometimes it doesn't. In the case of the definite integral for the variance on the inverse gamma, when alpha less than or equal to 2, this integral doesn't exist.
What is recursive rule?
A recursive rule is one which can be applied over and over again to its own output
How do you use variance analysis?
When data is homogeneous over k independent samples of size n_i for i=1,2,...,k, the pooled variance is given by s_p^2=((n_1-1) s_1^2+(n_2-1) s_2^2+⋯(n_k-1) s_k^2)/(n_1+n_2+⋯+n_k-k)
How is this relevant to marketing Assume the frequency that a household purchases milk per year is a normal distribution with a mean of 12. Over time the mean stays the same but the variance decreases?
It should make marketing easier because the amount purchased has a smaller variance. This means that the numbers are closer to 12 and so there is less of a need to carry large stocks for when the demand is high.
If actual overhead for the year is 33451 and applied overhead is 32000 is the overhead variance over applied or under applied assuming the amount is immaterial how would you dispose of the variance?
Difference between actual overhead and applied overhead is as follows: Difference = 33451 - 32000 = 1450 Difference of variance will be charged to income statement.
What factors are important in determining whether a company is under or over organized?
Important factors in determining whether a company is under or over organized include the clarity of roles and responsibilities, the efficiency of communication channels, the adaptability to change, and the level of bureaucracy present within the organization. Over organization can stifle creativity and innovation, while under organization can lead to confusion and inefficiency. Balancing these factors is key to achieving optimal organizational effectiveness.
When a simple machine is used to perform a task what factors may be affected?
the amount of force needed to perform the task the distance over which the force is applied the direction in which the force is applied
When a simple machine is used to perform a task factors may be affected?
the amount of force needed to perform the task the distance over which the force is applied the direction in which the force is applied
What is a positive or negative variance of a budget?
A variance is the difference between the projected budget and the actual performance for a particular account. A negative variance means that the budgeted amount was greater than the actual amount spent. A positive variance means that the budgeted amount was less than the actual amount spent. Note there is some debate over whether a negative variance means an underrun or an overrun. The Project Management Institute, however, endorses the accepted convention that a negative variance is a bad thing, and a positive variance a good thing.
What are the two factors that can affect impulse?
The two factors that can affect impulse are the force applied and the duration of time over which the force is applied. A greater force or a longer duration of force application will result in a greater impulse.
State the two factors that determine the amount of work done on an object?
The two factors that determine the amount of work done on an object are the force applied to the object and the distance over which the force is applied. Work is calculated as the product of the force and the displacement of the object in the direction of the force.
What are the most important factors in determining the rate or weathering are?
The most important factors in determining the rate of weathering are the type of rock or mineral being weathered, the climate of the area (temperature and precipitation), the presence of vegetation, and the length of time the rock has been exposed to weathering processes. These factors influence the physical and chemical processes that break down rocks over time.
How far an object moves?
The distance an object moves depends on factors such as the force applied, the time over which the force is applied, and the object's mass. The distance traveled can be calculated using the equation distance = rate x time.
What factors effect elastic potential energy?
Factors that affect elastic potential energy include the stiffness of the material (determined by its spring constant), the amount of stretch or compression applied to the material, and the distance over which the force is applied. Additionally, the elastic potential energy is directly proportional to the square of the deformation distance.
What two factors do you need to know to calculate how much work was done in any situation?
You need to know the amount of force applied to an object and the distance over which the force was applied in order to calculate the work done in any situation. Work is calculated as the product of force and the distance over which the force is applied, given by the equation work = force × distance.
What is the significance of variance in statistics?
Variance is a measure of "relative to the mean, how far away does the other data fall" - it is a measure of dispersion. A high variance would indicate that your data is very much spread out over a large area (random), whereas a low variance would indicate that all your data is very similar.Standard deviation (the square root of the variance) is a measure of "on average, how far away does the data fall from the mean". It can be interpreted in a similar way to the variance, but since it is square rooted, it is less susceptible to outliers.
