Stratified Random Sampling
Selection of restricted random samples in order to obtain a more accurate estimate of the expected loss (mean) than could be obtained by the selection of completely RANDOM SAMPLES. For example, assume it is the desire to obtain an accurate estimate of the average number of automobile accidents experienced by juniors in the Louisiana State University System. By selecting the proper size of random samples among the various colleges within the system, a more accurate estimate of the number of automobile accidents experienced by juniors system-wide can be obtained than by selecting the same total random sample from the system as a whole.
Popular Insurance Terms
Reductions in the value of property due to physical damage or destruction. ...
Provision found in current assumption whole life insurance policies under which the insurance company retains the contractual right to recalculate the premium (after a minimum period of ...
States that allow the placement of surplus lines only with insurance companies that the states have approved. ...
Insured losses that have occurred but have not been reported to a primary insurance company. These types of claims have a tremendous effect on a reinsurance treaty, which may be showing a ...
Fire that spreads substantial destruction. ...
Same as term Occurrence Basis: coverage, in liability insurance, for harm suffered by others because of events occurring while a policy is in force, regardless of when a claim is actually ...
Total of operating income plus realized capital gains (losses) from investment and underwriting operations minus federal income taxes. ...
basic feature of the social security act under which benefits paid are associated with the employee's earnings that have been taxed during the employment period. ...
Act that makes the liability cost for cleanup joint and several. Even if a party is only partially responsible for losses inflicted, that party may be liable for the payment of the total ...
Have a question or comment?
We're here to help.