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Question 1 of 10
1. Question
What do you mean when the risks are heterogeneous?
Correct
When different risks have different risk parameters, the combination is known to be heterogeneous, which means being different.
Incorrect
When different risks have different risk parameters, the combination is known to be heterogeneous, which means being different.
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Question 2 of 10
2. Question
What is the estimator of E[m(θ)]?
Correct
The estimator of E[m(θ)] means that it is the overall mean of the claims data for all the risks in the collective.
Incorrect
The estimator of E[m(θ)] means that it is the overall mean of the claims data for all the risks in the collective.
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Question 3 of 10
3. Question
What do you mean by estimator of E[s2(θ)]?
Correct
The usual estimators of the structural parameters have E[m(θ)], E[s2(θ)], and Var[m(θ)]. The estimator of E[s2(θ)] is known to be the mean of the individual risk sample variances.
Incorrect
The usual estimators of the structural parameters have E[m(θ)], E[s2(θ)], and Var[m(θ)]. The estimator of E[s2(θ)] is known to be the mean of the individual risk sample variances.
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Question 4 of 10
4. Question
What is the estimator of Var[m(θ)]?
Correct
The estimator of Var[m(θ)] is the sample variance of the risk means corrected for bias – the correction is a reduction given by the estimator of E[s2(θ)] divided by n, the number of years data for each risk that is available.
Incorrect
The estimator of Var[m(θ)] is the sample variance of the risk means corrected for bias – the correction is a reduction given by the estimator of E[s2(θ)] divided by n, the number of years data for each risk that is available.
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Question 5 of 10
5. Question
What does the large value of E[s2(θ)] imply?
Correct
A large value of E[s2(θ)] implies large variability from year to year within risks. This implies low credibility for the data from the particular risk
concerned and implies a low value of credibility.Incorrect
A large value of E[s2(θ)] implies large variability from year to year within risks. This implies low credibility for the data from the particular risk
concerned and implies a low value of credibility. -
Question 6 of 10
6. Question
What does the large value of Var[m(θ)] imply?
Correct
On the opposite of a large value of E[s2(θ)] implication result, the large value of Var[m(θ)] implies that data from other risks are not very relevant or are not informative or do not have a reliable source which in turn implies high credibility for the data from the individual risk concerned, and therefore there is a high value of the credibility factor.
Incorrect
On the opposite of a large value of E[s2(θ)] implication result, the large value of Var[m(θ)] implies that data from other risks are not very relevant or are not informative or do not have a reliable source which in turn implies high credibility for the data from the individual risk concerned, and therefore there is a high value of the credibility factor.
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Question 7 of 10
7. Question
Insurance data is usually organized in a two-way array, which can be identified as?
Correct
Insurance data are organized into two types of information, generally known as cases and variables. Cases include policies, claims, individuals, or accidents. Variables include the level of injury, sex, dollar cost, whether there is legal representation, and many others.
Incorrect
Insurance data are organized into two types of information, generally known as cases and variables. Cases include policies, claims, individuals, or accidents. Variables include the level of injury, sex, dollar cost, whether there is legal representation, and many others.
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Question 8 of 10
8. Question
What do you mean by the Continuous variables?
Correct
. Continuous variables are those called “interval” variables to indicate they can take on values anywhere in an interval of the real line.
Incorrect
. Continuous variables are those called “interval” variables to indicate they can take on values anywhere in an interval of the real line.
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Question 9 of 10
9. Question
What do you understand by Bernoulli variables, which are also known as binary variables?
Correct
Bernoulli variables or also known as Binary variables indicate the presence or absence of an attribute, or occurrence or non-occurrence of an event of interest such as a claim or fatality,and they are often coded as “0” and “1”.
Incorrect
Bernoulli variables or also known as Binary variables indicate the presence or absence of an attribute, or occurrence or non-occurrence of an event of interest such as a claim or fatality,and they are often coded as “0” and “1”.
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Question 10 of 10
10. Question
Generalized linear modeling is a methodology used for modeling relationships, which type of data does it analyze?
Correct
Generalized linear modeling- GLM, is a method used for the modeling of relationships between different variables, for example, it generalizes the normal linear model, by straightening some of its restrictive assumptions, and it also provides methods for the analysis of non-normal data.
Incorrect
Generalized linear modeling- GLM, is a method used for the modeling of relationships between different variables, for example, it generalizes the normal linear model, by straightening some of its restrictive assumptions, and it also provides methods for the analysis of non-normal data.