METHODS AND APPARATUS TO CHARACTERIZE HOUSEHOLDS WITH MEDIA METER DATA

1 . A method to determine an average visitor parameter (AVP), comprising:

calculating, with a processor, an exposure proportion for a category of interest based on visitor exposure minutes and total exposure minutes;

calculating a tuning proportion for the category of interest based on household tuning minutes and total tuning minutes;

calculating expected exposure minutes for the category of interest based on a product of the total exposure minutes and the exposure proportion;

calculating expected tuning minutes for the category of interest based on a product of the total tuning minutes and the viewing proportion; and

determining an average visitor parameter (AVP) based on a ratio of the expected exposure minutes and the expected tuning minutes.

2 . A method as defined in claim 1 , further comprising applying the AVP to a Poisson distribution for candidate visitor quantities of interest.

3 . A method as defined in claim 2 , further comprising identifying a probability for each of the candidate visitor quantities of interest.

4 . A method as defined in claim 3 , further comprising calculating a cumulative probability for each of the candidate visitor quantities of interest.

5 . A method as defined in claim 3 , further comprising generating a first random value to identify one of the candidate visitor quantity values from the visitor quantities of interest.

6 . A method as defined in claim 5 , wherein the one of the candidate visitor quantity values corresponds to a point in a cumulative probability value associated with the visitor quantities of interest.

7 . A method as defined in claim 5 , further comprising generating a second random value to identify a bounded age of the one of the candidate visitor quantity values.

8 . An apparatus to determine an average visitor parameter (AVP), comprising:

a distribution engine to:

calculate an exposure proportion for a category of interest based on visitor exposure minutes and total viewing minutes;

calculate a tuning proportion for the category of interest based on household tuning minutes and total tuning minutes;

calculate expected exposure minutes for the category of interest based on a product of the total exposure minutes and the exposure proportion; and

calculate expected tuning minutes for the category of interest based on a product of the total tuning minutes and the viewing proportion; and

an AVP engine to determine an AVP based on a ratio of the expected exposure minutes and the expected tuning minutes.

9 . An apparatus as defined in claim 8 , wherein the distribution engine is to apply the AVP to a Poisson distribution for candidate visitor quantities of interest.

10 . An apparatus as defined in claim 9 , wherein the distribution engine is to identify a probability for each of the candidate visitor quantities of interest.

11 . An apparatus as defined in claim 10 , wherein the distribution engine is to calculate a cumulative probability for each of the candidate visitor quantities of interest.

12 . An apparatus as defined in claim 10 , further comprising a random number generator to generate a first random value to identify one of the candidate visitor quantity values from the visitor quantities of interest.

13 . An apparatus as defined in claim 12 , further comprising a visitor assignor to identify a candidate visitor quantity value based on a point in a cumulative probability value.

14 . An apparatus as defined in claim 12 , further comprising a random number generator to generate a second random value to identify a bounded age of one of the candidate visitor quantity values.

15 . A tangible machine readable storage medium comprising instructions that, when executed, cause a machine to at least:

calculate an exposure proportion for a category of interest based on visitor exposure minutes and total viewing minutes;

calculate a tuning proportion for the category of interest based on household tuning minutes and total tuning minutes;

calculate expected exposure minutes for the category of interest based on a product of the total exposure minutes and the exposure proportion;

calculate expected tuning minutes for the category of interest based on a product of the total tuning minutes and the viewing proportion; and

determine an average visitor parameter (AVP) based on a ratio of the expected exposure minutes and the expected tuning minutes.

16 . A storage medium as defined in claim 15 , wherein the instructions, when executed, further cause the machine to apply the AVP to a Poisson distribution for candidate visitor quantities of interest.

17 . A storage medium as defined in claim 16 , wherein the instructions, when executed, further cause the machine to identify a probability for each of the candidate visitor quantities of interest.

18 . A storage medium as defined in claim 17 , wherein the instructions, when executed, further cause the machine to calculate a cumulative probability for each of the candidate visitor quantities of interest.

19 . A storage medium as defined in claim 17 , wherein the instructions, when executed, further cause the machine to generate a first random value to identify one of the candidate visitor quantity values from the visitor quantities of interest.

20 . A storage medium as defined in claim 19 , wherein the instructions, when executed, further cause the machine to select a point in a cumulative probability value associated with the visitor quantities of interest from the one of the candidate visitor quantity values.

21 . A storage medium as defined in claim 19 , wherein the instructions, when executed, further cause the machine to generate a second random value to identify a bounded age of the one of the candidate visitor quantity values.