In March 2015, a Nielsen global online survey "found that consumers are increasingly willing to pay more for socially responsible products."11 Over 30,000 people in 60 countries were polled about their purchasing habits, and 66% of respondents said that they were willing to pay more for products and services from companies who are committed to positive social and environmental impact. We are interested in estimating the proportion of all consumers willing to pay more. Give notation for the quantity we are estimating, notation for the quantity we are using to make the estimate, and the value of the best estimate. Be sure to clearly define any parameters in the context of this situation.

[tex]p[/tex] who represent the true proportion of respondents said that they were willing to pay more for products and services from companies who are committed to positive social and environmental impact

For this case we have an estimation given for this parameter. The estimation comes from a sample of 30000 people selected in 60 countries and they got:

[tex]\hat p = 0.66[/tex]

This value represent the best estimator for the true proportion since is an unbiased estimator of the real parameter:

[tex] E(\hat p) = p[/tex]

Step-by-step explanation:

For this case the parameter of interest is given by:

[tex]p[/tex] who represent the true proportion of respondents said that they were willing to pay more for products and services from companies who are committed to positive social and environmental impact

For this case we have an estimation given for this parameter. The estimation comes from a sample of 30000 people selected in 60 countries and they got:

[tex]\hat p = 0.66[/tex]

This value represent the best estimator for the true proportion since is an unbiased estimator of the real parameter:

[tex] E(\hat p) = p[/tex]

For this case if we want to test if the population proportion is equal to an specified value we can use the one sample z test for a proportion:

Null hypothesis:[tex]p=p_0[/tex]

Alternative hypothesis:[tex]p \neq p_o[/tex]

When we conduct a proportion test we need to use the z statisitc, and the is given by:

[tex]z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}}[/tex] (1)

The One-Sample Proportion Test is used to assess whether a population proportion [tex]\hat p[/tex] is significantly different from a hypothesized value [tex]p_o[/tex].