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# Test of hypothesis for proportions and standard error

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Nationally the proportion of American households with income above \$100,000 is 10%. A researcher in State of California finds that out of a sample of 300 households , 35 have income above \$ 100,000. Can it be concluded from this sample that the proportion of households in california with income of \$100,000 exceeds the proportion of homes eith income of \$100,000 in the rest of the country.Test to a significance of 10%.Calculate p value. Which type of error- Type I or II.What are the consequences of commiting that type of error.

Based on the definition of a Type I or Type II error, which error could have been commited based on the results of the hypothesis test. What are the potential consequences of committing that error for this situation.

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Nationally the proportion of American households with income above \$100,000 is 10%. A researcher in State of California finds that out of a sample of 300 households , 35 have income above \$ 100,000. Can it be concluded from this sample that the proportion of households in california with income of \$100,000 exceeds the proportion of homes eith income of \$100,000 in the rest of the country.Test to a significance of 10%. Calculate p value. Which type of error- Type I or II.What are the consequences of ...

#### Solution Summary

The solution carries out a one sample hypothesis test for proportions.

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