State and check the following conditions for performing a significance test about a population proportion:

1. Random Condition: The data should come from a random sample or a randomized experiment.

2. 10% Condition: When sampling without replacement, ensure that the sample size is no more than 10% of the population.

3. Large Counts Condition: The sample size should be large enough such that both [tex]np \geq 10[/tex] and [tex]n(1-p) \geq 10[/tex], where [tex]n[/tex] is the sample size and [tex]p[/tex] is the population proportion.

The conditions for performing a significance test about a population proportion include the Random, 10%, and Large Counts conditions. Random means that the samples must be simple random samples that are independent. 10% indicates that there must be at least 5 successes and failures for each sample. Large Counts means that the population size should be at least 10 or 20 times the size of the sample.

Explanation:

The conditions for performing a significance test about a population proportion are as follows:

Random: The samples must be simple random samples that are independent.
10%: The number of successes and failures for each sample must be at least 5.
Large Counts: The population must be at least 10 or 20 times the size of the sample to avoid over-sampling.

To check these conditions, ensure that the samples are randomly selected and independent, and check if the number of successes and failures in each sample is at least 5. Also, verify that the population size is large enough compared to the sample size.

Learn more about Significance test about a population proportion here:

https://brainly.com/question/35494785

#SPJ11