Optimizing One Sample Z-Test For Proportion | Meeting Conditions Like Random Sample And Normality

One Sample Z-Test for Proportion CONDITIONS

1. Random sample or assignment2. 10% Condition n ≤ 1/10(N)3. a) Population distribution is stated as NORMAL b) n ≥ 30 c) if n < 30, check graph of sample data to verify no strong skew or outliers

To perform a one sample z-test for proportion, there are a few conditions that should be met:

1. Random sample: The sample should be randomly selected from the population of interest. This means that each member of the population has an equal chance of being included in the sample.

2. Independent observations: Each observation in the sample should be independent of the others. This means that the value of one observation should not influence the value of any other observation.

3. Normality: The distribution of the sample proportion should be approximately normal. If the sample size is large enough (typically greater than 30), then this condition can be met by using the central limit theorem.

4. Success-failure condition: The number of successes and failures in the sample should be at least 10. This ensures that the distribution of the sample proportion is not too skewed.

If these conditions are met, then a one sample z-test can be performed to test a hypothesis about a population proportion.

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