The mean of a random sample of 18 test scores is x_bar. The standard deviation of the population of all test scores is sigma= 6. Under what condition can you use a z-test to decide whether to reject a claim that the population mean is mu=88?
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Step 1: Understand the z-test conditions. A z-test is appropriate when the population standard deviation (σ) is known, the sample size is sufficiently large (typically n ≥ 30), or the population is normally distributed regardless of sample size.
Step 2: Check if the population standard deviation (σ) is provided. In this problem, σ = 6 is given, which satisfies one of the conditions for using a z-test.
Step 3: Evaluate the sample size (n). The sample size is n = 18, which is less than 30. Therefore, the z-test can only be used if the population of test scores is normally distributed.
Step 4: Confirm the normality of the population distribution. If the population of test scores is known to be normally distributed, then the z-test can be used even with a sample size of n = 18.
Step 5: Conclude the condition for using the z-test. You can use the z-test to decide whether to reject the claim that the population mean is μ = 88 if the population of test scores is normally distributed and the population standard deviation (σ = 6) is known.
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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Z-Test
A Z-test is a statistical method used to determine if there is a significant difference between the means of two groups, or between a sample mean and a known population mean. It is applicable when the population standard deviation is known, and the sample size is sufficiently large (typically n > 30) or when the population is normally distributed, allowing for the use of the standard normal distribution.
Probability From Given Z-Scores - TI-84 (CE) Calculator
Central Limit Theorem
The Central Limit Theorem states that the distribution of the sample mean will approach a normal distribution as the sample size increases, regardless of the population's distribution, provided the sample size is large enough (usually n ≥ 30). This theorem justifies the use of the Z-test for sample means, as it allows for the assumption of normality in the sampling distribution.
The population standard deviation (σ) is a measure of the dispersion or spread of a set of values in a population. In hypothesis testing, knowing the population standard deviation is crucial for calculating the Z-score, which helps determine how far the sample mean is from the population mean under the null hypothesis. In this case, σ = 6 is provided, allowing for the application of the Z-test.