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Chapter 9

스터디 가이드 - 스마트 노트

자료에 맞춘 맞춤형 노트, 핵심 정의, 예시, 맥락을 확장해 제공합니다.

Hypothesis Testing for One Sample

Decision Rules for Hypothesis Testing

When conducting hypothesis tests for a single population mean, the decision to reject or not reject the null hypothesis (H0) is based on comparing the calculated test statistic (z or t) to a critical value from the appropriate distribution. The rules differ for two-tailed and one-tailed tests, and for whether the population standard deviation is known or unknown.

Decision Rules for the z-Test Statistic (σ Known)

  • Two-tailed test: Reject H0 if ; otherwise, do not reject H0.

  • One-tailed test (upper): Reject H0 if ; otherwise, do not reject H0.

  • One-tailed test (lower): Reject H0 if ; otherwise, do not reject H0.

Decision rules for z-test statistic

Decision Rules for the t-Test Statistic (σ Unknown)

  • Two-tailed test: Reject H0 if ; otherwise, do not reject H0.

  • One-tailed test (upper): Reject H0 if ; otherwise, do not reject H0.

  • One-tailed test (lower): Reject H0 if ; otherwise, do not reject H0.

Decision rules for t-test statistic

One-Sample z-Test: Population Standard Deviation Known

The one-sample z-test is used when the population standard deviation (σ) is known. The test statistic is calculated as:

  • Test Statistic Formula:

  • Where: = sample mean = hypothesized population mean = population standard deviation = sample size

z-test formula and decision rule

Example: Upper-Tailed z-Test

Suppose a manufacturer claims that the average life of a light bulb is at least 8,000 hours. A sample of 36 bulbs has a mean life of 8,120 hours and σ = 500 hours. Test at α = 0.05 if the average life exceeds 8,000 hours.

  • Step 1: State hypotheses:

  • Step 2: Significance level:

  • Step 3: Calculate test statistic:

  • Step 4: Critical value:

  • Step 5: Compare: → Do not reject

  • Step 6: Conclusion: Not enough evidence to support the claim that the average life exceeds 8,000 hours.

Excel Z test for the mean, sigma knownMegaStat menu for hypothesis testMegaStat input for hypothesis testMegaStat output for hypothesis testStatCrunch one sample z summaryStatCrunch z-test p-value plot

One-Sample z-Test: Two-Tailed Example

Suppose the mean data use for smartphone users is claimed to be 1.8 GB/month. A sample of 49 users has a mean of 1.86 GB, σ = 0.2 GB. Test at α = 0.05 if the average use differs from 1.8 GB.

  • Step 1: ,

  • Step 2:

  • Step 3:

  • Step 4: Critical value:

  • Step 5: → Reject

  • Step 6: Conclusion: Sufficient evidence to reject the null hypothesis; average use is not equal to 1.8 GB.

Excel Z test for the mean, sigma known, two-tailedMegaStat menu for hypothesis testMegaStat input for two-tailed testMegaStat output for two-tailed testStatCrunch one sample z summary, two-tailedStatCrunch z-test p-value plot, two-tailed

One-Sample z-Test: Lower-Tailed Example

Lindsay wants to test if the average wait time at her restaurant is less than 20 minutes. A sample of 45 wait times has a mean of 18.3 minutes, σ = 5 minutes. Test at α = 0.05.

  • Step 1: ,

  • Step 2:

  • Step 3:

  • Step 4: Critical value:

  • Step 5: → Reject

  • Step 6: Conclusion: Evidence supports that the average wait time is less than 20 minutes.

Excel Z test for the mean, sigma known, lower-tailedMegaStat menu for hypothesis testMegaStat input for lower-tailed testMegaStat output for lower-tailed testStatCrunch one sample z summary, lower-tailed

One-Sample t-Test: Population Standard Deviation Unknown

When the population standard deviation is unknown, the t-test is used. The test statistic is:

  • Test Statistic Formula:

  • Where: = sample standard deviation Degrees of freedom:

t-test formula and decision rule

Summary Table: Decision Rules for z and t Tests

Test

Hypothesis

Condition

Conclusion

Two-tail (z or t)

or

Reject

Two-tail (z or t)

or

Do not reject

One-tail (upper)

or

Reject

One-tail (upper)

or

Do not reject

One-tail (lower)

or

Reject

One-tail (lower)

or

Do not reject

Additional info: The images included above are directly relevant to the calculation and interpretation of hypothesis tests for one sample, including the use of statistical software (Excel, MegaStat, StatCrunch) for hypothesis testing. The summary table provides a concise reference for decision rules in both z and t tests.

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