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Survey Sampling and Inference: Hypothesis Testing for Population Means (Chapter 7 Review)

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Survey Sampling and Inference

Hypothesis Testing for Population Means

This section reviews the process of hypothesis testing for population means using sample data, focusing on the application of the one-sample t-test in a real-world context.

Formulating Hypotheses

  • Null Hypothesis (H0): The null hypothesis states that there is no change or effect. In this scenario, it asserts that the mean years of experience among nursing staff is still 12 years.

  • Alternative Hypothesis (HA): The alternative hypothesis posits that the mean years of experience has increased compared to 12 years.

Statistical Notation:

Example: Testing whether the average years of experience for nurses in 2024 is greater than the previously reported average of 12 years.

Appropriateness of the One-Sample t-Test

  • One-sample t-test: Used to compare the mean of a single sample to a known value (population mean) when the population standard deviation is unknown.

  • Conditions:

    • Sample is randomly selected.

    • Population standard deviation is unknown.

    • Sample size is moderate (n = 30), which is generally sufficient for the Central Limit Theorem to apply.

  • Conclusion: A one-sample t-test is appropriate because the sample mean is being compared to a known population mean, and the sample standard deviation is used as an estimate.

Example: Comparing the mean years of experience from a sample of 30 nurses to the historical mean of 12 years.

Calculating the t-Test Statistic

  • Formula:

  • = sample mean = 15

  • = population mean under H0 = 12

  • = sample standard deviation = 10

  • = sample size = 30

Calculation:

Rounded to three decimal places:

Interpreting Results and Drawing Conclusions

  • Critical t-value: At a 0.05 significance level with 29 degrees of freedom, the critical value is 2.045.

  • p-value: The p-value associated with the calculated t-statistic is 0.0181.

  • Decision Rule:

    • If the p-value is less than the significance level (), reject the null hypothesis.

    • If the t-statistic exceeds the critical value, also reject the null hypothesis.

  • Conclusion in Context: Since the p-value (0.0181) is less than 0.05, there is sufficient evidence to conclude that the mean years of experience among the hospital's nursing staff has increased compared to 12 years.

Example: The nurse manager can report that, based on the sample, the average years of experience for nurses is significantly higher than the previous average.

Summary Table: Hypothesis Testing Steps

Step

Description

Application to Example

1. State Hypotheses

Formulate null and alternative hypotheses

,

2. Select Test

Choose appropriate statistical test

One-sample t-test

3. Calculate Statistic

Compute t-statistic using sample data

4. Compare to Critical Value / p-value

Assess significance

Critical value = 2.045; p-value = 0.0181

5. Draw Conclusion

Interpret results in context

Mean years of experience has increased

Additional info: The one-sample t-test is robust to moderate deviations from normality, especially with sample sizes of 30 or more.

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