Home / AP Statistics 6.9 Justifying a Claim Based on a Confidence Interval for a Difference of Population Proportions Study Notes

AP Statistics 6.9 Justifying a Claim Based on a Confidence Interval for a Difference of Population Proportions Study Notes

AP Statistics 6.9 Justifying a Claim Based on a Confidence Interval for a Difference of Population Proportions Study Notes- New syllabus

AP Statistics 6.9 Justifying a Claim Based on a Confidence Interval for a Difference of Population Proportions Study Notes -As per latest AP Statistics Syllabus.

LEARNING OBJECTIVE

  • An interval of values should be used to estimate parameters, in order to account for uncertainty.

Key Concepts:

  •  Interpret a Confidence Interval for a Difference of Proportions
  • Justify a Claim Based on a Confidence Interval for a Difference of Proportions

AP Statistics -Concise Summary Notes- All Topics

 Interpret a Confidence Interval for a Difference of Proportions

 Interpret a Confidence Interval for a Difference of Proportions

A confidence interval for the difference in population proportions \( p_1 – p_2 \) provides a range of plausible values for the true difference between two populations. It reflects how confident we are that this interval captures the actual difference in proportions.

  • The interval is based on the sample data (\( \hat{p}_1, \hat{p}_2 \)) and accounts for sampling variability.
  • The form of the interval is:

\( (\hat{p}_1 – \hat{p}_2) \pm z^* \sqrt{\dfrac{\hat{p}_1 (1 – \hat{p}_1)}{n_1} + \dfrac{\hat{p}_2 (1 – \hat{p}_2)}{n_2}} \)

Interpretation:

  • We are C% confident that the true difference in population proportions \( p_1 – p_2 \) lies within the calculated interval.
  • In repeated random sampling with the same sample sizes, about C% of such intervals would capture the true difference.
  • The interpretation must always refer to:
    • the populations being compared,
    • the parameters of interest (\( p_1 – p_2 \)), and
    • the context of the situation.

Example:

A survey found that 60% of urban residents and 52% of rural residents support recycling incentives. A 95% confidence interval for \( p_1 – p_2 \) (urban − rural) is calculated as (0.01, 0.15).

Interpret the confidence interval.

▶️ Answer / Explanation
  • We are 95% confident that the true difference in proportions of urban and rural residents who support recycling lies between 0.01 and 0.15.
  • This means that the proportion of urban supporters is likely between 1% and 15% higher than that of rural supporters.
  • In repeated random sampling, about 95% of such intervals would capture the true difference in support rates.

Justify a Claim Based on a Confidence Interval for a Difference of Proportions

Justify a Claim Based on a Confidence Interval for a Difference of Proportions

A confidence interval can be used to determine whether the data provide convincing evidence for a difference between two population proportions.

  • If the confidence interval does not include 0:
    • There is statistical evidence of a difference between the population proportions.
    • The direction of the interval (positive or negative) indicates which proportion is greater.
  • If the confidence interval includes 0:
    • There is no significant difference between the population proportions.
    • The observed difference could be due to random sampling variability.

Steps to Justify a Claim:

  1. State the claim being evaluated (e.g., “Group A has a higher proportion than Group B”).
  2. Examine whether 0 lies within the confidence interval for \( p_1 – p_2 \).
  3. Use the interval’s sign and range to determine whether the data support or fail to support the claim.

Example:

A researcher claims that a greater proportion of seniors than juniors prefer hybrid classes. A 95% confidence interval for \( p_1 – p_2 \) (seniors − juniors) is (0.03, 0.21).

▶️ Answer / Explanation
  • The interval is entirely positive (0.03 to 0.21), meaning \( p_1 – p_2 > 0 \).
  • This suggests that the proportion of seniors preferring hybrid classes is likely higher than that of juniors.
  • Because 0 is not contained in the interval, the data support the researcher’s claim.

Conclusion: We are 95% confident that the proportion of seniors preferring hybrid learning is between 3% and 21% higher than that of juniors — justifying the claim.

Example:

A school claims that male and female students differ in their preference for online classes. A 95% confidence interval for \( p_1 – p_2 \) (male − female) is (−0.12, 0.08).

▶️ Answer / Explanation
  • The interval includes 0, which means the true difference could be positive, negative, or zero.
  • Therefore, there is insufficient evidence to conclude that the proportions differ significantly.
  • The data do not support the school’s claim.

Conclusion: Because 0 lies within the interval, the difference in preference between males and females could be due to random variation.

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