2 Sample interval of proportions
Statistical Testing Assumptions
Assumption of Simple Random Sampling (SRS)
The first assumption is that samples taken are simple random samples.
Ensures unbiased representation from the population.
Population Size Requirements
Population size for both groups must be larger than 10 for meaningful analysis.
Denote populations as greater than ten for both group one and group two.
Changes in Statistical Testing Techniques
From Significant Tests to Non-Pooled Proportions
In significant tests, the null hypothesis states the samples come from the same population.
Now, hypotheses are tested independently since there is no presumption of common population.
Avoid pooling data as the underlying population assumption is no longer valid.
Conditions for Validity
Calculating Sample Sizes
Ensure sufficient sample sizes for both p-hat calculations:
n1 * p-hat1 ≥ 10
n1 * q-hat1 ≥ 10
n2 * p-hat2 ≥ 10
n2 * q-hat2 ≥ 10
Significant vs Confidence Interval
In significance tests, data may be pooled; however, in confidence intervals, data is kept separate.
Example Analysis: Parental Influence on Teen Smoking
Study Overview
A study published by the American Academy of Pediatrics examined the relationship between parental attitudes and teen smoking.
Initial group consisting of students who have never smoked and their parental attitudes was surveyed.
Findings after Two Years
Among students whose parents disapproved of smoking, 54 out of 284 became smokers.
Among those whose parents were lenient, 11 out of 41 became smokers.
Analysis Approach
Use a 95% confidence interval to analyze whether a difference exists between the two parental attitude groups.
Confidence Interval Estimation
Calculate proportions and compare using:
P-hat calculations from both samples and evaluating differences.
Calculate margin of error to assess range of potential differences.
Final Conclusion
If zero is included within the confidence interval, it indicates no significant difference in smoking rates based on parental attitudes.
Personal Anecdotes and Vaping Trend Discussion
Impact of Vaping on Perception of Smoking
Discussed differences between smoking and vaping among youth.
Highlighted the cultural shift and changes in behavior and norms surrounding smoking.
Two Sample Proportions Analysis in Voter Support
Case Study: Voter Support Before and After Scandal
Examined a situation where voter support dropped from 54% to 51% after a candidate scandal.
Statistical Analysis Approach
Confirmed whether this is a two-sample problem focusing on the proportions.
Analyzed sample sizes for validity of statistical assumptions.
Testing Procedure
Calculated the z-score for differences in proportions:
Evaluated how significant the change is using p-values and alpha levels.
Conclusion Interpretation
If the p-value is less than the alpha level, we would reject the null hypothesis,
Leading to a conclusion that voter support indeed decreased after the candidate's scandal.