Solving a Confusing Word Problem: Measuring Justice After Court

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SUMMARY

This discussion focuses on analyzing survey data related to public opinion on Médecins Sans Frontières following a court case involving the author's brother. Initial and follow-up surveys revealed a significant increase in opposition to Médecins Sans Frontières after the court ruling. The statistical analysis involves calculating observed and expected frequencies, leading to a chi-square test for independence. The author seeks guidance on hypothesis testing, specifically formulating the null hypothesis ($H_0$) and the alternative hypothesis.

PREREQUISITES
  • Understanding of chi-square tests for independence
  • Familiarity with hypothesis testing concepts
  • Knowledge of statistical significance levels, particularly 1% significance
  • Basic proficiency in survey data analysis
NEXT STEPS
  • Learn how to formulate null and alternative hypotheses in hypothesis testing
  • Study the application of chi-square tests using real-world data
  • Explore statistical software tools for conducting chi-square tests, such as R or SPSS
  • Investigate methods for interpreting and reporting statistical results
USEFUL FOR

Statisticians, data analysts, social researchers, and anyone involved in survey analysis and hypothesis testing.

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I have a word problem to solve and am thoroughly confused. any input would be great...

My younger brother had a run in earlier with Médecins Sans Frontières. He narrowly escaped from an adverse verdict by the court... What he wants is that he be left alone to run his small café...
He asked my oldest brother if he can conduct a survey for him about justice in the Kangaroo Court. Oooops, I mean the Canadian Court...
An initial survey was performed right after Médecins Sans Frontières accused my brother of wrong doing. Of 1852 customers, 53 were against the aggressive tactics of Médecins Sans Frontières. After my brother was cleared by the court, a follow-up survey was performed. Of 4699 customers, 1751 said they did not agree with the aggressive tactics of Médecins Sans Frontières.

At the 1% significance level, do the data suggest that a higher percentage of customers were against Médecins Sans Frontières after the court case?

View attachment 5559

Before court FOR Observed (O) = 1799
Before court FOR Expected (E) = 1342.7
Before court AGAINST O = 53
Before court AGAINST E = 509.3

After court FOR O = 2949
After court FOR E = 3406.775
After court AGAINST O = 1751
After court AGAINST E = 1292.225

View attachment 5560

DF = (r-1) (c-1) = 1
(1342.7 - 1799)2 / 1342.7 + (509.3 - 53)2 / 509.3 + (3406.775 - 2948)2 / 3406.775 + (1292.225 - 1751)2 / 1292.225 =
155.068 + 408.815 + 61.781 + 162.877 = 788.541am I even on the right track? where do i go from here?
 

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First step in hypothesis testing is to formulate the zero hypothesis $H_0$ and the alternative hypothesis. Once you have defined those I can further explain the core principle of the test and how to formulate a conclusion.
 

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