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Sex selection and hypothesis testing: Across all of India, there are only 933 girls for every 1000 boys (Lloyd, 2006), evidence of a bias that

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Sex selection and hypothesis testing: Across all of India, there are only 933 girls for every 1000 boys (Lloyd, 2006), evidence of a bias that leads many parents to illegally select for boys or to kill their infant girls. This translates as a national proportion of girls of 0.483. In Punjab, a region of India in which residents tend to be more educated than in other regions, there are only 798 girls for every 1000 boys. Assume that you are a researcher interested in whether sex selection is more or less prevalent in educated regions of India, using Punjab as your sample, You select a sample of 1,798 children from Punjab (798 girls and 1,000 boys) and conduct a one- way chi-square (goodness of fit chi-square) to test whether the proportion of girls to boys is different in Punjab compared to the national proportion. 1. What hypothesis statements would you use? Remember that the hypothesis statements for the chi-square can be written out in sentence format. 0.5 points (0.25 per hypothesis) 2. How many categories (levels of the study variable) are there? This is k. 0.50 points 3. What degrees of freedom should you use for this problem? 0.50 points 4. What is the critical chi-square value (assume alpha = .05)? 0.50 points Use the national proportion to determine the expected frequencies for your sample. Use observed and expected frequencies of girls and boys to calculate the chi-square statistic. Observed Frequencies Expected Frequencies (Based in Punjab on the general population) 0.50 pts Boys Girls 0.50 pts Boys Girls Category Observed Expected (0 - B) (0- E) (0-EY (0) (E) E Boys Girls point 6. What is your decision (reject the null or fail to reject the null)? What does this mean in plain English: is the observed frequency (proportion in Punjab) different from the expected frequency (national proportion)? 1 point (0.5 nt for decision, 0.5 nt explanation)

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