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Ass6 - Assignment-6 due by Midnight(11:59pm Sunday May 1st...

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Assignment-6 due by Midnight (11:59pm) Sunday, May 1 st , 2011 (Chapters 12 & 13) True/False questions carry 1points each, Multiple Choices carry 1.5 points each and the Essay type questions carry 2.5 points each. The total score is 50 points. I will round up if your total score is in decimals. True/False (1 point each) Chapter 12 1 . The χ 2 goodness of fit cannot be used for quantitative data. T 2. The actually measured counts in the cells of a contingency table are referred to as the expected cell frequencies. F 3. The chi-square distribution is a continuous probability distribution that is skewed to the right. T 4. In a contingency table, if all of the expected frequencies equal the observed frequencies, then we can conclude that there is a perfect dependence between rows and columns. F 5. In performing a chi-square test of independence, as the difference between the respective observed and expected frequencies increase, the probability of concluding that the row variable is independent of the column variable increases. F 6. The chi-square goodness of fit test can be used to test whether a population has specified multinomial probabilities or to test if a sample has been selected from a normally distributed population. It can also be applied to test if a sample data comes from other distribution forms such as Uniform Distribution or Poisson. T Chapter 13 7. In a simple linear regression model, the coefficient of determination only indicates the strength of the relationship between independent and dependent 1
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variable, but does not show whether the relationship is positive or negative. T 8. When using simple regression analysis, if there is a strong correlation between the independent and dependent variable, then we can conclude that an increase in the value of the independent variable will lead to an increase in the value of the dependent variable. F 9. In Regression Analysis if the variance of the error term is constant, we call it the Heteroscedasticity property. F 10. In simple linear regression analysis, if the error terms exhibit a positive or negative autocorrelation over time, then the assumption of constant variance is violated. F 11. The expected value of the error term does not change from observation to observation. T 12. A significant positive correlation between X and Y implies that changes in X cause Y to change. T Multiple Choices (1.5 points each) Chapter 12 1. The chi-square goodness of fit is _________ a one-tailed test with the rejection region in the right tail. A. Always B. Sometimes C. Never
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