QUIZ 1

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East Tennessee State University *

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MISC

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Statistics

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Apr 3, 2024

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docx

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Uploaded by ChancellorNewt4102

ALL QUIZES Quiz 1 1. Which of the following is a nominal variable? A. Gender B. Blood type C. Temperature D. City 2. Simple linear regression is used to compare two means. A. True B. Fals e 3. Nominal variables allow only for quantitative classification. A. True B. Fa lse 4. Which of the following variables allows us to rank items that are measured? A. Nominal B. Ratio C. Ordinal D. B,c, and d 5. Type I error is made when a researcher rejects the null hypothesis when it is actually true. A. Tru e B. False 6. A researcher wants to compare a sample mean with a population mean, which of these tests will be employed? A. Paired T-Test B. One Sample t est

C. ANOVA D. Two independent t-tests 7. Correlation analysis is always used to evaluate the relationship between two continuous variables and can take values -1, +1 or any number between -1 and +1. A. True B. Fa lse 8. In testing the null hypothesis, the overall T-test obtained in a one-way ANOVA is useful in making inferences. A. True B. Fa lse *Anova uses F-tests 9. The result of a study shows that when the level of HDL cholesterol increases in an individual, the risk of cardiovascular disease increases. We can conclude that the two variables are highly negative correlated. A. True B. Fal se 10. Analysis of variance (ANOVA) is mainly used to compare more than two means. However, it will give the same results as two sample- independent T-test if we compare two means. A. Tru e B. False QUIZ 2 1. One usefulness of scatter plots is its ability to detect outliers A. Tru e B. False 2. Regression analysis is used to predict the value of the independent variable on the basis of the other dependent variables. A. Tru e B. False

3. For linear regression analysis, which of these variables will not be used to predict the response? A. Predictor variable B. Explanatory variable C. Independent variable D. Risk Factor E. None of the ab ove 4. The least squared method is used to minimize the sum of squares of the residuals, or the sum of distances from the regression line to the observed data points. A. Tr ue B. False 5. A deviation between the predicted and mean values of the response variable ( ^ y - (y-bar)) is the explained deviation be the regression line. A. Tru e B. False 6. Suppose we do a linear regression analysis, the best linear regression model to fit the data will be the one that minimizes the sum of squared errors. A. Tr ue B. False 7. Assume that the simple linear regression model we have fitted is y=b 0 +b 1 x. We can conclude that there is no negative association between two variables x and y if b 0 <0. A. True B. Fals e

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