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Unformatted text preview: Statistics 6126 Brief Solutions to Homework Exercises These solutions are solely for the use of students in STA 6126 at the University of Florida and are not to be distributed elsewhere. Please report any errors in these solutions to Alan Agresti, [email protected] , so they can be corrected. Chapter 1 1.2. (a) Population was all 7 million voters, and sample was 2705 voters in exit poll. (b) A statistic is the 56.5% who voted for Schwarzenegger from the exit poll sample of size 2705; a parameter is the 55.9% who actually voted for Schwarzenegger. 1.3. (a) All students at the University of Wisconsin. (b) A statistic, since it’s calculated only for the 100 sampled students. 1.5. (a) All adult Americans. (b) Proportion of all adult Americans who would answer definitely or probably true. (c) The sample proportion 0.523 estimates the population proportion. (d) No, it is a prediction of the population value but will not equal it exactly, because the sample is only a very small subset of the population. 1.17. (a) A statistic is the 45% of the sample of subjects interviewed in the UK who said yes . (b) A parameter is the true percent of the 48 million adults in the UK who would say yes . (c) A descriptive analysis is that the percentage of yes responses in the survey varied from 10% (in Bulgaria) to 60% in Luxembourg). (d) An inferential analysis is that the percentage of adults in the UK who would say yes falls between 41% and 49%. Chapter 2 2.1. (a) Discrete variables take a set of separate numbers for their values (such as nonnegative integers). Continuous variables take an infinite continuum of values. (b) Categorical variables have a scale that is a set of categories; for quantitative variables, the measurement scale has numerical values that represent different magnitudes of the variable. (c) Nominal variables have a scale of unordered categories, whereas ordinal variables have a scale of ordered categories. The distinctions among types of variables are important in determining the appropriate descriptive and inferential procedures for a statistical analysis. 2.2. (a) Quantitative (b) Categorical (c) Categorical (d) Quantitative (e) Categorical (f) Quantitative (g) Categorical (h) Quantitative (i) Categorical 2.3. (a) Ordinal (b) Nominal (c) Interval (d) Nominal (e) Nominal (f) Ordinal (g) Interval (h) Ordinal (i) Nominal (j) Interval (k) Ordinal 2.5. (a) Interval (b) Ordinal (c) Nominal 2.7. (a) Ordinal, since there is a sense of order to the categories. (b) Discrete, since separate values rather than continuum of numbers. (c) These values are statistics since they come from a sample. 2.13. (a) Observational study (b) Experiment (c) Observational study (d) Experiment 2.14. (a) Experimental study, since the researchers are assigning subjects to treatments. (b) An observational study could observe those who grew up in nonsmoking or smoking environments and examine incidence of lung cancer for each group....
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This note was uploaded on 01/15/2012 for the course STA 6126 taught by Professor Yesilcay during the Spring '08 term at University of Florida.
 Spring '08
 YESILCAY
 Statistics

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