ELEMTARY STATISTICS W/STATLAB(LL)
13th Edition
ISBN: 9781323774731
Author: Triola
Publisher: PEARSON
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Textbook Question
Chapter 3, Problem 7CQQ
Sleep Q3 For a sample of 80 sleep times, approximately how many of those times are less than Q3?
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The average miles per gallon for a sample of 40 cars of model SX last year was 32.1, with a population standard deviation of 3.8. A sample of 40 cars from this year’s model SX has an average of 35.2 mpg, with a population standard deviation of 5.4.
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Chapter 3 Solutions
ELEMTARY STATISTICS W/STATLAB(LL)
Ch. 3.1 - Average The defunct website IncomeTaxList.com...Ch. 3.1 - Whats Wrong? USA Today published a list consisting...Ch. 3.1 - Measures of Center In what sense are the mean,...Ch. 3.1 - Resistant Measures Here are four of the Verizon...Ch. 3.1 - Critical Thinking. For Exercises 5-20, watch out...Ch. 3.1 - Critical Thinking. For Exercises 5-20, watch out...Ch. 3.1 - Critical Thinking. For Exercises 5-20, watch out...Ch. 3.1 - Critical Thinking. For Exercises 5-20, watch out...Ch. 3.1 - Critical Thinking. For Exercises 5-20, watch out...Ch. 3.1 - Critical Thinking. For Exercises 5-20, watch out...
Ch. 3.1 - Critical Thinking. For Exercises 5-20, watch out...Ch. 3.1 - Critical Thinking. For Exercises 5-20, watch out...Ch. 3.1 - Critical Thinking. For Exercises 5-20, watch out...Ch. 3.1 - Critical Thinking. For Exercises 5-20, watch out...Ch. 3.1 - Critical Thinking. For Exercises 5-20, watch out...Ch. 3.1 - Critical Thinking. For Exercises 5-20, watch out...Ch. 3.1 - Critical Thinking. For Exercises 5-20, watch out...Ch. 3.1 - Critical Thinking. For Exercises 5-20, watch out...Ch. 3.1 - Critical Thinking. For Exercises 5-20, watch out...Ch. 3.1 - Critical Thinking. For Exercises 5-20, watch out...Ch. 3.1 - In Exercises 21-24, find the mean and median for...Ch. 3.1 - In Exercises 21-24, find the mean and median for...Ch. 3.1 - In Exercises 21-24, find the mean and median for...Ch. 3.1 - In Exercises 21-24, find the mean and median for...Ch. 3.1 - Large Data Sets from Appendix B. In Exercises...Ch. 3.1 - Large Data Sets from Appendix B. In Exercises...Ch. 3.1 - Large Data Sets from Appendix B. In Exercises...Ch. 3.1 - Large Data Sets from Appendix B. In Exercises...Ch. 3.1 - In Exercises 29-32, find the mean of the data...Ch. 3.1 - In Exercises 29-32, find the mean of the data...Ch. 3.1 - In Exercises 29-32, find the mean of the data...Ch. 3.1 - In Exercises 29-32, find the mean of the data...Ch. 3.1 - Weighted Mean A student of the author earned...Ch. 3.1 - Weighted Mean A student of the author earned...Ch. 3.1 - Degrees of Freedom Five pulse rates randomly...Ch. 3.1 - Censored Data Data Set 15 Presidents in Appendix B...Ch. 3.1 - Trimmed Mean Because the mean is very sensitive to...Ch. 3.1 - Harmonic Mean The harmonic mean is often used as a...Ch. 3.1 - Geometric Mean The geometric mean is often used in...Ch. 3.1 - Quadratic Mean The quadratic mean (or root mean...Ch. 3.1 - Median When data are summarized in a frequency...Ch. 3.2 - Range Rule of Thumb for Estimating s The 20 brain...Ch. 3.2 - Range Rule of Thumb for Interpreting s The 20...Ch. 3.2 - Variance The 20 subjects used in Data Set 8 IQ and...Ch. 3.2 - Symbols Identify the symbols used for each of the...Ch. 3.2 - In Exercises 5-20, find the range, variance, and...Ch. 3.2 - In Exercises 5-20, find the range, variance, and...Ch. 3.2 - In Exercises 5-20, find the range, variance, and...Ch. 3.2 - In Exercises 5-20, find the range, variance, and...Ch. 3.2 - In Exercises 5-20, find the range, variance, and...Ch. 3.2 - In Exercises 5-20, find the range, variance, and...Ch. 3.2 - In Exercises 5-20, find the range, variance, and...Ch. 3.2 - In Exercises 5-20, find the range, variance, and...Ch. 3.2 - In Exercises 5-20, find the range, variance, and...Ch. 3.2 - In Exercises 5-20, find the range, variance, and...Ch. 3.2 - In Exercises 5-20, find the range, variance, and...Ch. 3.2 - In Exercises 5-20, find the range, variance, and...Ch. 3.2 - In Exercises 5-20, find the range, variance, and...Ch. 3.2 - In Exercises 5-20, find the range, variance, and...Ch. 3.2 - In Exercises 5-20, find the range, variance, and...Ch. 3.2 - In Exercises 5-20, find the range, variance, and...Ch. 3.2 - In Exercises 21-24, find the coefficient of...Ch. 3.2 - In Exercises 21-24, find the coefficient of...Ch. 3.2 - In Exercises 21-24, find the coefficient of...Ch. 3.2 - In Exercises 21-24, find the coefficient of...Ch. 3.2 - Large Data Sets from Appendix B. In Exercises...Ch. 3.2 - Prob. 26BSCCh. 3.2 - Large Data Sets from Appendix B. In Exercises...Ch. 3.2 - Large Data Sets from Appendix B. In Exercises...Ch. 3.2 - Estimating Standard Deviation with the Range Rule...Ch. 3.2 - Prob. 30BSCCh. 3.2 - Estimating Standard Deviation with the Range Rule...Ch. 3.2 - Estimating Standard Deviation with the Range Rule...Ch. 3.2 - Identifying Significant Values with the Range Rule...Ch. 3.2 - Prob. 34BSCCh. 3.2 - Foot Lengths Based on Data Set 2 Foot and Height...Ch. 3.2 - Identifying Significant Values with the Range Rule...Ch. 3.2 - Finding Standard Deviation from a Frequency...Ch. 3.2 - Finding Standard Deviation from a Frequency...Ch. 3.2 - Finding Standard Deviation from a Frequency...Ch. 3.2 - Finding Standard Deviation from a Frequency...Ch. 3.2 - The Empirical Rule Based on Data Set 1 Body Data...Ch. 3.2 - The Empirical Rule Based on Data Set 3 Body...Ch. 3.2 - Chebyshevs Theorem Based on Data Set 1 Body Data...Ch. 3.2 - Chebyshevs Theorem Based on Data Set 3 Body...Ch. 3.2 - Why Divide by n 1? Let a population consist of...Ch. 3.2 - Mean Absolute Deviation Use the same population of...Ch. 3.3 - z Scores LeBron James, one of the most successful...Ch. 3.3 - Heights The boxplot shown below results from the...Ch. 3.3 - Boxplot Comparison Refer to the boxplots shown...Ch. 3.3 - z Scores If your score on your next statistics...Ch. 3.3 - z Scores. In Exercises 5-8, express all z scores...Ch. 3.3 - z Scores. In Exercises 5-8, express all z scores...Ch. 3.3 - z Scores. In Exercises 5-8, express all z scores...Ch. 3.3 - z Scores. In Exercises 5-8, express all z scores...Ch. 3.3 - Significant Values. In Exercises 9-12, consider a...Ch. 3.3 - Significant Values. In Exercises 9-12, consider a...Ch. 3.3 - Significant Values. In Exercises 9-12, consider a...Ch. 3.3 - Significant Values. In Exercises 9-12, consider a...Ch. 3.3 - Comparing Values. In Exercises 13-16, use z scores...Ch. 3.3 - Comparing Values. In Exercises 13-16, use z scores...Ch. 3.3 - Comparing Values. In Exercises 13-16, use z scores...Ch. 3.3 - Comparing Values. In Exercises 13-16, use z scores...Ch. 3.3 - Percentiles. In Exercises 17-20, use the following...Ch. 3.3 - Percentiles. In Exercises 17-20, use the following...Ch. 3.3 - Percentiles. In Exercises 17-20, use the following...Ch. 3.3 - Percentiles. In Exercises 17-20, use the following...Ch. 3.3 - Percentiles. In Exercises 17-20, use the following...Ch. 3.3 - Percentiles. In Exercises 17-20, use the following...Ch. 3.3 - Percentiles. In Exercises 17-20, use the following...Ch. 3.3 - Percentiles. In Exercises 17-20, use the following...Ch. 3.3 - Percentiles. In Exercises 17-20, use the following...Ch. 3.3 - Percentiles. In Exercises 17-20, use the following...Ch. 3.3 - Percentiles. In Exercises 17-20, use the following...Ch. 3.3 - Percentiles. In Exercises 17-20, use the following...Ch. 3.3 - Boxplots. In Exercises 29-32, use the given data...Ch. 3.3 - Boxplots. In Exercises 29-32, use the given data...Ch. 3.3 - Boxplots. In Exercises 29-32, use the given data...Ch. 3.3 - Boxplots. In Exercises 29-32, use the given data...Ch. 3.3 - Boxplots from Large Data Sets in Appendix B. In...Ch. 3.3 - Boxplots from Large Data Sets in Appendix B. In...Ch. 3.3 - Prob. 35BSCCh. 3.3 - Boxplots from Large Data Sets in Appendix B. In...Ch. 3.3 - Outliers and Modified Boxplots Repeat Exercise 33...Ch. 3 - Sleep Mean As part of the National Health and...Ch. 3 - Sleep Median What is the median of the sample...Ch. 3 - Sleep Mode What is the mode of the sample values...Ch. 3 - Sleep Variance The standard deviation of the...Ch. 3 - Prob. 5CQQCh. 3 - Sleep z Score A larger sample of 50 sleep times...Ch. 3 - Sleep Q3 For a sample of 80 sleep times,...Ch. 3 - Sleep 5-Number Summary For a sample of 100 sleep...Ch. 3 - Estimating s A large sample of sleep times...Ch. 3 - Sleep Notation Consider a sample of sleep times...Ch. 3 - Old Faithful Geyser Listed below are prediction...Ch. 3 - z Score Using the sample data from Exercise 1,...Ch. 3 - Boxplot Using the same prediction errors listed in...Ch. 3 - ER Codes In an analysis of activities that...Ch. 3 - Comparing Birth Weights The birth weights of a...Ch. 3 - Effects of an Outlier Listed below are platelet...Ch. 3 - Interpreting a Boxplot Shown below is a boxplot of...Ch. 3 - Estimating Standard Deviation Listed below is a...Ch. 3 - Prob. 1CRECh. 3 - Prob. 2CRECh. 3 - Stemplot Use the amounts of arsenic from Exercise...Ch. 3 - Prob. 4CRECh. 3 - Histogram The accompanying histogram depicts...Ch. 3 - Normal Distribution Examine the distribution shown...Ch. 3 - Words Spoken by Men and Women Refer to Data Set 24...Ch. 3 - Second-Hand Smoke Data Set 12 Passive and Active...
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- You want to compare the average number of tines on the antlers of male deer in two nearby metro parks. A sample of 30 deer from the first park shows an average of 5 tines with a population standard deviation of 3. A sample of 35 deer from the second park shows an average of 6 tines with a population standard deviation of 3.2. Find a 95 percent confidence interval for the difference in average number of tines for all male deer in the two metro parks (second park minus first park).Do the parks’ deer populations differ in average size of deer antlers?arrow_forwardSuppose that you want to increase the confidence level of a particular confidence interval from 80 percent to 95 percent without changing the width of the confidence interval. Can you do it?arrow_forwardA random sample of 1,117 U.S. college students finds that 729 go home at least once each term. Find a 98 percent confidence interval for the proportion of all U.S. college students who go home at least once each term.arrow_forward
- Suppose that you make two confidence intervals with the same data set — one with a 95 percent confidence level and the other with a 99.7 percent confidence level. Which interval is wider?Is a wide confidence interval a good thing?arrow_forwardIs it true that a 95 percent confidence interval means you’re 95 percent confident that the sample statistic is in the interval?arrow_forwardTines can range from 2 to upwards of 50 or more on a male deer. You want to estimate the average number of tines on the antlers of male deer in a nearby metro park. A sample of 30 deer has an average of 5 tines, with a population standard deviation of 3. Find a 95 percent confidence interval for the average number of tines for all male deer in this metro park.Find a 98 percent confidence interval for the average number of tines for all male deer in this metro park.arrow_forward
- Based on a sample of 100 participants, the average weight loss the first month under a new (competing) weight-loss plan is 11.4 pounds with a population standard deviation of 5.1 pounds. The average weight loss for the first month for 100 people on the old (standard) weight-loss plan is 12.8 pounds, with population standard deviation of 4.8 pounds. Find a 90 percent confidence interval for the difference in weight loss for the two plans( old minus new) Whats the margin of error for your calculated confidence interval?arrow_forwardA 95 percent confidence interval for the average miles per gallon for all cars of a certain type is 32.1, plus or minus 1.8. The interval is based on a sample of 40 randomly selected cars. What units represent the margin of error?Suppose that you want to decrease the margin of error, but you want to keep 95 percent confidence. What should you do?arrow_forward3. (i) Below is the R code for performing a X2 test on a 2×3 matrix of categorical variables called TestMatrix: chisq.test(Test Matrix) (a) Assuming we have a significant result for this procedure, provide the R code (including any required packages) for an appropriate post hoc test. (b) If we were to apply this technique to a 2 × 2 case, how would we adapt the code in order to perform the correct test? (ii) What procedure can we use if we want to test for association when we have ordinal variables? What code do we use in R to do this? What package does this command belong to? (iii) The following code contains the initial steps for a scenario where we are looking to investigate the relationship between age and whether someone owns a car by using frequencies. There are two issues with the code - please state these. Row3<-c(75,15) Row4<-c(50,-10) MortgageMatrix<-matrix(c(Row1, Row4), byrow=T, nrow=2, MortgageMatrix dimnames=list(c("Yes", "No"), c("40 or older","<40")))…arrow_forward
- Describe the situation in which Fisher’s exact test would be used?(ii) When do we use Yates’ continuity correction (with respect to contingencytables)?[2 Marks] 2. Investigate, checking the relevant assumptions, whether there is an associationbetween age group and home ownership based on the sample dataset for atown below:Home Owner: Yes NoUnder 40 39 12140 and over 181 59Calculate and evaluate the effect size.arrow_forwardNot use ai pleasearrow_forwardNeed help with the following statistic problems.arrow_forward
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