Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card
8th Edition
ISBN: 9781464158933
Author: David S. Moore, George P. McCabe, Bruce A. Craig
Publisher: W. H. Freeman
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Chapter 1.3, Problem 75E
To determine
To find: The five-number summary, boxplot, and histogram for the provided data with and without taking the logarithm of the observations and a short summary of the major features of this distribution.
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An experiment was conducted to determine the effect of type of fertilizer on the growth
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Chapter 1 Solutions
Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card
Ch. 1.1 - Prob. 1UYKCh. 1.1 - Prob. 2UYKCh. 1.1 - Prob. 3UYKCh. 1.1 - Prob. 5UYKCh. 1.1 - Prob. 4UYKCh. 1.1 - Prob. 6UYKCh. 1.1 - Prob. 7UYKCh. 1.1 - Prob. 8ECh. 1.1 - Prob. 9ECh. 1.1 - Prob. 10E
Ch. 1.1 - Prob. 11ECh. 1.1 - Prob. 12ECh. 1.1 - Prob. 13ECh. 1.1 - Prob. 14ECh. 1.1 - Prob. 15ECh. 1.2 - Prob. 16UYKCh. 1.2 - Prob. 17UYKCh. 1.2 - Prob. 18UYKCh. 1.2 - Prob. 19UYKCh. 1.2 - Prob. 20UYKCh. 1.2 - Prob. 21UYKCh. 1.2 - Prob. 22UYKCh. 1.2 - Prob. 23UYKCh. 1.2 - Prob. 24UYKCh. 1.2 - Prob. 25ECh. 1.2 - Prob. 26ECh. 1.2 - Prob. 27ECh. 1.2 - Prob. 28ECh. 1.2 - Prob. 29ECh. 1.2 - Prob. 30ECh. 1.2 - Prob. 31ECh. 1.2 - Prob. 32ECh. 1.2 - Prob. 33ECh. 1.2 - Prob. 34ECh. 1.2 - Prob. 35ECh. 1.2 - Prob. 42ECh. 1.2 - Prob. 36ECh. 1.2 - Prob. 43ECh. 1.2 - Prob. 37ECh. 1.2 - Prob. 44ECh. 1.2 - Prob. 38ECh. 1.2 - Prob. 45ECh. 1.2 - Prob. 46ECh. 1.2 - Prob. 39ECh. 1.2 - Prob. 40ECh. 1.2 - Prob. 41ECh. 1.3 - Prob. 47UYKCh. 1.3 - Prob. 48UYKCh. 1.3 - Prob. 49UYKCh. 1.3 - Prob. 50UYKCh. 1.3 - Prob. 51UYKCh. 1.3 - Prob. 52UYKCh. 1.3 - Prob. 53UYKCh. 1.3 - Prob. 54UYKCh. 1.3 - Prob. 55UYKCh. 1.3 - Prob. 56UYKCh. 1.3 - Prob. 57UYKCh. 1.3 - Prob. 58UYKCh. 1.3 - Prob. 59UYKCh. 1.3 - Prob. 60UYKCh. 1.3 - Prob. 67ECh. 1.3 - Prob. 69ECh. 1.3 - Prob. 61ECh. 1.3 - Prob. 62ECh. 1.3 - Prob. 63ECh. 1.3 - Prob. 64ECh. 1.3 - Prob. 65ECh. 1.3 - Prob. 66ECh. 1.3 - Prob. 74ECh. 1.3 - Prob. 75ECh. 1.3 - Prob. 76ECh. 1.3 - Prob. 71ECh. 1.3 - Prob. 68ECh. 1.3 - Prob. 70ECh. 1.3 - Prob. 77ECh. 1.3 - Prob. 78ECh. 1.3 - Prob. 79ECh. 1.3 - Prob. 80ECh. 1.3 - Prob. 81ECh. 1.3 - Prob. 82ECh. 1.3 - Prob. 83ECh. 1.3 - Prob. 84ECh. 1.3 - Prob. 85ECh. 1.3 - Prob. 86ECh. 1.3 - Prob. 87ECh. 1.3 - Prob. 88ECh. 1.3 - Prob. 89ECh. 1.3 - Prob. 90ECh. 1.3 - Prob. 91ECh. 1.3 - Prob. 92ECh. 1.3 - Prob. 93ECh. 1.3 - Prob. 94ECh. 1.3 - Prob. 95ECh. 1.3 - Prob. 96ECh. 1.3 - Prob. 72ECh. 1.3 - Prob. 97ECh. 1.3 - Prob. 98ECh. 1.3 - Prob. 99ECh. 1.3 - Prob. 100ECh. 1.3 - Prob. 73ECh. 1.4 - Prob. 101UYKCh. 1.4 - Prob. 102UYKCh. 1.4 - Prob. 103UYKCh. 1.4 - Prob. 104UYKCh. 1.4 - Prob. 105UYKCh. 1.4 - Prob. 106UYKCh. 1.4 - Prob. 107UYKCh. 1.4 - Prob. 108UYKCh. 1.4 - Prob. 109ECh. 1.4 - Prob. 110ECh. 1.4 - Prob. 111ECh. 1.4 - Prob. 112ECh. 1.4 - Prob. 113ECh. 1.4 - Prob. 114ECh. 1.4 - Prob. 115ECh. 1.4 - Prob. 116ECh. 1.4 - Prob. 117ECh. 1.4 - Prob. 118ECh. 1.4 - Prob. 119ECh. 1.4 - Prob. 120ECh. 1.4 - Prob. 121ECh. 1.4 - Prob. 122ECh. 1.4 - Prob. 123ECh. 1.4 - Prob. 124ECh. 1.4 - Prob. 125ECh. 1.4 - Prob. 126ECh. 1.4 - Prob. 127ECh. 1.4 - Prob. 128ECh. 1.4 - Prob. 129ECh. 1.4 - Prob. 130ECh. 1.4 - Prob. 131ECh. 1.4 - Prob. 132ECh. 1.4 - Prob. 133ECh. 1.4 - Prob. 134ECh. 1.4 - Prob. 135ECh. 1.4 - Prob. 136ECh. 1.4 - Prob. 137ECh. 1.4 - Prob. 138ECh. 1.4 - Prob. 139ECh. 1.4 - Prob. 140ECh. 1.4 - Prob. 141ECh. 1.4 - Prob. 142ECh. 1.4 - Prob. 143ECh. 1.4 - Prob. 144ECh. 1.4 - Prob. 145ECh. 1.4 - Prob. 146ECh. 1.4 - Prob. 147ECh. 1.4 - Prob. 148ECh. 1.4 - Prob. 149ECh. 1.4 - Prob. 150ECh. 1.4 - Prob. 151ECh. 1.4 - Prob. 152ECh. 1.4 - Prob. 153ECh. 1.4 - Prob. 154ECh. 1.4 - Prob. 155ECh. 1 - Prob. 156ECh. 1 - Prob. 157ECh. 1 - Prob. 158ECh. 1 - Prob. 159ECh. 1 - Prob. 160ECh. 1 - Prob. 161ECh. 1 - Prob. 162ECh. 1 - Prob. 163ECh. 1 - Prob. 164ECh. 1 - Prob. 165ECh. 1 - Prob. 166ECh. 1 - Prob. 167ECh. 1 - Prob. 168ECh. 1 - Prob. 169ECh. 1 - Prob. 170ECh. 1 - Prob. 171ECh. 1 - Prob. 172ECh. 1 - Prob. 173ECh. 1 - Prob. 174ECh. 1 - Prob. 175ECh. 1 - Prob. 176ECh. 1 - Prob. 177E
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- In the accompanying data table, the entries are for five different years and consist of the weights (metric tons) of lemons imported from another country and car crash fatality rates per 100,000 population. The data are based on data from a scientific publication. Lemon Imports 489 529 Crash Fatality Rate 14.8 15.6 Given that the data are matched and considering the units of the data, does it make sense to use the difference between each pair of values? Why or why not? 231 15.6 268 15.1 Save 362 15.4arrow_forwardPeriodically, the county Water Department tests the drinking water of homeowners for contaminants such as lead and copper. The lead and copper levels in water specimens collected in 1998 for a sample of 10 residents of a subdevelopement of the county are shown below. lead (g/L) copper (mg/L) 2.9 0.2 5.1 4.2 5.5 1.2 0.3 1.3 4.9 1.7 0.133 0.774 0.214 0.671 0.444 0.234 0.357 0.761 0.176 0.888 (a) Construct a 99% confidence interval for the mean lead level in water specimans of the subdevelopment. OSASO (b) Construct a 99% confidence interval for the mean copper level in water specimans of the subdevelopment. ≤H≤arrow_forwardAn article reported on a study in which each of 13 workers was provided with both a conventional shovel and a shovel whose blade was perforated with small holes. The authors of the cited article provided the following data on energy expenditure [kcal/kg(subject)/lb(clay)]. Worker: 2 4 5 6 Conventional: 0.0015 0.0015 0.0018 0.0022 0.001 0.0016 0.0028 Perforated: 0.0015 0.001 0.0019 0.0013 0.0011 0.0017 0.0024 Worker: 10 11 12 13 Conventional: 0.0021 0.0015 0.0014 0.0023 0.0017 0.002 Perforated: 0.0021 0.0013 0.0013 0.0017 0.0015 0.0013 n USE SALT Do these data provide convincing evidence that the mean energy expenditure using the conventional shovel exceeds that using the perforated shovel? Test the relevant hypotheses using a significance level of 0.05. (Use SALT to calculate the P-value. Use Hd = Hconventional - Hperforated Round your test statistic to one decimal place and your P-value to three decimal places.) t= df = p-value = State your conclusion. O we fail to reject H,. We have…arrow_forward
- Periodically, the county Water Department tests the drinking water of homeowners for contminants such as lead and copper. The lead and copper levels in water specimens collected in 1998 for a sample of 10 residents of a subdevelopement of the county are shown below. lead (?μg/L) copper (mg/L) 3.33.3 0.6280.628 3.33.3 0.2930.293 0.30.3 0.7830.783 4.74.7 0.1950.195 55 0.3780.378 1.41.4 0.2330.233 0.90.9 0.1010.101 0.90.9 0.6980.698 3.63.6 0.80.8 1.21.2 0.7610.761 (a) Construct a 99% confidence interval for the mean lead level in water specimans of the subdevelopment. _____≤μ≤_____ (b) Construct a 99% confidence interval for the mean copper level in water specimans of the subdevelopment. ______≤μ≤______arrow_forwardA botanist grew 24 pepper plants on the same greenhouse bench. After 21 days, she measured the total stem length (cm) of each plant, and obtained the following values: 10.1 10.9 11.8 12.2 12.2 12.5 13.2 13.2 13.5 What terms can be used to classify the variable of interest in this study? 9.8 12.1 13.1 O A. Categorical - Nominal OB. Categorical - Ordinal OC. Numeric - Continuous OD. Numeric - Discrete 11.3 12.3 13.4 11.9 12.6 13.5 12.0 12.7 13.6 12.0 13.0 14.1arrow_forwardYou have been hired to measure the concentration of ammonia in water from wells at two districts on Long Island. After sampling 10 wells in one of the districts you find the values are, in mg/L: 6.4, 2.1, 1.4, 0.7, 6.8, 3.2, 2.7, 1.6, 4.9, 1.2. Your assistant plots the data from the second set of wells and the histogram of data from that sample looks pretty much the same as for your data set. Which statistical test do you anticipate that you will use? An one-sample t-test An unpaired, two-sample t-test A paired, two-sample t-test A one-way anova A Mann-Whitney U test Main Contentarrow_forward
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