Traffic accidents: Traffic engineers compared rates of traffic accidents at intersections with raised medians with rates atintersections with two-way left-turn lanes. They found that out of 4642 accidents at intersections with raised medians, 2290 wererear-end accidents, and out of 4579 accidents at two-way left-turn lanes, 2005 were rear-end accidents.Part: 0/2Part 1 of 2(a) Assuming these to be random samples of accidents from the two types of intersection, construct a 98% confidence forthe difference between the proportions of accidents that are of the rear-end type at the two types of intersection. Use theTI-84 calculator and round the answers to three decimal places. Let P, represent the population for accidents atintersections with raised medians.A 98% confidence interval for the difference between the proportions of accidents that are ofthe rear-end type at the two types of intersection is

The question is about confidence interval Given : Total no. of accidents at intersection with raised…

Answered: Traffic accidents: Traffic engineers…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Snow avalanches can be a real problem for travelers in the western United States and Canada. A very common type of avalanche is called the slab avalanche. These have been studied extensively by David McClung, a professor of civil engineering at the University of British Columbia. Suppose slab avalanches studied in a region of Canada had an average thickness of u = 67 cm. The ski patrol at Vail, Colorado, is studying slab avalanches in its region. A random sample of avalanches in spring gave the following thicknesses (in cm). 59 51 76 38 65 54 49 62 68 55 64 67 63 74 65 79 (i) Use a calculator with sample mean and standard deviation keys to find x and s. (Round your answers to two decimal places.) X= cm S= cm (ii) Assume the slab thickness has an approximately normal distribution. Use a 1% level of significance to test the claim that the mean slab thickness in the Vail region is different from that in the region of Canada. (a) What is the level of significance? State the null and…
Hi, I'm stuck with question 2. Question 1 given the example for this question
As a hospital administrator of a large hospital, you are concerned with the absenteeism among nurses' aides. The issue has been raised by registered nurses, who feel they often have to perform work normally done by their aides. To get the facts, absenteeism data were gathered for the last three weeks, which is considered a representative period for future conditions. After taking random samples of 64 personnel files each day, the following data were produced Day 1 2 3 4 Aides Absent 5 4 2 6 a Day 6 7 8 9 10 Aides Absent 6 7 9 3 7 Day Aides Absent 11 12 13 (Enter your responses rounded to The upper control limit is and the lower control limit is three decimal places. If your answer for the lower control limit is negative, enter this value as 0.) 14 15 6 8 10 1 2 Because your assessment of absenteeism is likely to come under careful scrutiny, you would like a type I error of only 1 percent. You want to be sure to identify any instances of unusual absences. If some are present, you will…
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A two-way ANOVA experiment with interaction was conducted. Factor A had three levels (columns), factor B had five levels (rows), and six observations were obtained for each combination. Assume normality in the underlying populations. The results include the following sum of squares terms: SST=1542 SSA= 1042 SSB = 358 SSAB = 39 a. Construct an ANOVA table. (Round "MS" to 4 decimal places and "F" to 3 decimal places.) ANOVA Source of Variation Rows Columns Interaction Error Total SS 0 df Answer is not complete. 0 MS F p- value 0.000 0.000 0.002
apter 10) Post-Class A consumer advocate researches the length of life between two brands of refrigerators, Brand A and Brand B. He colle (measured in years) on the longevity of 40 refrigerators for Brand A and repeats the sampling for Brand B. These data in years. (You may find it useful to reference the appropriate table: z table or t table) Brand A Brand B Brand A Brand B 17 16 23 24 18 22 14 16 14 24 17 18 19 18 20 22 19 19 22 18 24 19 14 12 14 16 22 23 22 18 24 21 23 19 12 20 19 13 18 15 13 23 17' 19 15 23 16 16 21 16 14 19 12 21 22 14 21 24 24 12 P 15 12 12 20 15 16 12 19 24 21 20 20 13 15 19 21 14 20 14 Click here for the Excel Data File Saved Assume that μ₁ is the mean longevity for Brand A and 2 is the mean longevity for Brand B. a. Select the competing hypotheses to test whether the average length of life differs between the two brands. O He: H1 - H₂ = 0; HA: M1 - µ2 * 0
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Statistical Methods in Atmospheric Science
PETROGAS is testing new filters for its motorbikes. One brand of filter (Filter A) is placed in one motorbike, and the other brand (Filter B) is placed in the second motorbike. Random samples of air released from the motorbikes are taken at different times throughout the day. Pollutant concentrations are measured for both motorbikes at the same time. The following data attached represent the pollutant concentrations (in parts per million) for samples taken at 20 different times after passing through the filters. a. Test the hypothesis that the mean for the pollutant concentration for Filter B is greater than 30. Use the 1% level of significance. b. Construct a 95% confidence interval for the difference in mean pollutant concentration, where a difference is equal to the pollutant concentration passing through Filter A minus the passing through Filter B. c. Using the 5% significance level, determine whether there is evidence that mean for the pollutant concentration for Filter A…
The Wall Street Journal asked Concur Technologies, Inc., an expense management company, to examine data from 8.3 million expense reports to provide insights regarding business travel expenses. Their analysis of the data showed that New York was the most expensive city. The following table shows the average daily hotel room rate (X) and the average amount spent on entertainment (Y) for a random sample of 9 of the 25 most-visited U.S. cities. These data lead to the estimated regression equation y = 17.49 + 1.0334x. For these data SSE = 1541.4. Use Table 1 of Appendix B. a. Predict the amount spent on entertainment for a particular city that has a daily room rate of $89 (to 2 decimals). b. Develop a 95% confidence interval for the mean amount spent on entertainment for all cities that have a daily room rate of $89 (to 2 decimals). c. The average room rate in Chicago is $128. Develop a 95% prediction interval for the amount spent on entertainment in Chicago (to 2 decimals).

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