Make comments and interpretation of the graph. 2283704050meanmedianmode185566989672.466677821135287487118IMPORTANT VALUES OF FDTRange145Number of classes6.491972Class size20.714291512189132158variancestdev72190120103115741583.339.79071412108642078132421786922212883percentilepercentile(80)981241124393Histogram1021122137250.65911213-33 34-54 55-75 76-96 97-117 118-138139-159Class BoundaryLower Upper13345576971181391.200001.000000.800000.600000.400000.200000.0000033547596117138159Class Boundary Frequency CF13 - 3334-5455-7576-9697-117118 - 138139 - 159ogive12469761451CRF1216223138444513-33 34-54 55-75 76-96 97-117 118-138 139 - 159RF2CRF0.26667 0.266670.266670.35556 0.08889 0.355560.48889 0.13333 0.488890.68889 0.20000 0.688890.84444 0.15556 0.844440.97778 0.13333 0.977781.00000 0.022221.00000

From the histogram of the given grouped data set we can see that the tail is on right side. So the…

Answered: 83 70 40 50 mean median mode 55 66 98…

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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There are 20 total people that took this survey and 2 people that are older than 70 years old. What percentage of people surveyed are older than 70 years old? 5.0- 4.0- 3.0- 2.0- There are 20 total people that took this survey and people that are younger than 50. What people surveyed are younger than 50 years old? ntage of 1.0- .0- 20 30 40 50 60 70 80 90 100 Age DELL Frequency
n 10 of 16 > Here is a stemplot of the areas of the 46 counties in South Carolina. Note that the data have been rounded to the nearest What is the area of the largest South Carolina county? 10 square miles (mi?). O 655 square miles 3 9999 4 0116689 501115566778 6 47899 7 01245579 8 0011 13 10 8 11 390 square miles 122 square miles O 12.2 square miles O 1,220 square miles Key: 64 represents a county with an area of 635 to 644.99 9. 233 12 2 square miles.
A special bumper was installed on selected vehicles in a large fleet. The dollar cost of body repairs was recorded for all vehicles that were involved in accidents over a 1-year period. Those with the special bumper are the test group and the other vehicles are the control group, shown below. Each "repair incident" is defined as an invoice (which might include more than one separate type of damage). Statistic Test Group Control Group Mean Damage X⎯⎯⎯1X¯1 = $ 1,188 X⎯⎯⎯2X¯2 = $ 1,792 Sample Std. Dev. s1 = $ 712 s2 = $ 800 Repair Incidents n1 = 16 n2 = 14 Source: Unpublished study by Thomas W. Lauer and Floyd G. Willoughby. (a) Construct a 95 percent confidence interval for the true difference of the means assuming equal variances. (Round your final answers to 3 decimal places. Negative values should be indicated by a minus sign.) The 95% confidence interval is from to (b) Repeat part (a), using the assumption of unequal variances with Welch's…
The mean waiting time at the drive-through of a fast-food restaurant from the time an order is placed to the time the order is received is 88.9 seconds. A manager devises a new drive-through system that he believes will decrease wait time. As a test, he initiates the new system at his restaurant and measures the wait time for 10 randomly selected orders. The wait times are provided in the table to the right. Complete parts (a) and (b) below. 103.3 79.2 69.5 95.7 58.6 87.7 73.8 72.7 64.2 85.3 Click the icon to view the table of correlation coefficient critical values (a) Because the sample size is small, the manager must verify that the wait time is normally distributed and the sample does not contain any outliers. The normal probability plot is shown below and the sample correlation coefficient is known to be r 0.992. Are the conditions for testing the hypothesis satisfied? Expected z-score 2- Yes,the conditions satisfied. The normal probability plot linear enough, since the…
#Original immigrant datax = c(61159, 57524,56186,52254,54884,51869,29743,39877,50086,53672,65707,73861) #Age of labor dataage_over_16 = x*0.95 #Illegal immigrant data of employede1 = age_over_16*0.65 #Illegal immigrant data of unemployede2 = age_over_16*0.04 #Illegal immigrant data of Not in the labor forcee3 = age_over_16*0.30 What linear regression model should I use in R? Thanks.
#Original immigrant datax = c(61159, 57524,56186,52254,54884,51869,29743,39877,50086,53672,65707,73861) #Age of labor dataage_over_16 = x*0.95 #Illegal immigrant data of employede1 = age_over_16*0.65 #Illegal immigrant data of unemployede2 = age_over_16*0.04 #Illegal immigrant data of Not in the labor forcee3 = age_over_16*0.30 What linear regression model should I use in R? And how to draw the linear regression graph based on this model? Thanks.
The mean waiting time at the drive-through of a fast-food restaurant from the time an order is placed to the time the order is received is 87.3 seconds. A manager devises a new drive-through system that he believes will decrease wait time. As a test, he initiates the new system at his restaurant and measures the wait time for 10 randomly selected orders. The wait times are provided in the table to the right. Complete parts (a) and (b) below. 103.3 81.3 69.8 95.4 59.9 85.9 73.8 72.2 67.1 81.3 Click the icon to view the table of correlation coefficient critical values. (a) Because the sample size is small, the manager must verify that the wait time is normally distributed and the sample does not contain any outliers. The normal probability plot is shown below and the sample correlation coefficient is known to be e=0.983 Are the conditions for testing the hypothesis satisfied? ▼ No, Yes, the conditions…
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The mean waiting time at the drive-through of a fast-food restaurant from the time an order is placed to the time the order is received is 84.7 seconds. A manager devises a new drive-through system that he believes will decrease wait time. As a test, he initiates the new system at his restaurant and measures the wait time for 10 randomly selected orders. The wait times are provided in the table to the right. Complete parts (a) and (b) below.
A special bumper was installed on selected vehicles in a large fleet. The dollar cost of body repairs was recorded for all vehicles that were involved in accidents over a 1-year period. Those with the special bumper are the test group and the other vehicles are the control group, shown below. Each "repair incident" is defined as an invoice (which might include more than one separate type of damage). Statistic Test Group Control Group Mean Damage X⎯⎯⎯1X¯1 = $ 1,245 X⎯⎯⎯2X¯2 = $ 1,790 Sample Std. Dev. s1 = $ 721 s2 = $ 835 Repair Incidents n1 = 17 n2 = 14 Source: Unpublished study by Thomas W. Lauer and Floyd G. Willoughby. (a) Construct a 99 percent confidence interval for the true difference of the means assuming equal variances. (Round your final answers to 3 decimal places. Negative values should be indicated by a minus sign.) The 99% confidence interval is from to (b) Repeat part (a), using the assumption of unequal variances with Welch's…
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The mean waiting time at the drive-through of a fast-food restaurant from the time an order is placed to the time the order is received is 84.8 seconds. A manager devises a new drive-through system that she believes will decrease wait time. As a test, she initiates the new system at her restaurant and measures the wait time for 10 randomly selected orders. The wait times are provided in the table to the right. Complete parts (a) and (b) below. Click the icon to view the table of correlation coefficient critical values. C the conditions satisfied. The normal probability plot addition, a boxplot does not show any outliers. (b) is the new system effective? Conduct a hypothesis test using the P-value approach and a level of significance of α = 0.1. 109.5 67.1 59.4 than the critical value. In 73.4 67.8 (a) Because the sample size is small, the manager must verify that the wait time is normally distributed and the sample does not contain any outliers. The normal probability plot is shown…

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