moving = data.frame (hours = c(49, 61.5, 65, 38, 26, 46, 28, 45.5, 35.5, 62, 18,...

moving = data.frame (hours = c(49, 61.5, 65, 38, 26, 46, 28, 45.5, 35.5, 62, 18, 11, 53, 22, 59.5, 17, 44, 49, 45, 24.5, 25, 43, 29, 37, 20.5, 31, 29, 19.5, 17.5, 14, 41, 37, 27, 25.5, 43.5, 41.5, 65.5, 45, 18, 54.5, 53, 11, 13.5), size = c(940, 1187, 1135, 849, 524, 992, 563, 953, 628, 1122, 394, 264, 1109, 472, 1148, 316, 875, 1096, 836, 355, 407, 693, 745, 719, 511, 667, 576, 498, 381, 459, 810, 758, 433, 602, 862, 979, 1200, 823, 225, 927, 1005, 238, 420))

A : Construct a 95% confidence interval estimate of the slope of the regression line.

B: Construct and interpret a 95% confidence interval for the mean time for all moves with 1000 cubic feet.

C :Construct and interpret a 95% prediction interval for the time required for a move with 1000 cubic feet.

Expert Solution

orchestra answered 1 year ago

# R Hypothesis Tests install.packages("dplyr") tScore_before <- c(40, 62, 74, 22, 64, 65, 49, 49, 49)...

# R Hypothesis Tests install.packages("dplyr") tScore_before <- c(40, 62, 74, 22, 64, 65, 49, 49, 49) tScore_after <- c(68, 61, 64, 76, 90, 75, 66, 60, 63) # Create a data frame my_data <- data.frame( group = rep(c("Score Before", "Score After"), each = 9), scores = c(tScore_before, tScore_after) ) # Print all data print(my_data) #Compute summary statistics by groups library(dplyr) group_by(my_data, group) %>% summarise( count = n(), mean = mean(scores, na.rm = TRUE), sd...

Resident Commuter 22 25 27 23 26 28 26 24 18 20 19 18 22 25...

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A survey of daily travel time had these results (in minutes): 26, 33, 65, 28, 34,...

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A portfolio has 38 percent of its funds invested in Security C and 62 percent invested...

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The following represent the scores 63 96 71 91 65 62 73 66 85 28 70 &n

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Consider the following sample data: 33 38 25 46 31 35 c. Calculate the sample variance....

Consider the following sample data: 33 38 25 46 31 35 c. Calculate the sample variance. (Round your intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.) d. Calculate the sample standard deviation. (Round your intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.) ****Need this correct

Age (yr) 18 28 38 48 58 68 Median Income ($) 17,480 30,650 37,440 41,230 37,570...

Age (yr) 18 28 38 48 58 68 Median Income ($) 17,480 30,650 37,440 41,230 37,570 21,390 Find an appropriate model for the data. Round values to the nearest hundredth.

Age (years) 74 68 63 55 50 45 38 31 26 21 16 Time (hours) 0...

Age (years) 74 68 63 55 50 45 38 31 26 21 16 Time (hours) 0 2 4 6 8 10 12 14 16 18 20 1. Find the equation of a linear regression line for the data where age is the independent variable, x, and time is the dependent variable. (Enter a mathematical expression. Round your numerical answers to three decimal places.) ŷ = 2. Using the equation from part (a), estimate the number of hours a person 30...

For the stress data given below with the nearest error of 1: 27-17-11-24-36-13-29-22-18 23-30-12-46-17-32-48-11-18 18-32-26-24-38-24-15-13-13 18-21-27-20-16-15-37-19-19...

For the stress data given below with the nearest error of 1: 27-17-11-24-36-13-29-22-18 23-30-12-46-17-32-48-11-18 18-32-26-24-38-24-15-13-13 18-21-27-20-16-15-37-19-19 a) Construct a frequency distribution table. b) Construct the three types of statistical graphs. c) Determine the (1) Mean, (2) Median, (3) Mode, (4) Range, Variance, and (6) Standard Deviation.

Date Transaction Units Cost Sell 1/1 Beginning inventory 1,700 $28 3/6 Sale 1,100 $38 6/26 Purchase...

Date Transaction Units Cost Sell 1/1 Beginning inventory 1,700 $28 3/6 Sale 1,100 $38 6/26 Purchase 3,100 29 8/2 Purchase 2,100 30 10/31 Sale 3,500 40 (e) Periodic system, weighted-average cost flow. (f) Perpetual system, moving-average cost flow.

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