1. Urban Pizza bought a used Ford delivery van on January​ 2, 2018​, for $ 23000. The van was expected to remain in service for four years left parenthesis 102000 ​miles). At the end of its useful​ life, Urban management estimated that the​ van's residual value would be $ 2600. The van traveled 40000 miles the first​ year, 33000 miles the second​ year, 18000 miles the third​ year, and 11000 miles in the fourth year.

Instructions:

Prepare a schedule of depreciation expense per year for the van under the three depreciation methods.​ (For units-of-production and​ double-declining-balance methods, round to the nearest two decimal places after each step of the​ calculation.)

Which method best tracks the wear and tear on the​ van?

Which method would Urban prefer to use for income tax​ purposes? Explain your reasoning in detail.

2. Barn Sales Company completed the following note payable​ transactions:

1.How much interest expense must be accrued at December​ 31, 2018​? ​(Round your answer to the nearest whole​ dollar.)

2.Determine the amount of Barn ​Sales' final payment on July ​1, 2019.

3.How much interest expense will Barn Sales report for 2018 and for 2019​? ​(If needed, round your answer to the nearest whole​ dollar.)

Find the maximum value and minimum value in milesTracker. Assign the maximum value to maxMiles, and the minimum value to minMiles. Sample output for the given program:

Min miles: -10
Max miles: 40

import java.util.Scanner;

public class ArraysKeyValue {
public static void main (String [] args) {
Scanner scnr = new Scanner(System.in);
final int NUM_ROWS = 2;
final int NUM_COLS = 2;
int [][] milesTracker = new int[NUM_ROWS][NUM_COLS];
int i;
int j;
int maxMiles; // Assign with first element in milesTracker before loop
int minMiles; // Assign with first element in milesTracker before loop

for (i = 0; i < milesTracker.length; i++){
for (j = 0; j < milesTracker[i].length; j++){
milesTracker[i][j] = scnr.nextInt();
}
}

/* your solution goes here*/
  
minMiles = milesTracker[0][0];
maxMiles = milesTracker[0][0];
for (i=0; i<NUM_ROWS; ++i) {
for(j=0; j< NUM_COLS; ++j) {
if (milesTracker[i][j]> maxMiles)
maxMiles= milesTracker[i][j];
if (milesTracker[i][j]< minMiles)
minMiles= milesTracker[i][i];
}
}
/* Your solution goes here */

System.out.println("Min miles: " + minMiles);
System.out.println("Max miles: " + maxMiles);
}
}

when using the inputs -10 20 30 40 the code works fine, but when its run with different inputs the code can't seem the recognize the Min Miles (ie, 73 0 50 12, the code is suggesting 12 is the minimum output

Question: Analysis and Design Models: What's the Difference?

With the analysis phase behind us, reflect on the models built for the Theater project. How are they different from the models you plan on using during the design phase. Explain the differences in your own words. Next, find an article and/or video to share with the class on the subject.  

Find the standard deviation of the following data. Round your answer to one decimal place.

The table below lists weights​ (carats) and prices​ (dollars) of randomly selected diamonds. Find the​ (a) explained​ variation, (b) unexplained​ variation, and​ (c) indicated prediction interval. There is sufficient evidence to support a claim of a linear​ correlation, so it is reasonable to use the regression equation when making predictions. For the prediction​ interval, use a​ 95% confidence level with a diamond that weighs 0.8 carats. Weight 0.3 0.4 0.5 0.5 1.0 0.7 Price ​$517 ​$1163 ​$1350 ​$1410 ​$5672 ​$2278

a. Find the explained variation. nothing ​(Round to the nearest whole number as​ needed.)

b. Find the unexplained variation. nothing ​(Round to the nearest whole number as​ needed.)

c. Find the indicated prediction interval. ​$ nothingless thanyless than​$ nothing ​(Round to the nearest whole number as​ needed.) Enter your answer in each of the answer boxes.

The maintenance manager at a trucking company wants to build a regression model to forecast the time (in years) until the first engine overhaul based on four explanatory variables: (1) annual miles driven (in 1,000s of miles), (2) average load weight (in tons), (3) average driving speed (in mph), and (4) oil change interval (in 1,000s of miles). Based on driver logs and onboard computers, data have been obtained for a sample of 25 trucks. A portion of the data is shown in the accompanying table.

a. For each explanatory variable, discuss whether it is likely to have a positive or negative causal effect on time until the first engine overhaul.

The effect on time is either Positive or Negative! Fill them in below.

b. Estimate the regression model. (Negative values should be indicated by a minus sign. Round your answers to 4 decimal places.)

TimeˆTime^  = ________+_______ Miles +_______ Load + ________ Speed + _______ Oil

c. Based on part (a), are the signs of the regression coefficients logical?
The below signs will be filled with the word logical or not logical!

d. What is the predicted time before the first engine overhaul for a particular truck driven 57,000 miles per year with an average load of 18 tons, an average driving speed of 57 mph, and 18,000 miles between oil changes. (Round coefficient estimates to at least 4 decimal places and final answer to 2 decimal places.)

Excel data:

Don't care how you solve as long as answers are correct. I will like for it being correct!

Your small biotech firm operates a fleet of two specialized delivery vans in Chicago. As a policy, your firm has decided that the operational life of a van is 3 years (a cycle), and both vans are purchased at the same time to receive discounted fleet pricing. The driving demands placed on the vans are uncertain, as are the maintenance costs, and each van is different in its use, demand, and costs. In the past, the firm has been surprised by unexpectedly high (and low) maintenance costs associated with the vans; thus, it is important to analyze the potential of cost variation and to use this information in the annual-budgeting process. You decide to model the arrival of failures (breakdowns of the van) that lead to maintenance costs—each failure has a cost.

You and your staff decide that the model should be simple, but that it should reflect reality. The model should also determine the variation in maintenance costs for 3-year cycles of vehicle use. To determine maintenance cost, you assume the following: 1) Miles Demand for each van is randomly selected from a defined probability distribution (Table 1) for each year of operation; thus, 3 Miles Demand (one for each year) for each van in a cycle. 2) Once the Miles Demand is known, a Yearly Failure Rate is determined (Table 2). This is a Poisson-average yearly arrival rate and a Poisson distribution with this arrival rate is then sampled to determine Actual number of Failures. 3) Each failure arrival is assigned a randomly selected cost from a set of normally distributed costs (Table 3). Finally, costs are aggregated for all vans over the 3 year cycle (an experiment) and many trials are simulated to create a risk profile for total 3-year maintenance cost.

a) Create a Monte Carlo simulation that simulates the 3-year cost of maintenance for the fleet. A suggested structure is provided to simplify your efforts. Simulate 5000 trials (experiments).

b) Provide the risk profile for the model in (a), along with the summary statistics—mean, standard deviation, and 5th and 95th percentile.

c) Calculate the 95% confidence interval for the mean of the simulation.

d) What is the value ($ reduction in cost) that you would derive if you could reduce the Yrly Fail-Rate by 1 for all Miles Demand for Van 1, through a preventative maintenance program? For example, in table 2 the rate for 25000 would change to 1, the rate for 40000 would change to 2, etc. Produce the new Risk Profile and determine the new summary stats.

e). How much would you budget for the 3-year maintenance cycle to meet up to 90% of the maintenance costs?

PLEASE LIST STEP-BY-STEP PROCESS FOR BUILDING THIS TABLE. THANK YOU SO MUCH!

Company A is trying to sell its website to Company B. As part of the sale, Company A claims that the average user of their site stays on the site for 10 minutes. Company B is concerned that the mean time is significantly less than 10 minutes. Company B collects the times (in minutes) below for a sample of 19 users. Assume normality.

Conduct the appropriate hypothesis test for Company B using a 0.08 level of significance.

a) What are the appropriate null and alternative hypotheses?

H₀: μ = 10 versus H_a: μ > 10

H₀: μ = 10 versus H_a: μ < 10    

H₀: x = 10 versus H_a: x ≠ 10

H₀: μ = 10 versus H_a: μ ≠ 10

b) What is the test statistic? Give your answer to four decimal places.  
c) What is the critical value for the test? Give your answer to four decimal places.  
d) What is the appropriate conclusion?

Reject the claim that the mean time is 10 minutes because the test statistic is larger than the critical point.

Fail to reject the claim that the mean time is 10 minutes because the test statistic is larger than the critical point.  

Reject the claim that the mean time is 10 minutes because the test statistic is smaller than the critical point.

Fail to reject the claim that the mean time is 10 minutes because the test statistic is smaller than the critical point.

How do I convert 60 miles per hour to SIU?

A meteorologist was interested in the average speed of a thunderstorm in his area. He sampled 13 thunderstorms and found that the average speed at which they traveled across the area was 15 miles per hour with a sample standard deviation of 1.7 miles per hour.

Assuming the speed of a thunderstorm is approximately normal, construct a 99% confidence interval for the true average speed of a thunderstorm in his area.

Question

How would I enter this into a TI84 calculator?