The manager of an amusement park would like to be able to predict daily attendance in order to develop more accurate plans about how much food to order and how many ride operators to hire. After some consideration, he decided that the following three factors are critical:
Yesterday’s attendance
Weekday or weekend (1 if weekend, 0 if weekday)
Predicted weather
Rain forecast ( 1 if forecast for rain, 0 if not)
Sun ( 1 if mostly sunny, 0 if not)
He then took a random sample of 40 days. For each day, he recorded the attendance, the previous day’s attendance, day of the week, and weather forecast. An example of the first few lines of Data and the regression output are below:
Attendance   Yest Att   I1   I2   I3
7882   8876   0   1   0
6115   7203   0   0   0
5351   4370   0   0   0
8546   7192   1   1   0

SUMMARY OUTPUT                  
                      
Regression Statistics                  
Multiple R   0.836766353                  
R Square   0.700177929                  
Adjusted R Square   0.665912549                  
Standard Error   810.7745532                  
Observations   40                  
                      
ANOVA                      
    df   SS   MS   F   Significance F  
Regression   4   53729535   13432384   20.43398   9.28E-09  
Residual   35   23007438   657355.4          
Total   39   76736973                 
                      
    Coefficients   Standard Error   t Stat   P-value   Lower 95%   Upper 95%
Intercept   3490.466604   469.1554   7.439894   1.04E-08   2538.031   4442.903
Yest Att   0.368547078   0.077895   4.731349   3.6E-05   0.210412   0.526682
I1   1623.095785   492.5497   3.295294   0.002258   623.1668   2623.025
I2   733.4646317   394.3718   1.85983   0.071331   -67.1527   1534.082
I3   765.5429068   484.6621   -1.57954   0.123209   -1749.46   218.3734
Test to see if the model is valid. Use alpha = .05
Can we conclude that weather is a factor in determining attendance?
If the manager is looking for a way to help predict attendance, Is this a good model to use? How would you suggest making this model better?

please give proper details for the answer. Thank you

The manager of an amusement park would like to be able to predict daily attendance in order to develop more accurate plans about how much food to order and how many ride operators to hire. After some consideration, he decided that the following three factors are critical: Yesterday’s attendance Weekday or weekend Predicted weather He then took a random sample of 36 days. For each day, he recorded the attendance, the previous day’s attendance, day of the week, and weather forecast(mostly sunny, rain, cloudy). The first independent variable is interval, but the other two are nominal. a. Create the three indicator variables you need. b. Conduct a regression analysis. c. Is this model valid? Explain. d. Can we conclude that weather is a factor in determining attendance? e. Do these results provide sufficient evidence that weekend attendance is, on average, larger than weekday attendance? f. Do these results provide sufficient evidence that mostly sunny attendance is, on average, larger than cloudy attendance?

Dandy's Fun Park is evaluating the purchase of a new game to be located on its Midway.? Dandy's has narrowed their choices down to? two: the Wacky Water Race game and the

Whackminus?Aminus?Mole

game. Financial data about the two choices follows.

What is the total present value of future cash inflows and residual value from the

Whackminus?Aminus?Mole

?game?

A man is hiking at a park. At the beginning, he followed a straight trail. From the starting point, he traveled two miles down the first trail. Then he turned to his left by 30 degree angle to follow a second trail for one point five miles. Next, he turned to his right by 160 degree angle and follow a third trail for one point seven miles. At this point he was getting very tired and would like to get back as quickly as possible, but all of the available trails seem to lead him deeper into the woods. He would like to take a shortcut directly through the woods. How far to his right should you suggest him to turn, and how far do he have to walk, to go directly back to his starting point?

Q1: The man has to turn ____ degree to the right and walk ___ miles to the starting point.

The health of the bear population in a park is monitored by periodic measurements taken from anesthetized bears. A sample of the weights of such bears is given below. Find a​ 95% confidence interval estimate of the mean of the population of all such bear weights. The​ 95% confidence interval for the mean bear weight is the following.

data table 80 344 416 348 166 220 262 360 204 144 332 34 140 180

Technology is taking much of the fun out of finding a place to park the car. Now, in cities from New York to Seattle, the door is open to a host of wireless technologies seeking to improve the parking meter even further. Chicago and Sacramento, CA, among others are equipping enforcement vehicles with infrared cameras capable of scanning license plates even at 30 miles an hour. Using a global positioning system, the cameras can tell which individual cars have parked too long in a two-hour parking zone. At a cost of $75,000 a camera, the system is an expensive upgrade of the old method of chalking tires and then coming back two hours later to see if the car has moved.

Parking czars in municipalities across the country are starting to realize parking meters' original goals: generating revenue and creating a continuous turnover of parking spaces on city streets. Clearly, their main questions are "Would there be enough new revenue from installing the expensive parking monitoring devices?" and "How many devices should be installed to maximize the revenue streams?" From the device manufacturing's point of view, the question is "Would there be enough demand for their products to justify the investment required in new facilities and marketing?" If the manufacturing decides to go ahead and market the products, but the actual demand is far less than its forecast or the adoption of the technology is too low, what would be the potential financial risk?

Soap Makers International

Several years ago, Ingrid Krause wanted some international expertise and applied for a transfer to her company’s soap division, which is located south of Warsaw, Poland. The soap division manufactures hand soap for use in a large number of settings, from hospitals to luxury hotels. Ingrid was awarded the transfer to the soap division and was assigned to the accounting department. She is responsible for overseeing the costing and probability analysis of the various soaps and soap-making processes. During her tenure in the soap division, there were numerous changes in the number of soaps manufactured and the processes to make the different soaps. Consequently, Ingrid’s position required her to consider changes in the accounting processes to reflect the changes in the soap division’s business.

For several decades, the company’s soap-making process required a large labour force that manufactured and packaged the soap mainly by hand. Local economic changes meant that the labour force that the factory required was not as available as it had been in the past. As a result, the division was experiencing slower processing time, and more snap being rejected during inspections because of quality concerns. To address the issues related to the lack of labour availability, the division’s management decided three years ago that automation was the way to go. Consequently, over the last three years, the soap making processes have changed with the implementation of automation.

The automation of the soap making processes have allowed for a much larger variety of soap and packing, a reduced direct labour force and direct labour costs, and a higher level of traceability of costs to the various soaps because of technological improvements. Soaps made for industrial applications require different ingredients, less time in processing, less time in finishing, and less time in and cheaper packaging than do soaps for the hotel industry. The costs of materials and packaging are directly traceable to the various types of soaps through new software that uses bar codes and counters to trace material costs to the various soaps directly.

Ingrid feels that the current costing system should be revisited. The cost driver for allocation of the overhead costs (such as supervisory salaries and plant utilities) have always been direct labour hours cost. However, given the decline in the use of labour due to automation, Ingrid is questioning its suitability as a basis of allocation. Ingrid would like to explore activity based costing to allocate overhead costs.

Ingrid has gathered cost data for two representative soaps: one sold to hospitals and one sold to hotels. Further, Ingrid has gathered data from the automated system on the amount of time each type of soap spends in the three manufacturing processes: processing, finishing, and packaging. The soap is produced in large batches, consequently, the data are adjusted to reflect the average cost per 100g of soap. The data for type of soap for one month’s production are in Exhibit 1.

REQUIRED

1. Calculate the costs (of direct material, direct labour, and overhead) for each of the two representative types of soap using direct labour as the basis for the allocation of overhead.

EXHIBIT 1 – COSTS FOR ONE MONTH’S PRODUCTION OF SOAP

EXHIBIT 2 – TIME REQUIRED FOR ONE MONTH’S PRODUCTION OF SOAP

Use Newton’s method to find the real root (in four decimal places) near 0.5 of the equation x^5 −4x^2 + 2 = 0

After crossing over has already occurred, the ________ assembles near the centromere and allows microtubules to attach so that centromeres can be pulled to opposite poles

Describe the difference between a substitutional solute atom, an interstitial solute atom, and a vacancy. Discuss whether the stress in the material near the defect will be tensile or compressive