An amusement park studied methods for decreasing the waiting time (minutes) for rides by loading and unloading riders more efficiently. Two alternative loading/unloading methods have been proposed. To account for potential differences due to the type of ride and the possible interaction between the method of loading and unloading and the type of ride, a factorial experiment was designed. Use the following data to test for any significant effect due to the loading and unloading method, the type of ride, and interaction. Use . Factor A is method of loading and unloading; Factor B is the type of ride.

Set up the ANOVA table (to whole number, but -value to 2 decimals and  value to 1 decimal, if necessary).

An amusement park studied methods for decreasing the waiting time (minutes) for rides by loading and unloading riders more efficiently. Two alternative loading/unloading methods have been proposed. To account for potential differences due to the type of ride and the possible interaction between the method of loading and unloading and the type of ride, a factorial experiment was designed. Use the following data to test for any significant effect due to the loading and unloading method, the type of ride, and interaction. Use  = .05. Factor A is method of loading and unloading; Factor B is the type of ride.

1. Set up the ANOVA table (to 2 decimal, if necessary). Round p-value to four decimal places.
   

   Source of Variation	Sum of Squares	Degrees of Freedom	Mean Square	F	p-value
   Factor A
   Factor B
   Interaction
   Error
   Total

   
   
2. The p-value for Factor A is Select:less than .01, between .01 and .025, between .025 and .05, between .05 and .10, greater than .10
3. What is your conclusion with respect to Factor A? Select:Factor A is significant, Factor A is not significant
4. The p-value for Factor B is Select: less than .01, between .01 and .025 between .025 and .05, between .05 and .10, greater than .10
5. What is your conclusion with respect to Factor B?
   Select: Factor B is significant, Factor B is not significant
   
6. The p-value for the interaction of factors A and B is Select: less than .01, between .01 and .025, between .025 and .05, between .05 and .10, greater than .10
7. What is your conclusion with respect to the interaction of Factors A and B?
   Select: The interaction of factors A and B is significant, The interaction of factors A and B is not significantI
   
8. What is your recommendation to the amusement park?
   Select: Use method 1; it has a lower sample mean waiting time and is the best method, Withhold judgment; take a larger sample before making a final decision Since method is not a significant factor, use either loading and unloading method

In a city park a nonuniform wooden beam 9.00 m long is suspended horizontally by a light steel cable at each end. The cable at the left-hand end makes an angle of 30.0∘ with the vertical and has tension 630 N. The cable at the right-hand end of the beam makes an angle of 50.0∘ with the vertical.

a) As an employee of the Parks and Recreation Department, you are asked to find the weight of the beam.

b) Find the location of its center of gravity.

Ms Scott arrives in the ED by car. She reports having been at the park with her spouse and children when she suddenly started having severe shortness of breath….

1. You need to quickly gather information. What questions do you ask?

2. What assessments do you want to make?

Ms Scott tells you that she has no previously known allergies. On her arm you note a small area that looks like a sting or bite. She quickly remembers that she was stung by a bee in the park and had forgotten because of her concern over her difficulty breathing. Your assessment reveals swelling of the lips/tongue, RR 28 and shallow, 02 sat 88%. Her lung sounds reveal wheezes throughout and you hear a faint, high pitched wheeze coming from her upper airway.

3. What do you need to do first?

4. What orders would you like? Why?

The ED healthcare provider comes in to quickly assess and orders:

• Oxygen 2-4 l/min to keep sat above 92%
• Placement of an oral airway
• NS 100 ml/hr
• Epinephrine 1:1000 – 0.4 mg IM
• Solu-Medrol 125 mg IVP
• Albuterol nebulizers
• Telemetry monitoring
• VS q 30 minutes for 2 hours

5. What is the reasoning for these orders?

After a dose of epinephrine, Solu-Medrol, and a bronchodilator, Ms. Scott begins to improve. Later that day, they decide to discharge her to home with a prescription for an epi pen.

6. What do you absolutely need to teach her before she leaves?

7. What other things would you like to teach her?

An amusement park studied methods for decreasing the waiting time (minutes) for rides by loading and unloading riders more efficiently. Two alternative loading/unloading methods have been proposed. To account for potential differences due to the type of ride and the possible interaction between the method of loading and unloading and the type of ride, a factorial experiment was designed. Use the following data to test for any significant effect due to the loading and unloading method, the type of ride, and interaction. Use  = .05. Factor A is method of loading and unloading; Factor B is the type of ride.

1. Set up the ANOVA table (to 2 decimal, if necessary). Round p-value to four decimal places.
   

   Source of Variation	Sum of Squares	Degrees of Freedom	Mean Square	F	p-value
   Factor A
   Factor B
   Interaction
   Error
   Total

   
   
2. The p-value for Factor A is Selectless than .01between .01 and .025between .025 and .05between .05 and .10greater than .10Item 21
   
   What is your conclusion with respect to Factor A?
   SelectFactor A is significantFactor A is not significantItem 22
   
3. The p-value for Factor B is Selectless than .01between .01 and .025between .025 and .05between .05 and .10greater than .10Item 23
   
   What is your conclusion with respect to Factor B?
   SelectFactor B is significantFactor B is not significantItem 24
   
4. The p-value for the interaction of factors A and B is Selectless than .01between .01 and .025between .025 and .05between .05 and .10greater than .10Item 25
   
   What is your conclusion with respect to the interaction of Factors A and B?
   SelectThe interaction of factors A and B is significantThe interaction of factors A and B is not significantItem 26
   
5. What is your recommendation to the amusement park?

Some geysers such as Old Faithful in Yellowstone National Park are remarkably consistent in the periodicity of their eruption. For example, in 1988, 6,900 timed intervals between eruptions for Old Faithful averaged 76.17 minutes, with the shortest observed interval 41 minutes and the longest 114 minutes. In the past 120 years Old Faithful's yearly average interval has always been between 60 and 79 minutes.

It is also well known that the relationship between the length of the eruption and the length of the subsequent interval duration is a positive one. Suppose the following data were collected over a several day period.

1: Compute r, the Pearson correlation coefficient

2: At the 0.05 level of significance, test the null hypothesis that the (“eruption time” and the “interval duration”) population correlation coefficient [ρ] is equal to 0.

3: Compute and use the regression equation you came up with in the previous part (namely “f”) to predict the “interval duration” for an “eruption time” of 6 minutes.

An amusement park studied methods for decreasing the waiting time (minutes) for rides by loading and unloading riders more efficiently. Two alternative loading/unloading methods have been proposed. To account for potential differences due to the type of ride and the possible interaction between the method of loading and unloading and the type of ride, a factorial experiment was designed. Use the following data to test for any significant effect due to the loading and unloading method, the type of ride, and interaction. Use α = 0.05.

a) Find the value of the test statistic for method of loading and unloading.

Find the p-value for method of loading and unloading. (Round your answer to three decimal places.)

p-value =

b) Find the value of the test statistic for type of ride.

Find the p-value for type of ride. (Round your answer to three decimal places.)

p-value =

c) Find the value of the test statistic for interaction between method of loading and unloading and type of ride.

Find the p-value for interaction between method of loading and unloading and type of ride. (Round your answer to three decimal places.)

p-value =

Buckeye Creek Amusement Park is open from the beginning of May to the end of October. Buckeye Creek relies heavily on the sale of season passes. The sale of season passes brings in significant revenue prior to the park opening each season, and season pass holders contribute a substantial portion of the food, beverage, and novelty sales in the park. Greg Ross, director of marketing at Buckeye Creek, has been asked to develop a targeted marketing campaign to increase season pass sales. Greg has data for last season that show the number of season pass holders for each zip code within 50 miles of Buckeye Creek. he has also obtained the total population of each zip code from the U.S. Census bureau website. Greg thinks it may be possible to use regression analysis to predict the number of season pass holders in a zip code given the total population of a zip code. If this is possible, he could then conduct a direct mail campaign that would target zip codes that have fewer than the expected number of season pass holders.

1. Did the estimated regression equation provide a good fit?

2. Use residual analysis to determine whether the assumed regression model is appropriate.

3. Discuss if/how the estimated regression equation should be used to guide the marketing campaign.

4. What other data might be useful to predict the number of season pass holders in a zip code?

An amusement park studied methods for decreasing the waiting time (minutes) for rides by loading and unloading riders more efficiently. Two alternative loading/unloading methods have been proposed. To account for potential differences due to the type of ride and the possible interaction between the method of loading and unloading and the type of ride, a factorial experiment was designed. Use the following data to test for any significant effect due to the loading and unloading method, the type of ride, and interaction. Use . Factor A is method of loading and unloading; Factor B is the type of ride.

Set up the ANOVA table (to whole number, but -value to 2 decimals and value to 1 decimal, if necessary).