Detergent Powder Formulations

Why Detergent PD3 is better than others two? is different amount CFAS, LABS, STPP, Sodium Sulfate and sodium Carbonate in this process affect the quality of the detergent? Explain why

Suppose that, in a given population, the probability of success for a given drug is 0.7 for men and 0.5 for women (the researchers cannot be aware of this). In a study to determine the probability of success, 7 men and 14 women were assigned to receive the drug (no blocking was performed; all were lumped in to the treatment group). What is the bias in this study for each biological sex? (This may be a positive or a negative number).

Suppose that the MPC in a country is 0.7.

Complete the following table by calculating the change in GDP predicted by the multiplier process given each fiscal policy change listed.

Application: Elasticity and hotel rooms.

The following graph input tool shows the daily demand for hotel rooms at the Big Winner Hotel and Casino in Las Vegas, Nevada. To help the hotel management better understand the market, an economist identified three primary factors that affect the demand for rooms each night. These demand factors, along with the values corresponding to the initial demand curve, are shown in the following table and alongside the graph input tool.

Use the graph input tool to help you answer the following questions. You will not be graded on any changes you make to this graph.

Note: Once you enter a value in a white field, the graph and any corresponding amounts in each grey field will change accordingly.

For each of the following scenarios, begin by assuming that all demand factors are set to their original values and Big Winner is charging $350 per room per night.

If average household income increases by 20%, from $50,000 to $60,000 per year, the quantity of rooms demanded at the Big Winner (Falls or Rises ) from ( ) rooms per night to ( ) rooms per night. Therefore, the income elasticity of demand is (Negative or Positive) , meaning that hotel rooms at the Big Winner are ( A normal good or An inferior good ).

If the price of an airline ticket from LAX to LAS were to increase by 20%, from $250 to $300 roundtrip, while all other demand factors remain at their initial values, the quantity of rooms demanded at the Big Winner (Falls or Rises) from ( ) rooms per night to ( ) rooms per night. Because the cross-price elasticity of demand is (Negative or Positive), hotel rooms at the Big Winner and airline trips between LAX and LAS are (Substitutes or Complements).

Big Winner is debating decreasing the price of its rooms to $325 per night. Under the initial demand conditions, you can see that this would cause its total revenue to (Decrease or Increase)  . Decreasing the price will always have this effect on revenue when Big Winner is operating on the (Elastic or Inelastic) portion of its demand curve.

Lab Text Manipulation

Inside the main method, do the following:

• Create an ArrayList of strings and call it parks.
• Read in the names of national parks from the user until the user enters done(or DONE,
  or dOnE, .. ) Keep in mind, that the names of some national parks consist of more than one word, for example, Mesa Verde.
  As you read in the national parks, add them to the list.
• Next, we are going to build a string based on the elements in the list parks. Since the text keeps changing as we add one park at a time, we use class StringBuilder for this task.
  • Use a StringBuilder called sb to create the string  nationalParks .
  • Loop through all the elements of the list  parks and add them one at a time.
    The resulting string should have the following format:
    Favorite National Parks: {park1} | {park2} | . . . | {parkN}
    The parks are separated by a space, a vertical bar, and another space. However, there is no vertical bar after the last element. {park1}, {park2}, {parkN} are the various list elements with updated spelling.
  • Create a private method to update the spelling.
    We can't control whether the user enters the park names in uppercase or lowercase letters. However, we can change the names to a spelling where all letters are lowercase except for the first letters of each individual word. In order to make those changes, create a private method called updateSpelling. It has the following method header:
    private static String updateSpelling(String text)
    E.g.: When you pass the string "MESA VERDE" the method returns "Mesa Verde"
    E.g.: When you pass "yEllOwstOnE" it returns "Yellowstone"
    E.g.: Passing "black canyon of the gunnison" returns "Black Canyon Of The Gunnison"
    E.g.: Passing "Denali" returns "Denali"
  • When you are done building the specified string in SringBuilder, print it.

The output depends on the information provided by the user.

Please enter your favorite National Park or DONE to stop: mesa verde
Please enter your favorite National Park or DONE to stop: black CANYON of ThE gunnisON
Please enter your favorite National Park or DONE to stop: DENALI
Please enter your favorite National Park or DONE to stop: yellowStone
Please enter your favorite National Park or DONE to stop: Done

Favorite National Parks: Mesa Verde | Black Canyon Of The Gunnison | Denali | Yellowstone

In​ baseball, League A allows a designated hitter​ (DH) to bat for the​ pitcher, who is typically a weak hitter. In League​ B, the pitcher must bat. The common belief is that this results in League A teams scoring more runs. In interleague​ play, when League A teams visit League B​ teams, the League A pitcher must bat.​ So, if the DH does result in more​ runs, it would be expected that league A teams will score more runs in League A park than when visiting League B parks. To test this​ claim, a random sample of runs scored by league A teams with and without their DH is given in the accompanying table. Complete parts​ a) through​ d) below.

a) Draw​ side-by-side boxplots of the number of runs scored by League A teams with and without their DH. Choose the correct graph below.

A.

051015AB

Two boxplots, one above the other, share a horizontal axis labeled from 0 to 15 in increments of 1. The bottom boxplot is labeled A and has vertical line segments drawn at 4, 6, and 7. A box encloses the vertical line segments, and horizontal line segments extend from both sides of the box to 0 and 13. An x is plotted at 14. The top boxplot is labeled B and has vertical line segments at 3, 4.5, and 7. A box encloses the vertical line segments, and horizontal line segments extend from both sides of the box to 0 and 11.

B.

051015AB

Two boxplots, one above the other, share a horizontal axis labeled from 0 to 15 in increments of 1. The bottom boxplot is labeled A and has vertical line segments drawn at 4, 6, and 7. A box encloses the vertical line segments, and horizontal line segments extend from both sides of the box to 0 and 9. Three x's are plotted at 12, 13, and 14. The top boxplot is labeled B and has vertical line segments at 2, 3.5, and 6. A box encloses the vertical line segments, and horizontal line segments extend from both sides of the box to 0 and 10.

C.

051015AB

Two boxplots, one above the other, share a horizontal axis labeled from 0 to 15 in increments of 1. The bottom boxplot is labeled A and has vertical line segments drawn at 3, 5, and 6. A box encloses the vertical line segments, and horizontal line segments extend from both sides of the box to 0 and 12. Two x's are plotted at 13 and 14. The top boxplot is labeled B and has vertical line segments at 2, 3.5, and 6. A box encloses the vertical line segments, and horizontal line segments extend from both sides of the box to 0 and 12.

D.

051015AB

Two boxplots, one above the other, share a horizontal axis labeled from 0 to 15 in increments of 1. The bottom boxplot is labeled A and has vertical line segments drawn at 4, 6, and 7. A box encloses the vertical line segments, and horizontal line segments extend from both sides of the box to 1 and 14. The top boxplot is labeled B and has vertical line segments at 2, 3.5, and 6. A box encloses the vertical line segments, and horizontal line segments extend from both sides of the box to 0 and 12.

Does there appear to be a difference in the number of runs between these​ situations?

A. No but the number of runs scored in a League A park appear to be slightly higher than the number of runs scored in a League B park.

B. Yes because the number of runs scored in a League B park appear to have a higher median than the number of runs scored in a League A park.

C.Yes because the number of runs scored in a League A park appear to have a higher median than the number of runs scored in a League B park.

D.No because the number of runs scored in a League A park is about the same as the number of runs scored in a League B park.

​b) Explain why a hypothesis test may be used to test whether the mean number of runs scored for the two types of ballparks differ.

Select all that apply.

A.Each sample has the same sample size.

B.Each sample is obtained independently of the other.

C.Each sample size is small relative to the size of its population.

D.Each sample is a simple random sample.

E.Each sample size is large.

​c) Test whether the mean number of runs scored in a League A park is greater than the mean number of runs scored in a League B park at the

alphaα=0.05 level of significance.

Determine the null and alternative hypotheses for this test. Let mu Subscript Upper AμA

represent the mean number of runs scored by a League A team in a League A park and let

mu Subscript Upper BμB represent the mean number of runs scored by a League A team in a League B park.

Upper H 0H0​:

▼

sigma Subscript Upper AσA

pp mu Subscript Upper AμA

▼

greater than>

equals=

less than<

not equals≠

▼

sigma Subscript Upper BσB

mu Subscript Upper BμB

p 0p0

versus

Upper H 1H1​:

▼

mu Subscript Upper AμA

pp

sigma Subscript Upper AσA

▼

greater than>

equals=

less than<

not equals≠

▼

p0 mu Subscript Upper BμB sigma Subscript Upper BσB Find t0​,the test statistic for this hypothesis test. t0=nothing

​(Round to two decimal places as​ needed.)

Determine the​ P-value for this test.

​P-value=

​(Round to three decimal places as​ needed.)

State the appropriate conclusion. Choose the correct answer below.

A.Do not reject Upper H0. There is not sufficient evidenceThere is not sufficient evidence at the level of significance to conclude that games played with a designated hitter result in more runs.

B.Reject Upper H 0H0.There is not sufficient evidence at the level of significance to conclude that games played with a designated hitter result in more runs.

C.Do not reject Upper H0.There is sufficient evidenceat the level of significance to conclude that games played with a designated hitter result in more runs.

D.Reject Upper H0. There is sufficient evidenceThere is sufficient evidence at the level of significance to conclude that games played with a designated hitter result in more runs.

​d) Construct a 95​% confidence interval for the mean difference in the number of runs scored by League A teams in a League A park and the number of runs scored by League A teams in a League B park. Interpret the interval.

Lower​ bound:

Upper​ bound:

​(Round to three decimal places as​ needed.)

Interpret the confidence interval. Select the correct choice below and fill in the answer boxes to complete your choice.

​(Round to three decimal places as needed. Use ascending​ order)

A. We are 95​%confident the difference between the mean number of runs scored in a League A park and the mean number of runs scored in a League B park is between nothing and nothing.The confidence interval does not containdoes not contain ​zero, so there is sufficient evidence to conclude there is a difference in the mean number of runs scored with or without the DH.

B. We are 95​% confident the difference between the mean number of runs scored in a League A park and the mean number of runs scored in a League B park is between nothing and nothing.The confidence interval contains ​zero, so there is notis not sufficient evidence to conclude there is a difference in the mean number of runs scored with or without the DH.

Find the standard deviation of the following data. Round your answer to one decimal place. x −6 −5 −4 −3 −2 −1 P(X=x) 0.1 0.1 0.3 0.1 0.1 0.3

Project Risk Response

Risk responses and action steps are defined during the risk response planning phase. Here the project team must plan the actions that will be taken should any identified risk actually materialize. This is typically done for some subset of the total population of risk issues identified—most likely those that are of the highest probability and/or impact. Risks can be both negative (threats) and positive (opportunities). The possible strategies for responding to negative risks include the following: avoid, transfer, mitigate, and accept. The possible strategies for responding to positive risks include the following: exploit, enhance, share, and accept.

QUESTION

Based on the below risk register regarding the Pepsi Refresh Program

Summarize the approach for developing risk response strategies. For example, which risks should one first attempt to avoid? Should they do it based on the risk factor score (P*I) or EMV?

Describe the process to use to determine risk triggers (the event that tells someone that the risk event is imminent).

Part II
4. For a diploid species, assume one set of 100 demes, each with a constant size of 10 individuals, and another set of 100 demes, each with 100 individuals.

a) If in each deme the frequencies of neutral alleles A1 and A2 are 0.2 and 0.8, respectively, what fraction of demes in each set is likely to become fixed for allele A1 versus A2? Show your work below:

b) Assume that a neutral mutation arises in each deme. Calculate the probability that it will become fixed in a population of each size. In what fraction of demes do you expect it to become fixed?

c) If fixation occurs, how many generations do you expect it to take?

d) Compare your results for the two sets of demes. What effect does population size have on the results? Explain any differences.

5. Population size is a very important measurement in population genetics.

a) What is the difference between N and Ne? How are they measured/estimated?
Explain in your own words!

b) Ne is often smaller than N for 5 reasons. In your own words, describe these reasons below: