Pizza analysis, lab3pr1.py You noticed that the menu of your favorite pizza

chain store is rather complicated. They offer a range of pizza size and price op-
tions, making it difficult to see what option offers the most pizza for your dol-
lars. So you decide to write program that calculates the cost per square inch

of a circular pizza, given its diameter and price, similar to how grocery stores
display cost-per-ounce prices. The formula for area is A = r

2 ∗ π. Use two func-
tions: one called area(radius) to compute the area of a pizza, and one called

cost per inch(diameter, price) to compute cost per square inch. Sample runs
of your program should look like this:

Please enter the diameter of your pizza, in inches: 20
Please enter its cost, in dollars: 20
The cost is 0.06 dollars per square inch.
>>>>
Please enter the diameter of your pizza, in inches: 8.5
Please enter its cost, in dollars: 12.99
The cost is 0.23 dollars per square inch.

Use the built-in Python function round(value, 2) to round the final cost-per-
inch value to two decimal points. Use import math and math.pi to get the value

of pi for area computation.

use python

Standard labour cost of producing 40 units of a product is 30-hour work by skilled workers at a standard rate of Rs. 60 per hour and 90-hour work by unskilled workers at standard rate of Rs. 20 per hour. 40 units of the product were produced for which the skilled workers were paid for 20 hours at Rs. 55 per hour and unskilled workers were paid for 130 hours at Rs. 24 per hour. Due to a machine break-down, both skilled as well as unskilled workers lost 9 hours each. They were paid even for this time.

Calculate: (i) LCV; (ii) LRV; (iii) LEV; (iv) LITV; (v) LMV; (vi) LYV.

I am conducting a research study.  I have two populations. Sample population 1 is a control group. Sample population 2 has received the intervention.

The question is, how do I determine if there is a relationship between the two populations using the data sets below:

• Sample from Population 1: 33, 29, 35, 39, 39, 41, 25, 33, 38
• Sample from Population 2: 46, 43, 42, 46, 44, 47, 50, 43, 39

I am conducting a research study.  I have two populations. Sample population 1 is a control group. Sample population 2 has received the intervention.

The question is, how do I determine if there is a relationship between the two populations using the data sets below:

• Sample from Population 1: 33, 29, 35, 39, 39, 41, 25, 33, 38
• Sample from Population 2: 46, 43, 42, 46, 44, 47, 50, 43, 39

The following data set shows the ages of the Best Actress and Best Actor award at a given awards show for various years:

Using a Sign Test, test the claim that there is no median difference between the ages of Best Actress and Best Actor award winners.

Find the null and alternative hypothesis.

H0:A)The median of the differences is NOT zero.

B)The median of the differences is zero.

C)The median age of actresses is more than the median age of actors.

D)The median age of actresses is less than the median age of actors.

H1:A)The median age of actresses is less than the median age of actors.

   B)The median of the differences is zero.

   C)The median of the differences is NOT zero.

D)The median age of actresses is more than the median age of actors.

If we consider + to represent when the female was older than the male, then how many of each sign is there?

Positive Signs:

Negative Signs:

Total Signs:

What is the p-value?

At a 0.025 significance, what is the conclusion about the null? A)Reject the null hypothesis.

B)Support the null hypothesis.

C)Fail to reject the null hypothesis.

   D)Fail to support the null hypothesis.

What is the conclusion about the claim? A)There is insufficient evidence to support the claim that there is no difference in median age.

   B)Support the claim that there is no difference in median age.

C)Fail to reject the claim that there is no difference in median age

   D)Reject the claim that there is no difference in median age.

Let's now perform a mean-matched pairs test to test the claim that there is no mean difference between the age of males and females. For the context of this problem, d=x2−x1 where the first data set represents actress (female) ages and the second data set represents male (actor) ages. We'll continue to use a significance of 0.025. You believe the population of difference scores is normally distributed, but you do not know the standard deviation.

H0: μd=0

H1:μd≠0

What is the critical value for this test? t=±

What is the test statistic for this sample? t=

What is the p-value?

Conclusion about the null: A)Support the null hypothesis.

   B)Reject the null hypothesis.

   C)Fail to reject the null hypothesis.

   D)Fail to support the null hypothesis.

Conclusion about the claim: A)Support the claim that there is no mean difference in the ages.

B)There is insufficient evidence to support the claim that there is no mean difference in the ages.

   C)Reject the claim that there is no mean difference in the ages.

D)Fail to reject the claim that there is no mean difference in the ages.

How were these two tests similar?

How were these two tests different?

The following   information is given for a company.

Risk free rate: 4%

Market risk premium: 7%

Expected growth rate of cash flows after 4.year = 5%

Beta Asset = 1.6

Beta Debt=1

Cost of Debt=8%

The company is planning to change the capital structure by the end of its 2^rd year. For the first two years debt to equity   ratio is 2/3 and 1/4 afterwards. Assume the cost of debt is decreased to 6% with the change in the debt of the company.   Calculate the value of the company using WACC approach. Assume corporate tax rate is 40%.

The quality of the orange juice produced by a manufacturer is constantly monitored. There are numerous sensory and chemical components that combine to make the best-tasting orange juice. For example, one manufacturer has developed a quantitative index of the “Sweetness” of orange juice (the higher the index, the sweeter the juice). Is there a relationship between the sweetness index and a chemical measure such as the amount of water-soluble pectin (parts per million) in the orange juice? Data collected on these two variables for 30 production runs at a juice manufacturing plant are shown in the table. Suppose a manufacturer wants to use simple linear regression to predict the sweetness from the amount of pectin. Perform the linear regression analysis and answer the following questions.

1. Is the whole regression model significant in predicting the sweetness of orange juice? Make sure to show which values you use to make the decision.

2. Write down the regression model using the actual values from regression analysis and actual names of the variables.

3. What is the value of the estimated slope? Interpret the value of the estimated slope in terms of orange juice sweetness and amounts of pectin.

4. What is the value of the estimated intercept? Interpret the value in terms of orange juice sweetness and amounts of pectin.

5. If the amount of pectin is decreased by 5 units, how will the sweetness of the orange juice change?.

A 50-year-old man has been suffering from substernal pain for the last 5 months, particularly on waking up in the morning. He lost his job a year ago and was suffering from depression. He consumes about 12–16 cans of beer every day. He has lost his appetite too and says that eating aggravates pain.

• Is this acute or chronic gastritis?
• What factors may lead to the development of gastritis?
• What investigation should be performed?
• How can the patient be treated?

A 50-year-old man has been suffering from substernal pain for the last 5 months, particularly on waking up in the morning. He lost his job a year ago and was suffering from depression. He consumes about 12–16 cans of beer every day. He has lost his appetite too and says that eating aggravates pain.

• Is this acute or chronic gastritis?
• What factors may lead to the development of gastritis?
• What investigation should be performed?
• How can the patient be treated?