Questions
The 2.4 billion working people in the developing countries often have to endure employment conditions, which do not meet even basic occupational safety and health (OSH) standards.

 

PHC261

The 2.4 billion working people in the developing countries often have to endure employment conditions, which do not meet even basic occupational safety and health (OSH) standards. The lack of work safety, excessive workloads, and occupational physical, chemical and biological exposures result in occupational diseases, injuries and as many as 1.2 million fatalities each year. Furthermore, as little as 15% of workers in the developing countries have access to occupational health and safety services.” (Rantanen et al., 2004).

In your own words, to what extent do you agree with the information provided by the quote above? Support your argument by giving further details about developing and developed countries with examples of the services. (250 words)

 

In: Nursing

Find the SSE for the given data and linear models, and indicate which model gives the...

  1. Find the SSE for the given data and linear models, and indicate which model gives the better fit.

(2,4) (6,8) (8,12) (10,0)

  1. Y = - 0.1 x + 7                        SSE = ________
  2. Y = - 0.2 x + 6                        SSE = ________
  3. The better fit is          Y = __________________
  1. The following table shows the average price of a two-bedroom apartment in downtown New York City from 1994 to 2004 (x=0 represents 1994)

Year x

0

2

4

6

8

10

Price (millions)

0.38

0.40

0.60

0.95

1.2

1.6

find:

x = ______              y = ______             xysum of = ______          

x2 = ______            y2 = _______       

Regression line: ___________________________

Correlation Coefficient (2 decimal places): ____________

Using the regression line, what would be the price for 2007? ________

In: Statistics and Probability

Part II: Causes A. Consider whether each of the following relationships is a causal relationship or...

Part II: Causes

A.

Consider whether each of the following relationships is a causal relationship or merely a correlation.

Discuss how you would go about verifying which type it is. (10 points)

1. There has been an increase in the number of twins being born and a later age of marriage in the past

decade.

2. During the past decade there has been a decrease in the size of the Greenland ice cap and an increase in

the number of twins being born.

3. People who are members of a religious organization tend to be happier.

4. Jason drank nine bottles of beer at the party and is having trouble walking straight.

5. Almost all the animals that could flee to higher ground did so shortly before the tsunami struck Indonesia in

2004.

In: Psychology

a) What is considered insider trading? Multiple Choice All of the other statements describe insider trading....

a) What is considered insider trading?

Multiple Choice

  • All of the other statements describe insider trading.

  • Marlene, an individual investor, buys shares in a company because her financial analysis of the company suggests that it is undervalued.

  • Bill buys shares after the company's earnings announcement because he personally knows the auditor who audited the company's earnings announcement / press release.

  • Chris, a hedge fund manager, purchases a 5% stake in a company because he wants to install his colleagues on to the company's board of directors.

  • Karen sells shares in a company before the earnings announcement because her brother-in-law, who's the CEO, said that EPS will fall short of market expectations.

b).

Which of the following statements is true about the classified income statement?

Multiple Choice

  • Income tax expense is subtracted from operating income to obtain pre-tax income.

  • Net income is computed by subtracting operating expenses from gross profit.

  • Cost of goods sold is the difference between net sales revenue and gross profit.

  • Gross sales revenue is the first line of the income statement; contra-revenues is the second line; and net sales revenue is the third line.

  • Dividend expense is classified as a non-operating (other) item on the income statement.

In: Accounting

Creates a function called pick. The function receives a "string" representing one year (the variable with...

Creates a function called pick. The function receives a "string" representing one year (the variable with this "string" will be called uve) and a list containing "strings" representing bank accounts (call this bera list). <br>
• Each account is represented by 8 characters. The format of each account number is "**-**-**", where asterisks are replaced by numeric characters. o
For example, "59-04-23".
• The two central characters of the "string" for each account represent the year the account was created. o
For example, the account "59-04-23" was created in 2004.
Presumes that every year they are from 2000 onwards.
• The year in uve is represented by four characters. o
Example,"2001"
• The feature must return a list of all accounts that were created in the year indicated in uve, with each<br>t without the "-" symbols.<br> o
For example, if the accounts are ["49-01-26", "19-01-33", "99-01-53", "59-04-23"] and the year of interest is<br>"2001", then the function must return ["490126", "190133", "990153"]; note that the accounts follow<br>in the form of "string".<br>
• In addition, the function must return the percent of accounts that were created in the year indicated by uve. <br>
For example, if the accounts are ["49-01-26", "19-01-33", "99-01-53", "59-04-23"] and the year of interest is "2001", then the function should return 75% (three accounts were created in 2001, and there are four<br>accounts, therefore 100 x 3 x 75%)

Python(programming language)

In: Computer Science

Your client, Mary Barnhart, wants to open her own business. She is having difficulty understanding the...

Your client, Mary Barnhart, wants to open her own business. She is having difficulty understanding the purposes of financial statements and how they fit together across time. REQUIRED: Write a one-page letter to Ms. Barnhart explaining the purposes of the income statement, statement of owners' equity, and the balance sheet and how they are linked. Use the attached example for guidance.

Henry Whiteapples

123 Maple Street

Columbus, OH, 45888

December 21, 2004

Dear Mr. Whitebridge,

I understand you are concerned about the Statement of Cash Flows and what it means.

The Statement of Cash Flows is one of four important financial statements for every business. It provides details about the sources and uses of cash during a fiscal period (month, quarter, or year). There are three sections to the Statement of Cash Flows: Operating Activities, Investing Activities, and Financing Activities. The Operating Activities section provides details about cash receipts and payments for day-to-day operations. The Investing Activities section provides details about cash receipts and payments for long-term assets and the Financing Activities section provides details about cash receipts and payments for debt (long-term borrowing) and equity (stock) transactions. The total on this statement is equal to the cash account balance on the Balance Sheet for the same period.

I hope this explanation helps you better understand the Statement of Cash Flows. Please feel free to contact me if you have additional questions.

Sincerely,

Kelsey Sioen

In: Accounting

Year Name MinPressure_before Gender_MF Category alldeaths 1950 Easy 958 1 3 2 1950 King 955 0...

Year    Name    MinPressure_before      Gender_MF       Category        alldeaths
1950    Easy    958     1       3       2
1950    King    955     0       3       4
1952    Able    985     0       1       3
1953    Barbara 987     1       1       1
1953    Florence        985     1       1       0
1954    Carol   960     1       3       60
1954    Edna    954     1       3       20
1954    Hazel   938     1       4       20
1955    Connie  962     1       3       0
1955    Diane   987     1       1       200
1955    Ione    960     0       3       7
1956    Flossy  975     1       2       15
1958    Helene  946     1       3       1
1959    Debra   984     1       1       0
1959    Gracie  950     1       3       22
1960    Donna   930     1       4       50
1960    Ethel   981     1       1       0
1961    Carla   931     1       4       46
1963    Cindy   996     1       1       3
1964    Cleo    968     1       2       3
1964    Dora    966     1       2       5
1964    Hilda   950     1       3       37
1964    Isbell  974     1       2       3
1965    Betsy   948     1       3       75
1966    Alma    982     1       2       6
1966    Inez    983     1       1       3
1967    Beulah  950     1       3       15
1968    Gladys  977     1       2       3
1969    Camille 909     1       5       256
1970    Celia   945     1       3       22
1971    Edith   978     1       2       0
1971    Fern    979     1       1       2
1971    Ginger  995     1       1       0
1972    Agnes   980     1       1       117
1974    Carmen  952     1       3       1
1975    Eloise  955     1       3       21
1976    Belle   980     1       1       5
1977    Babe    995     1       1       0
1979    Bob     986     0       1       1
1979    David   970     0       2       15
1979    Frederic        946     0       3       5
1980    Allen   945     0       3       2
1983    Alicia  962     1       3       21
1984    Diana   949     1       2       3
1985    Bob     1002    0       1       0
1985    Danny   987     0       1       1
1985    Elena   959     1       3       4
1985    Gloria  942     1       3       8
1985    Juan    971     0       1       12
1985    Kate    967     1       2       5
1986    Bonnie  990     1       1       3
1986    Charley 990     0       1       5
1987    Floyd   993     0       1       0
1988    Florence        984     1       1       1
1989    Chantal 986     1       1       13
1989    Hugo    934     0       4       21
1989    Jerry   983     0       1       3
1991    Bob     962     0       2       15
1992    Andrew  922     0       5       62
1993    Emily   960     1       3       3
1995    Erin    973     1       2       6
1995    Opal    942     1       3       9
1996    Bertha  974     1       2       8
1996    Fran    954     1       3       26
1997    Danny   984     0       1       10
1998    Bonnie  964     1       2       3
1998    Earl    987     0       1       3
1998    Georges 964     0       2       1
1999    Bret    951     0       3       0
1999    Floyd   956     0       2       56
1999    Irene   987     1       1       8
2002    Lili    963     1       1       2
2003    Claudette       979     1       1       3
2003    Isabel  957     1       2       51
2004    Alex    972     0       1       1
2004    Charley 941     0       4       10
2004    Frances 960     1       2       7
2004    Gaston  985     0       1       8
2004    Ivan    946     0       3       25
2004    Jeanne  950     1       3       5
2005    Cindy   991     1       1       1
2005    Dennis  946     0       3       15
2005    Ophelia 982     1       1       1
2005    Rita    937     1       3       62
2005    Wilma   950     1       3       5
2005    Katrina 902     1       3       1833
2007    Humberto        985     0       1       1
2008    Dolly   963     1       1       1
2008    Gustav  951     0       2       52
2008    Ike     935     0       2       84
2011    Irene   952     1       1       41
2012    Isaac   965     0       1       5
2012    Sandy   945     1       2       159
                                        

Open Hurricane data.

SETUP: Is it reasonable to assume that average hurricane pressure for category 4 is different from that of category 1? Given the data, your job is to check if this assertion is indeed reasonable or not. HINT: Read Lecture 24.

19. What would be the correct Null-Hypothesis?

  • a. Data related to two different categories should not be related.
  • b. The population averages are equal.
  • c. The slope of the regression line is equal to zero.
  • d. None of these.

20. The P-value is 3.33E-09. What can be statistically concluded?

  • a. We reject the Null Hypothesis.
  • b. We accept the Null Hypothesis.
  • c. We cannot reject the Null Hypothesis.
  • d. None of these.

21. Write a one-line additional comment.

  • a. We cannot conclude that data related to two different hurricane categories are related.
  • b. We are confident that hurricanes with category 4 has different pressure than those of category 1.
  • c. We cannot conclude that hurricanes with category 4 has lower pressure than those of category 1.
  • d. None of these.

In: Statistics and Probability

Year Name MinPressure_before Gender_MF Category alldeaths 1950 Easy 958 1 3 2 1950 King 955 0...

Year    Name    MinPressure_before      Gender_MF       Category        alldeaths
1950    Easy    958     1       3       2
1950    King    955     0       3       4
1952    Able    985     0       1       3
1953    Barbara 987     1       1       1
1953    Florence        985     1       1       0
1954    Carol   960     1       3       60
1954    Edna    954     1       3       20
1954    Hazel   938     1       4       20
1955    Connie  962     1       3       0
1955    Diane   987     1       1       200
1955    Ione    960     0       3       7
1956    Flossy  975     1       2       15
1958    Helene  946     1       3       1
1959    Debra   984     1       1       0
1959    Gracie  950     1       3       22
1960    Donna   930     1       4       50
1960    Ethel   981     1       1       0
1961    Carla   931     1       4       46
1963    Cindy   996     1       1       3
1964    Cleo    968     1       2       3
1964    Dora    966     1       2       5
1964    Hilda   950     1       3       37
1964    Isbell  974     1       2       3
1965    Betsy   948     1       3       75
1966    Alma    982     1       2       6
1966    Inez    983     1       1       3
1967    Beulah  950     1       3       15
1968    Gladys  977     1       2       3
1969    Camille 909     1       5       256
1970    Celia   945     1       3       22
1971    Edith   978     1       2       0
1971    Fern    979     1       1       2
1971    Ginger  995     1       1       0
1972    Agnes   980     1       1       117
1974    Carmen  952     1       3       1
1975    Eloise  955     1       3       21
1976    Belle   980     1       1       5
1977    Babe    995     1       1       0
1979    Bob     986     0       1       1
1979    David   970     0       2       15
1979    Frederic        946     0       3       5
1980    Allen   945     0       3       2
1983    Alicia  962     1       3       21
1984    Diana   949     1       2       3
1985    Bob     1002    0       1       0
1985    Danny   987     0       1       1
1985    Elena   959     1       3       4
1985    Gloria  942     1       3       8
1985    Juan    971     0       1       12
1985    Kate    967     1       2       5
1986    Bonnie  990     1       1       3
1986    Charley 990     0       1       5
1987    Floyd   993     0       1       0
1988    Florence        984     1       1       1
1989    Chantal 986     1       1       13
1989    Hugo    934     0       4       21
1989    Jerry   983     0       1       3
1991    Bob     962     0       2       15
1992    Andrew  922     0       5       62
1993    Emily   960     1       3       3
1995    Erin    973     1       2       6
1995    Opal    942     1       3       9
1996    Bertha  974     1       2       8
1996    Fran    954     1       3       26
1997    Danny   984     0       1       10
1998    Bonnie  964     1       2       3
1998    Earl    987     0       1       3
1998    Georges 964     0       2       1
1999    Bret    951     0       3       0
1999    Floyd   956     0       2       56
1999    Irene   987     1       1       8
2002    Lili    963     1       1       2
2003    Claudette       979     1       1       3
2003    Isabel  957     1       2       51
2004    Alex    972     0       1       1
2004    Charley 941     0       4       10
2004    Frances 960     1       2       7
2004    Gaston  985     0       1       8
2004    Ivan    946     0       3       25
2004    Jeanne  950     1       3       5
2005    Cindy   991     1       1       1
2005    Dennis  946     0       3       15
2005    Ophelia 982     1       1       1
2005    Rita    937     1       3       62
2005    Wilma   950     1       3       5
2005    Katrina 902     1       3       1833
2007    Humberto        985     0       1       1
2008    Dolly   963     1       1       1
2008    Gustav  951     0       2       52
2008    Ike     935     0       2       84
2011    Irene   952     1       1       41
2012    Isaac   965     0       1       5
2012    Sandy   945     1       2       159
Test if there is a significant difference in the death by Hurricanes and Min Pressure measured. Answer the questions for Assessment. (Pick the closest answer)

7. What is the P-value?

  • a. #DIV/0!
  • b. 0.384808843
  • c. 0.634755682
  • d. None of these

8. What is the Statistical interpretation?

  • a. The P-value is too large to have a conclusive answer.
  • b. The P-value is too small to have a conclusive answer.
  • c. ​​The P-value is much smaller than 5% thus we are certain that the average of hurricane deaths is significantly different from average min pressure.
  • d. None of the above.

9. What is the conclusion?

  • a. The statistics does not agree with the intuition since one would expect that stronger hurricanes to be deadlier.
  • b. ​​Statistical interpretation agrees with the intuition, the lower the pressure the stronger the hurricanes.
  • c. Statistics confirms that hurricanes’ pressure does relate to the death count.
  • d. The test does not make statistical sense, it compares “apples and oranges”.

In: Statistics and Probability

Open Hurricanes data. Test if there is a significant difference in the death by Hurricanes and...

Open Hurricanes data.

Test if there is a significant difference in the death by Hurricanes and Min Pressure measured. Answer the questions for Assessment. (Pick the closest answer)

7. What is the P-value?

  • a. #DIV/0!
  • b. 0.384808843
  • c. 0.634755682
  • d. None of these

8. What is the Statistical interpretation?

  • a. The P-value is too large to have a conclusive answer.
  • b. The P-value is too small to have a conclusive answer.
  • c. ​​The P-value is much smaller than 5% thus we are certain that the average of hurricane deaths is significantly different from average min pressure.
  • d. None of the above.

9. What is the conclusion?

  • a. The statistics does not agree with the intuition since one would expect that stronger hurricanes to be deadlier.
  • b. ​​Statistical interpretation agrees with the intuition, the lower the pressure the stronger the hurricanes.
  • c. Statistics confirms that hurricanes’ pressure does relate to the death count.
  • d. The test does not make statistical sense, it compares “apples and oranges”.

Year   Name   MinPressure_before   Gender_MF   Category   alldeaths
1950   Easy   958   1   3   2
1950   King   955   0   3   4
1952   Able   985   0   1   3
1953   Barbara   987   1   1   1
1953   Florence   985   1   1   0
1954   Carol   960   1   3   60
1954   Edna   954   1   3   20
1954   Hazel   938   1   4   20
1955   Connie   962   1   3   0
1955   Diane   987   1   1   200
1955   Ione   960   0   3   7
1956   Flossy   975   1   2   15
1958   Helene   946   1   3   1
1959   Debra   984   1   1   0
1959   Gracie   950   1   3   22
1960   Donna   930   1   4   50
1960   Ethel   981   1   1   0
1961   Carla   931   1   4   46
1963   Cindy   996   1   1   3
1964   Cleo   968   1   2   3
1964   Dora   966   1   2   5
1964   Hilda   950   1   3   37
1964   Isbell   974   1   2   3
1965   Betsy   948   1   3   75
1966   Alma   982   1   2   6
1966   Inez   983   1   1   3
1967   Beulah   950   1   3   15
1968   Gladys   977   1   2   3
1969   Camille   909   1   5   256
1970   Celia   945   1   3   22
1971   Edith   978   1   2   0
1971   Fern   979   1   1   2
1971   Ginger   995   1   1   0
1972   Agnes   980   1   1   117
1974   Carmen   952   1   3   1
1975   Eloise   955   1   3   21
1976   Belle   980   1   1   5
1977   Babe   995   1   1   0
1979   Bob   986   0   1   1
1979   David   970   0   2   15
1979   Frederic   946   0   3   5
1980   Allen   945   0   3   2
1983   Alicia   962   1   3   21
1984   Diana   949   1   2   3
1985   Bob   1002   0   1   0
1985   Danny   987   0   1   1
1985   Elena   959   1   3   4
1985   Gloria   942   1   3   8
1985   Juan   971   0   1   12
1985   Kate   967   1   2   5
1986   Bonnie   990   1   1   3
1986   Charley   990   0   1   5
1987   Floyd   993   0   1   0
1988   Florence   984   1   1   1
1989   Chantal   986   1   1   13
1989   Hugo   934   0   4   21
1989   Jerry   983   0   1   3
1991   Bob   962   0   2   15
1992   Andrew   922   0   5   62
1993   Emily   960   1   3   3
1995   Erin   973   1   2   6
1995   Opal   942   1   3   9
1996   Bertha   974   1   2   8
1996   Fran   954   1   3   26
1997   Danny   984   0   1   10
1998   Bonnie   964   1   2   3
1998   Earl   987   0   1   3
1998   Georges   964   0   2   1
1999   Bret   951   0   3   0
1999   Floyd   956   0   2   56
1999   Irene   987   1   1   8
2002   Lili   963   1   1   2
2003   Claudette   979   1   1   3
2003   Isabel   957   1   2   51
2004   Alex   972   0   1   1
2004   Charley   941   0   4   10
2004   Frances   960   1   2   7
2004   Gaston   985   0   1   8
2004   Ivan   946   0   3   25
2004   Jeanne   950   1   3   5
2005   Cindy   991   1   1   1
2005   Dennis   946   0   3   15
2005   Ophelia   982   1   1   1
2005   Rita   937   1   3   62
2005   Wilma   950   1   3   5
2005   Katrina   902   1   3   1833
2007   Humberto   985   0   1   1
2008   Dolly   963   1   1   1
2008   Gustav   951   0   2   52
2008   Ike   935   0   2   84
2011   Irene   952   1   1   41
2012   Isaac   965   0   1   5
2012   Sandy   945   1   2   159
                  

In: Statistics and Probability

Do you believe marketing efforts should be to maintain a relationship with current customers or new...

Do you believe marketing efforts should be to maintain a relationship with current customers or new customers? Why?

In: Operations Management