Short Answer Writing Assignment All answers should be complete sentences.

In the Week 2 Lab, you found the mean and the standard deviation for the SLEEP variable for both males and females. Use those values for follow these directions to calculate the numbers again.

(From Week 2 Lab: Calculate descriptive statistics for the variable Sleep by Gender. Sort the data by gender by clicking on Data and then Sort. Copy the Sleep of the males from the data file into the Descriptive Statistics worksheet of the Week 1 Excel file. [Write down the mean and standard deviation.] These are sample data. Then, copy and paste the female data into the Descriptive Statistics workbook and do the same. Keep three decimal places.)

You will also need the number of males and the number of females in the dataset. You can actually count these in the dataset. Then use the Week 5 spreadsheet to calculate the following confidence intervals. The male confidence interval would be one calculation in the spreadsheet and the females would be a second calculation.

1. Give and interpret the 95% confidence intervals for males and a second 95% confidence interval for females on the SLEEP variable. Which is wider and why?

2. Give and interpret the 99% confidence intervals for males and a second 99% confidence interval for females on the SLEEP variable. Which is wider and why? We need to find the confidence interval for the SHOE SIZE variable. To do this, we need to find the mean and standard deviation with the Week 1 spreadsheet. Then we can the Week 5 spreadsheet to find the confidence interval. This does not need to be separated by males and females, rather one interval for the entire data set. First, find the mean and standard deviation by copying the SHOE SIZE variable and pasting it into the Week 1 spreadsheet. Write down the mean and the sample standard deviation as well as the count. Open the Week 5 spreadsheet and type in the values needed in the green cells at the top to find the confidence interval.

3. Give and interpret the 95% confidence interval for the size of students’ shoes. Change the confidence level to 99% to find the 99% confidence interval for the SHOE SIZE variable.

4. Give and interpret the 99% confidence interval for the size of students’ shoes.

5. Compare the 95% and 99% confidence intervals for the size of students’ shoes. Explain the difference between these intervals and why this difference occurs.

6. Find the mean and standard deviation of the DRIVE variable by copying that variable into the Week 1 spreadsheet. Use the Week 4 spreadsheet to determine the percentage of data points from that data set that we would expect to be less than 25. To find the actual percentage in the dataset, sort the DRIVE variable and count how many of the data points are less than 25 out of the total 35 data points. That is the actual percentage. How does this compare with your prediction? Mean: ______________ Standard deviation: ____________________ Predicted percentage: Actual percentage: Comparison ___________________________________________________ ______________________________________________________________

7. What percentage of data would you predict would be between 25 and 50 and what percentage would you predict would be more than 50 miles? Use the Week 4 spreadsheet again to find the percentage of the data set we expect to have values between 25 and 50 as well as for more than 50. Now determine the percentage of data points in the dataset that fall within each of these ranges, using same strategy as above for counting data points in the data set. How do each of these compare with your prediction and why is there a difference? Predicted percentage between 25 and 50: ______________________________ Actual percentage: Predicted percentage more than 50 miles: Actual percentage: ___________________________________________ Comparison ____________________________________________________ _______________________________________________________________ Why? __________________________________________________________ ________________________________________________________________

October

1. S.Erickson invested $50,000 cash, a $16,000 pool equipment, and $12,000 of office equipment in the company.

2. The company paid $4,000 cash for five months’ rent.

3. The company purchased $1,620 of office supplies on credit from Todd’s Office Products.

5. The company paid $4,220 cash for one year’s premium on a property and liability insurance policy.

6. The company billed Deep End Co $4,800 for services performed in installing a new pool

8. The company paid $1, 620 cash for the office supplies purchased from Todd’s Office Products on October 3.

10. The company hired Julie Kruitas a part-time assistant for $136 per day, as needed.

12. The company billed Deep End Co another $1,600 for services performed.

15. The company received $4,800 cash from Deep End Co as partial payment on its account.

17. The company paid $750 cash to repair pool equipment that was damaged when moving it.

20. The company paid $1,958 cash for advertisements published in the local newspaper.

22. The company received $1,600 cash from Deep End Co. on its account.

28. The company billed Happy Summer Corp $6,802 for consulting services performed.

31. The company paid $952 cash for Julie Kruit’s wages for seven days’ work.

31. S.Erickson withdrew $3,500 cash from the company for personal use.

November

1. The Company reimbursed S. Erickson in cash for business automobile mileage allowance (Erickson logged 1,500 miles at $0.32 per mile).

2. The company received $5,630 cash from Underground Inc. for consulting services performed.

5. The company purchased office supplies for $1,325 cash from Todd’s Office Products.

8. The company billed Slides R Us $7,568 for services performed.

13. The company agreed to perform future services for Henry’s Pool and Spa Co. No work has been performed.

18. The company received $2,802 cash from Happy Summer Corp as partial payment of the October 28 bill.

22. The company donated $450 cash to the United Way in the company’s name.

24. The company completed work and sent a bill for $4,800 to Henry’s Pool and Spa Co.

25. The company sent another bill to Happy Summer Corp for the past-due amount of$4,000.

28. The company reimbursed S. Erickson in cash for business automobile mileage(1,300miles at $0.32 per mile).

30. The company paid cash to Julie Kruit for 14 days’ work.

30. S.Erickson withdrew $1,500 cash from the company for personal use.

December

2. Paid $1,200 cash to West Side Mall for Splashing Around’s share of mall advertising costs.

3. Paid $350 cash for minor repairs to the company’s pool equipment.

4. Received $ 4,800 cash from Henry’s Pool and Spa Co. for the receivable from November.

10. Paid cash to Julie Kruit for six days of work at the rate of $136 per day.

14. Notified by Henry’s Pool and Spa Co. that Splashing Around’s bid of $10,000 on a proposed project has been accepted. Henry’s paid a $6,500 cash advance to Splashing Around

15. Purchased $1,400 of office supplies on credit from Todd’sOffice Products.

16. Sent a reminder to Slides R Us to pay the fee for services recorded on November 8.

20. Completed a project for Underground Inc and received $6,545 cash.

22–26. Took the week off for the holidays.

28. Received $4,500 cash from Slides R Us on its receivable.

29. Reimbursed S.Erickson for business automobile mileage (500 miles at $0.32 per mile).31.S.Erickson withdrew $2,500 cash from the company for personal use

Prepare an income statement for the three months ended December 31, 2019

Prepare a statement of owner’s equity for the three months ended December 31, 2019

Prepare a classified balance sheet as of December 31, 2019

Record the closing entries for Splashing Around

Post the closing entries to the general ledger under "closing entry"

Prepare a post-closing trial balance as of December 31, 2019.

We need to find the confidence interval for the SLEEP variable. To do this, we need to find the mean and standard deviation with the Week 1 spreadsheet. Then we can the Week 5 spreadsheet to find the confidence interval.

First, find the mean and standard deviation by copying the SLEEP variable and pasting it into the Week 1 spreadsheet. Write down the mean and the sample standard deviation as well as the count. Open the Week 5 spreadsheet and type in the values needed in the green cells at the top. The confidence interval is shown in the yellow cells as the lower limit and the upper limit.

1. Give and interpret the 95% confidence interval for the hours of sleep a student gets.
2. Give and interpret the 99% confidence interval for the hours of sleep a student gets
3. Compare the 95% and 99% confidence intervals for the hours of sleep a student gets. Explain the difference between these intervals and why this difference occurs.

In the Week 2 Lab, you found the mean and the standard deviation for the HEIGHT variable for both males and females. Use those values for follow these directions to calculate the numbers again.

(From Week 2 Lab: Calculate descriptive statistics for the variable Height by Gender. Click on Insert and then Pivot Table. Click in the top box and select all the data (including labels) from Height through Gender. Also click on “new worksheet” and then OK. On the right of the new sheet, click on Height and Gender, making sure that Gender is in the Rows box and Height is in the Values box.   Click on the down arrow next to Height in the Values box and select Value Field Settings. In the pop up box, click Average then OK. Write these down. Then click on the down arrow next to Height in the Values box again and select Value Field Settings. In the pop up box, click on StdDev then OK. Write these values down.)

You will also need the number of males and the number of females in the dataset. You can either use the same pivot table created above by selecting Count in the Value Field Settings, or you can actually count in the dataset.

Then use the Week 5 spreadsheet to calculate the following confidence intervals. The male confidence interval would be one calculation in the spreadsheet and the females would be a second calculation.

1. Give and interpret the 95% confidence intervals for males and females on the HEIGHT variable. Which is wider and why?

2. Give and interpret the 99% confidence intervals for males and females on the HEIGHT variable. Which is wider and why?

3. Find the mean and standard deviation of the DRIVE variable by copying that variable into the Week 1 spreadsheet. Use the Week 4 spreadsheet to determine the percentage of data points from that data set that we would expect to be less than 40. To find the actual percentage in the dataset, sort the DRIVE variable and count how many of the data points are less than 40 out of the total 35 data points. That is the actual percentage. How does this compare with your prediction?

4. What percentage of data would you predict would be between 40 and 70 and what percentage would you predict would be more than 70 miles? Use the Week 4 spreadsheet again to find the percentage of the data set we expect to have values between 40 and 70 as well as for more than 70. Now determine the percentage of data points in the dataset that fall within this range, using same strategy as above for counting data points in the data set. How do each of these compare with your prediction and why is there a difference?

On October 1, 2016, Adria Lopez launched a computer services company called Success Systems, which provides consulting services, computer system installations, and custom program development. Adria adopts the calendar year for reporting purposes and expects to prepare the company's first set of financial statements on December 31, 2016. The company's initial chart of accounts and transactions follows. Account No. Account No. Cash 101 Common Stock 307 Accounts Receivable 106 Dividends 319 Computer Supplies 126 Computer Services Revenue 403 Prepaid Insurance 128 Wages Expense 623 Prepaid Rent 131 Advertising Expense 655 Office Equipment 163 Mileage Expense 676 Computer Equipment 167 Miscellaneous Expenses 677 Accounts Payable 201 Repairs Expense - Computer 684 Oct. 1 Adria Lopez invested $55,000 cash, a $20,000 computer system, and $8,000 of office equipment in the company in exchange for its common stock. The company paid $3,300 cash for four months' rent. (Hint: Debit Prepaid Rent for $3,300.) The company purchased $1,420 of computer supplies on credit from Harris Office Products. The company paid $2,220 cash for one year's premium on a property and liability insurance policy. (Hint Debit Prepaid Insurance for $2,220.) The company billed Easy leasing $4,800 for services performed in installing a new Web server. 8 The company paid $1,420 cash for the computer supplies purchased from Harris Office Products on October 3. 10 The company hired Lyn Addie as a part-time assistant for $125 per day, as needed. 12 The company billed Easy leasing another $1,400 for services performed. 15 The company received $4,800 cash from Easy Leasing as partial payment on its account. 17 The company paid $805 cash to repair computer equipment that was damaged when moving it. 20 The company paid $1,940 cash for advertisements published in the local newspaper. 22 The company received $1,400 cash from Easy Leasing on its account. 28 The company billed IFM Company $5,208 for services performed. 31a The Company paid $875 cash for Lyn Addie's wages for seven days' work. 31b The Company paid $3,600 cash in dividends. Nov. 1 The Company reimbursed Adria Lopez in cash for business automobile mileage allowance (Lopez logged 1,000 miles at $0.32 per mile). 2 The company received $4,633 cash from Liu Corporation for computer services performed. 5 The company purchased computer supplies for $1,125 cash from Harris Office Products. 8 The company billed Gomez Co. $5,668 for services performed. 13 The company received notification from Alex's Engineering Co. that Success Systems' bid of $3,950 for an upcoming project is accepted. 18 The company received $2,208 cash from IFM Company as partial payment of the October 28 bill. 22 The company donated $250 cash to the United Way in the company's name. The company completed work for Alex's Engineering Co. and sent it a bill for $3,950. The company sent another bill to IFM Company for the past-due amount of $3,000. 28 The company reimbursed Adria Lopez in cash for business automobile mileage (1,200 miles at $0.32 per mile). 30a The Company paid $1,750 cash for Lyn Addie's wages for 14 days' work. 30b The Company paid $2,000 cash in dividends. Required: Using Micro Soft Excel and Word: Prepare journal entries to record each of the above transactions for Success Systems. (If no entry is required for a particular transaction, select "No journal entry required” in the first account field.) Post the journal entries to ledger accounts. (Add additional ledger accounts when necessary.) Prepare a trial balance as of the end of November. (Trial Balance total $ 108,659) (Be sure to show formulas in your worksheets.) This question has been posted but the answer is wrong please review and help thanks I found the mistake in the answer the 11/2 transaction shoud be cash debit revenue credit your welcome!

If you have a chance please answer as many as possible, thank you and I really appreciate your help experts!

Question 16 2 pts

In a hypothesis test, the claim is μ≤28 while the sample of 29 has a mean of 41 and a standard deviation of 5.9. In this hypothesis test, would a z test statistic be used or a t test statistic and why?

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Question 17 2 pts

A university claims that the mean time professors are in their offices for students is at least 6.5 hours each week. A random sample of eight professors finds that the mean time in their offices is 6.2 hours each week. With a population standard deviation of 0.49 hours, can the university’s claim be supported at α=0.05?

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Question 18 2 pts

A credit reporting agency claims that the mean credit card debt in a town is greater than $3500. A random sample of the credit card debt of 20 residents in that town has a mean credit card debt of $3619 and a standard deviation of $391. At α=0.10, can the credit agency’s claim be supported?

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Question 19 2 pts

A car company claims that its cars achieve an average gas mileage of at least 26 miles per gallon. A random sample of eight cars from this company have an average gas mileage of 25.6 miles per gallon and a standard deviation of 1 mile per gallon. At α=0.06, can the company’s claim be supported?

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Question 20 2 pts

A researcher wants to determine if extra homework problems help 8^th
grade students learn algebra. One 8^th grade class has extra homework problems and another 8^th grade class does not. After 2 weeks, the both classes take an algebra test and the results of the two groups are compared. To be a valid matched pair test, what should the researcher consider in creating the two groups?

Write in java

The submission utility will test your code against a different input than the sample given.

When you're finished, upload all of your .java files to Blackboard.

Grading:

Each problem will be graded as follows:

0 pts: no submission

1 pts: submitted, but didn't compile

2 pts: compiled, but didn't produce the right output

5 pts: compiled and produced the right output

Problem 1: "Letter index"

Write a program that inputs a word and an unknown number of indices and prints the letters of the word corresponding to those indices. If the index is greater than the length of the word, you should break from your loop

Sample input:

apple 0 3 20

Sample output:

a

l

Problem 2: "Matching letters"

Write a program that compares two words to see if any of their letters appear at the same index. Assume the words are of equal length and both in lower case. For example, in the sample below, a and e appear in both words at the same index.

Sample input:

apple andre

Sample output

a

e

Problem 3: "Word count"

You are given a series of lowercase words separated by spaces and ending with a . , all one on line. You are also given, on the first line, a word to look up. You should print out how many times that word occured in the first line.

Sample input:

is

computer science is no more about computers than astronomy is about telescopes .

Sample output:

2

Problem 4: "Treasure Chest"

The input to your program is a drawing of a bucket of jewels. Diamonds are represented as @, gold coins as $, rubies as *.   Your program should output the total value in the bucket, assuming diamonds go for $1000, gold coins for $500, and rubies for $300. Note that the bucket may be wider or higher than the bucket in the example below.

Sample input:

|@* @ |

| *@@*|

|* $* |

|$$$* |

| *$@*|

-------

Sample output:

$9900

Problem 5: “Speed Camera”

Speed cameras are devices that monitor traffic and automatically issue tickets to cars going above the speed limit.   They work by comparing two pictures of a car at a known time interval. If the car has traveled more than a set distance in that time, the car is given a citation.

The input are two text representations of a traffic picture with a car labeled as letters “c” (the car is moving upwards. These two pictures are shot exactly 1 second apart. Each row is 1/50 of a mile. The car is fined $10 for each mile per hour over 30 mph, rounded down to the nearest mph. Print the fine amount.

Sample input:

|.|

|.|

|.|

|.|

|c|

---

|.|

|c|

|.|

|.|

|.|

Sample output:

$1860

Problem 6. Distance from the science building

According to Google Maps, the DMF science building is at GPS coordinate 41.985 latitude, -70.966 longitude. Write a program that will read somebody’s GPS coordinate and tell whether that coordinate is within one-and-a-half miles of the science building or not.

Sample input:

-70.994

41.982

Sample output:

yes

At our position, 1 1/2 miles is about .030 degrees longitude, but about .022 degrees latitude. That means that you should calculate it as an ellipse, with the east and west going from -70.936 to -70.996, and the north and south going from 41.963 to 42.007.

Hint: Use the built in Ellipse2D.Double class. Construct a Ellipse2D.Double object using the coordinates given, and then use its "contains" method.

Problem 7: "Palindrome Numbers"

A palindrome is a word that reads the same forwards and backwards, such as, for example, "racecar", "dad", and "I". A palindrome number is the same idea, but applied to digits of a number. For example 1, 121, 95159 would be considered palindrome numbers.

The input to your program are two integers start and end. The output: all of the palindrome numbers between start and end (inclusive), each on a new line.

Sample input:

8 37

Sample output:

8

9

11

22

33

Hints:

1. Start by writing and testing a function that takes a number and returns true/false if the number is a palindrome. Then call that function in a for loop.

2. To see if a number is a palindrome, try turning it into a string. Then use charAt to compare the first and last digits, and so on.

Can someone just answer 8 A B C D and E please!!!

Regression Analysis (Excel 2010 & 2007)

1.         Open a new Excel worksheet (which will be saved as REGRESSION.xlsx).  In cell A1 type your name.  In cell A2 type the course and section number (i.e. ECON225-01).  In cell A3 type the date.  Skip cell A4.  In cell A5 type “Assignment: Regression Analysis”.  In cell A6 type “File: REGRESSION.xlsx”.

2.         Type X in cell B8 and type Yin cell C8.  Type Miles in cell B9 and type Minutes  in cell C9.

In cells B10 through B18 enter the following values:

11, 10, 15, 7, 3, 6, 9, 12, 5

                        In cells C10 through C18, enter the following data values:  

                        28, 27, 35, 15, 8, 14, 20, 29, 13  

            Center format cells B8 through C18 for a more professional appearance.

3.         Click on the Datatab in the toolbar, then select Data Analysis. Next, select   Regressionfrom the Analysis Tools and click on OK.  In the Regression dialog boxes type C10:C18in the Input Y Range dialog box, then type B10:B18in the Input X Range dialog box.  Under Output Options select Output Range and type A20:I40in the output range dialog box.  Click onOK. A Summary Output table will appear.

4.         Select cell D27 and type Forecast for Y when X = 13:  Next select cell G27, then click on the Formulas tabin the toolbar, then select More Functions. Under the Function category select Statistical.  Under the Function name select  FORECAST.  In the dialog boxes type 13in the X dialog box, type C10:C18in the Known Y’s dialog box, and type B10:B18in the Known X’s dialog box.  Click on OK. The forecasted value for Y when X=13 will appear in cell G27.

5.         Return to the Home tab in the toolbar.  Select the columns of X and Y data values from B10 through C18(do not select their headings).  Next, click on the Insert tabin the toolbar, under Charts select Scatter, then select the first choice of a scatter diagram graph.    Resize and reposition the scatter diagram to the location of cell E9 for the top left corner of the diagram, and cell I 22 for the bottom right corner of the diagram.  (This will allow everything to fit on one printed page.) Delete the “Series 1” label box. You can label the axes with the variable names (Miles and Minutes) by clicking on the outside corner of the graph, then select Axis Titles in the toolbar. Label both the X and Y axes of the graph with their appropriate variable names.

            (Instructions continue on the next page.)

6.         Next, click any place inside of the scatter diagram. Under the Analysis options, click on Trendline,thenselectLinear Trendline. Click on OK. A trend line will be added to the scatter diagram.  Do a Print Preview to make sure that your graph fits onto the printed page.

7.         Save your worksheet on a disk as REGRESSION.xlsx and print-out the worksheet to submit to the instructor.  

8.         In addition to submitting a print-out of the worksheet(s), also submit typed answers to the following questions, referencing the data in your print-out and your textbook or Notes:

(a)        What is the regression equation for this data set? (Write the printed “a” and “b” values into the equation.  Hint: Under the Coefficient column the value for the Intercept is the value for “a” and the X Variable value is the value for “b”.)

(b)       Interpret the printed value for “a” relative to its definition, the X and Y variable names, and its value.  

(c)        Interpret the printed value for “b” relative to its definition, the X and Y variable names, and its value.

(d)       Interpret the printed value for “r” relative to its definition, the X and Y variable names, and its value.  (**Hint: Under the Regression Statistics section the Multiple R value is the correlation coefficient and the R Square value is the Coefficient of Determination.  The printed table value for “r” does not always indicate direction (+ or -), therefore, check that the sign for your “r” value agrees with the sign for your “b” value.)  

(e)        Interpret the printed value for “r²” relative to its definition, the X and Y variable names, and its value.  

Write a paragraph (4 - 6 sentences) that summarizes the information that you have learned about Television.  This summary should be in your own words, do not directly quote the source.

Write a thesis statement based on the information written in your summary.  Be sure to create a thesis statement that is clear, specific, and thought-provoking. Create a thesis statement that argues a controversial position.

READ THIS ARTICLE:

Television is one of the most significant communications inventions. Television has fundamentally changed the political process, our use of leisure, as well as social relations among family and friends. Television was not developed by any single individual or even a group of people working together. Scientists and visionaries imagined a device that would capture images with sound and transmit them into homes since the 1880s. The word television was first used at the 1900 Exhibition in Paris. Scottish inventor John Logie Baird (1888–1946) was the first person to provide a television transmission in October 1925, and he subsequently demonstrated it to the British public on January 26, 1926. On December 25, 1926, Kenjiro Takayanagi (1899–1990) displayed the first image in Japan. The technology improved slowly with athletes participating in the 1936 Olympic games in Berlin able to see some poor quality images of the games. In 1936 France and Page 319 | Top of Article Germany began television programming. In Great Britain King George VI’s coronation from Hyde Park Corner on May 12, 1937, was the first broadcast of its kind, and the first U.S. election reported on television was on November 8, 1941, where news of Franklin Delano Roosevelt’s victory was transmitted to an estimated 7,500 sets. The development of television was halted during the Second World War in Europe and North America where manufacturers directed their attentions to munitions. Regular television service reached ninety-six countries by 1973. Many of the things we associate with modern television technology were patented or devised in television’s infancy. In 1928 Vladimir Zworyking (1889–1982) owned the first U.S. patent for an all-electronic color television; however, the development did not come to fruition for another twenty-five years. During the 1939 World’s Fair in New York, television could not only receive audio and video images, but it was also designed to record those images, foreshadowing video recording devices (VCRs). And Baird later patented a 600-line electronic high definition color system in Britain in 1945. TELEVISION’S GOLDEN AGE The golden age of television is associated with the years 1949 to 1960 when American television viewing consisted of a variety of entertainment programming. The burgeoning prosperity and optimism of post-World War II influenced the spread of television. As more people were able to purchase televisions the demand for content grew. Early television programs offered revamped radio programs. There was some news and information programming, but those tended to be of short duration. A similar golden age is associated with British television. Early programs were reworked vaudeville acts and radio shows. Later situational comedies such as I Love Lucy and The Honeymooners would create new talent and genres. The shared experience of watching key television programming provided an avenue for discussion and next-day water cooler conversation. As television matured so did the content, with programs such as All in the Family offering political and social commentary on issues ranging from race relations to the Vietnam War. Television’s depiction of the family changed through time as well. While initial programming presented unified traditional families with bread-winning fathers and stay-at-home mothers, later programs depicted the breakdown of the traditional family dealing in both fiction and nonfiction with divorce, remarriage, blended families, and later, with same-sex unions. Not only did television provide scripted programming, but it also broadcasted major sporting events. The first televised hockey game between the Montreal Canadiens losing six-to-two to the New York Rangers in Madison Square Gardens was seen on February 25, 1940. Television is also closely associated with the increasing popularity of the Olympic games, soccer, American football, and baseball. With technological improvements, viewing time increased as well as television’s influence on the public and politics. In 1947 there were only 60,000 American homes with television sets; by 1950 this figure grew to 12.5 million. Televisions are now found in nearly every home in the United States and Europe. In the developing world, the allure of television is so great that some want television before other communications devices such as telephones. The hold of major networks on audiences soon dissipated with the advent of cable and specialty television programming. Rather than having a system where the networks catered to a common denominator of programming, the proliferation of specialty programs allowed people to view content that interested them specifically. Moving from analog to digital signals allowed for a so-called 500-channel universe where any specific interest could be satisfied, from golf to cooking; from sport to fashion; and from all news to pornography. As a result of these technological changes, the era of the mass audience was over. While there remain a few programs that can attain mass audiences, the market has been so fragmented that networks must compete for an ever-shrinking television audience. EFFECTS ON CHILDREN The rapid adoption of television fundamentally changed modern society. Television has been blamed for the decline in civil society, the breakdown of the family, suicide, mass murder, childhood obesity, and the trivializing of politics. Children have been the target of broadcasters since the 1950s. Initially American broadcasters provided twenty-seven hours a week of children’s television programming. By the 1990s there was twenty-four hour a day programming available to children. Children in Canada spend fourteen hours per week (Statistics Canada) watching television, while American children spend twenty-one hours per week (Roberts et al. 2005, p. 34). Some surveys suggest that British children have the highest rate of television viewing in the world. There are several concerns associated with television and children’s viewing patterns. Many researchers have noted the link between the advent of television and increasing obesity and other weight-related illnesses. The time spent watching television is time not spent playing outdoors or in other physically challenging activities. High television viewership of violence is linked to an increase in violent children. Prolonged exposure to violent Page 320 | Top of Article television programming has shown that children can become more aggressive, become desensitized to violence, become accepting of violence as a means to solve problems, imitate violence viewed on television, and identify with either victims or victimizers. Despite the negatives associated with television, it remains a powerful tool in shaping and educating children. While many point to the destructive nature of television, there are others who acknowledge television’s positive impact. Researchers and programmers have developed content that has positively influenced children. Early studies on the PBS program Sesame Street found that children who viewed the program were better readers in grade one than students who had not watched the program. Programs were developed not only to help with literacy, but with other subjects as well as socialization, problem solving, and civic culture. Notwithstanding the positive effects of children and television viewing, high television viewing has been associated with a decline in civic culture. As people have retreated to their homes to watch television, they have been less inclined to participate in politics either by voting or by joining political parties. In addition television viewing means that people are not interacting as much with friends or neighbors. What is more, television viewing also has been associated with an overall decline in group participation as well as volunteerism. ADVERTISING AND OWNERSHIP The issue of ownership of content and transmission was debated from television’s onset. In 1927 the U.S. Radio Act declared public ownership of the airways. They argued that the airwaves should “serve the PICN—public interest, convenience, and necessity.” Because of this understanding of the public owning the airwaves, it set the stage for regulatory bodies around the world licensing stations according to content regulations. Taking the issue of public interest one step further, the British government founded the British Broadcasting Corporation (BBC) in 1927. Other countries followed establishing their own public broadcasting systems. The United States lagged behind other nations by adopting a Public Broadcasting Service (PBS) in 1968. With the increasing adoption of television, many countries found the need to create new regulatory agencies. In the United States, the U.S. Federal Communications Commission (FCC) was created as an act of Congress on June 19, 1934. The most successful television enterprises are closely associated with advertising. From the outset the way in which television content was funded was through the pursuit of advertising dollars. As a result it has often been said that television does not bring content to audiences, but instead it brings audiences to advertisers. The propaganda model of the media, coined by Edward Herman and Noam Chomsky in their 1988 publication Manufacturing Consent: The Political Economy of the Mass Media, argues that the media uphold the dominant ideology in America. The five pillars of the model focus on ownership, advertising, sourcing, flak, and anticommunism. This model has been linked to other western media systems, but is most fitting in the United States where the power of the media rests with the owners. Television’s hold on the public imagination stems in part because of its ease of transmission. No one needs any special skill to receive the messages. All that is required is a television that can pick up a signal. More important, television influences our view of the world precisely because images are transmitted into people’s homes. Since its inception, television transmissions have had the power to change our perceptions of world events. Starting with the Vietnam War and continuing to a myriad of events from the arms race to Tiananmen Square, and from the Civil Rights movement to the war in Iraq, television has become synonymous with the phrase “the whole world is watching.”

The following data represent the level of health and the level of education for a random sample of 1504 residents. Complete parts​ (a) and​ (b) below. Education Excellent Good Fair Poor Not a H.S. graduate 89 151 52 112 H.S. graduate 86 101 53 100 Some college 81 132 66 108 Bachelor Degree or higher 58 147 60 108 ​(a) Does the sample evidence suggest that level of education and health are independent at the alphaequals0.05 level of​ significance? Conduct a​ P-value hypothesis test. State the hypotheses. Choose the correct answer below. A. Upper H 0​: Level of education and health are independent. Upper H 1​: Level of education and health are dependent. B. Upper H 0​: p1equalsp2equalsp3 Upper H 1​: At least one of the proportions are not equal. C. Upper H 0​: mu1equalsE1 and mu2equalsE2 and mu3equalsE3 and mu4equalsE4 Upper H 1​: At least one mean is different from what is expected. Calculate the test statistic. chi Subscript 0 Superscript 2equals nothing ​(Round to three decimal places as​ needed.) The​ P-value is nothing. ​(Round to three decimal places as​ needed.) Make the proper conclusion. Choose the correct answer below. A. Reject Upper H 0. There is sufficient evidence that level of education and health are associated. B. Reject Upper H 0. There is not sufficient evidence that level of education and health are associated. C. Fail to reject Upper H 0. There is sufficient evidence that level of education and health are associated. D. Fail to reject Upper H 0. There is not sufficient evidence that level of education and health are associated. ​(b) Construct a conditional distribution of health by level of education and draw a bar graph. Education Excellent Good Fair Poor Not a H.S. graduate nothing nothing nothing nothing H.S. graduate nothing nothing nothing nothing Some college nothing nothing nothing nothing Bachelor Degree or higher nothing nothing nothing nothing ​(Round to three decimal places as​ needed.) Choose the correct bar graph below. A. A side-by-side bar graph has a vertical axis labeled from 0 to 0.5 in increments of 0.1 and a horizontal axis labeled with four education levels. The bar graph contains four vertical bars above each horizontal axis label; the four bars in each set are labeled as follows from left to right: E, G, F, P. From left to right, the vertical bars in each set have approximate heights as follows, where for each set of four bars the horizontal axis label is listed first and individual bar heights are listed from left to right: "Not H S Grad," 0.28, 0.13, 0.37, 0.22; "H S Grad," 0.29, 0.16, 0.25, 0.3; "Some College," 0.34, 0.17, 0.28, 0.21; "Bachelor," 0.16, 0.29, 0.16, 0.39. 0 0.5 E E E E G G G G F F F F P P P P Not HS Grad HS Grad Some College Bachelor B. A side-by-side bar graph has a vertical axis labeled from 0 to 0.5 in increments of 0.1 and a horizontal axis labeled with four education levels. The bar graph contains four vertical bars above each horizontal axis label; the four bars in each set are labeled as follows from left to right: E, G, F, P. From left to right, the vertical bars in each set have approximate heights as follows, where for each set of four bars the horizontal axis label is listed first and individual bar heights are listed from left to right: "Not H S Grad," 0.22, 0.37, 0.13, 0.28; "H S Grad," 0.25, 0.3, 0.16, 0.29; "Some College," 0.21, 0.34, 0.17, 0.28; "Bachelor," 0.16, 0.39, 0.16, 0.29. 0 0.5 E E E E G G G G F F F F P P P P Not HS Grad HS Grad Some College Bachelor Click to select your answer(s).

Education   Excellent   Good   Fair   Poor
Not a H.S. graduate   89   151   52   112
H.S. graduate   86   101   53   100
Some college   81   132   66   108
Bachelor Degree or higher   58   147   60   108

The following data represent the level of health and the level of education for a random sample of 1504 residents. Complete parts​ (a) and​ (b) below. Education Excellent Good Fair Poor Not a H.S. graduate 89 151 52 112 H.S. graduate 86 101 53 100 Some college 81 132 66 108 Bachelor Degree or higher 58 147 60 108 ​(a) Does the sample evidence suggest that level of education and health are independent at the alphaequals0.05 level of​ significance? Conduct a​ P-value hypothesis test. State the hypotheses. Choose the correct answer below. A. Upper H 0​: Level of education and health are independent. Upper H 1​: Level of education and health are dependent. B. Upper H 0​: p1equalsp2equalsp3 Upper H 1​: At least one of the proportions are not equal. C. Upper H 0​: mu1equalsE1 and mu2equalsE2 and mu3equalsE3 and mu4equalsE4 Upper H 1​: At least one mean is different from what is expected. Calculate the test statistic. chi Subscript 0 Superscript 2equals nothing ​(Round to three decimal places as​ needed.) The​ P-value is nothing. ​(Round to three decimal places as​ needed.) Make the proper conclusion. Choose the correct answer below. A. Reject Upper H 0. There is sufficient evidence that level of education and health are associated. B. Reject Upper H 0. There is not sufficient evidence that level of education and health are associated. C. Fail to reject Upper H 0. There is sufficient evidence that level of education and health are associated. D. Fail to reject Upper H 0. There is not sufficient evidence that level of education and health are associated. ​(b) Construct a conditional distribution of health by level of education and draw a bar graph. Education Excellent Good Fair Poor Not a H.S. graduate nothing nothing nothing nothing H.S. graduate nothing nothing nothing nothing Some college nothing nothing nothing nothing Bachelor Degree or higher nothing nothing nothing nothing ​(Round to three decimal places as​ needed.) Choose the correct bar graph below. A. A side-by-side bar graph has a vertical axis labeled from 0 to 0.5 in increments of 0.1 and a horizontal axis labeled with four education levels. The bar graph contains four vertical bars above each horizontal axis label; the four bars in each set are labeled as follows from left to right: E, G, F, P. From left to right, the vertical bars in each set have approximate heights as follows, where for each set of four bars the horizontal axis label is listed first and individual bar heights are listed from left to right: "Not H S Grad," 0.28, 0.13, 0.37, 0.22; "H S Grad," 0.29, 0.16, 0.25, 0.3; "Some College," 0.34, 0.17, 0.28, 0.21; "Bachelor," 0.16, 0.29, 0.16, 0.39. 0 0.5 E E E E G G G G F F F F P P P P Not HS Grad HS Grad Some College Bachelor B. A side-by-side bar graph has a vertical axis labeled from 0 to 0.5 in increments of 0.1 and a horizontal axis labeled with four education levels. The bar graph contains four vertical bars above each horizontal axis label; the four bars in each set are labeled as follows from left to right: E, G, F, P. From left to right, the vertical bars in each set have approximate heights as follows, where for each set of four bars the horizontal axis label is listed first and individual bar heights are listed from left to right: "Not H S Grad," 0.22, 0.37, 0.13, 0.28; "H S Grad," 0.25, 0.3, 0.16, 0.29; "Some College," 0.21, 0.34, 0.17, 0.28; "Bachelor," 0.16, 0.39, 0.16, 0.29. 0 0.5 E E E E G G G G F F F F P P P P Not HS Grad HS Grad Some College Bachelor Click to select your answer(s).

Education   Excellent   Good   Fair   Poor
Not a H.S. graduate   89   151   52   112
H.S. graduate   86   101   53   100
Some college   81   132   66   108
Bachelor Degree or higher   58   147   60   108