Country | Number of sexual predators identified |
---|---|

Albania | 2 |

Algeria | 1 |

Argentina | 1 |

Australia | 46 |

Austria | 3 |

Bahrain | 3 |

Bangladesh | 4 |

Belgium | 13 |

Belize | 1 |

Bosnia-Herzegovenia | 2 |

Brazil | 2 |

Britain | 110 |

Canada | 54 |

China | 3 |

Costa Rica | 1 |

Croatia | 2 |

Cuba | 1 |

Cyprus | 1 |

Germany | 44 |

India | 103 |

Ireland | 3 |

New Zealand | 4 |

South Africa | 3 |

United States | 254 |

Terre des Hommes Netherlands raised the alarm about a largely unknown, but quickly spreading new form of child exploitation that has got tens of thousands victims involved in the Philippines alone: Webcam Child Sex Tourism (WCST). In less than two and a half months Terre des Hommes researchers were able to identify over 1,000 adults who were willing to pay children in developing countries to perform sexual acts in front of the webcam. With the help of a virtual 10 year old Philippine girl the researchers identified adults from more than 65 countries. The number of predators by country is listed above. Use the number of predators, the second column, to answer the following questions.

- __________ Calculate the sample size n.
- __________ Calculate the minimum (quartile 0).
- __________ Calculate the first quartile (Q1).
- __________ Calculate the median (quartile 2).
- __________ Calculate the third quartile (Q3).
- __________ Calculate the maximum (quartile 4).
- __________ Calculate the Inter-Quartile Range (IQR).
- Sketch the box plot for the data.

- __________ Calculate the range.
- __________ If the data is divided into
**three**classes,

what is the width of a single class? -
Determine the frequency and calculate the relative

frequency for the data using three classes.

Record your results in the table provided.

Class upper limits Frequency F Rel. Freq. **Sums:** -
Sketch a
**frequency**histogram for the data, labeling your horizontal axis and vertical axis as appropriate.

- __________ What is the shape of the histogram?
- __________ Calculate the mode.
- __________ Calculate the mean.
- __________ Calculate the sample standard deviation sx.
- __________ Calculate the standard error SE of the sample mean.
- __________ Calculate the degrees of freedom.
- __________ Calculate t-critical for a 95% confidence level.
- __________ Calculate the margin of error E of the sample mean.
- Calculate the 95% confidence interval for the population mean μ

p(__________ < μ < __________) = 0.95

On 04 November 2013 Terre des Hommes released the video Stop webcam child sex tourism! under the username Sweetie. The video went viral for just over a hundred hours until super typhoon Haiyan hit the Philippines and knocked Sweetie out of the news cycle.

Hours on line Number of views (thousands) 0 0 14 307 62 1338 83 2114 106 2611 130 2846

- _________ For the paired data, calculate the sample size n (the number of data pairs).
- ______________ Calculate the slope of the linear regression for the data.
- ______________ Calculate the y-intercept of the linear regression for the data.
- ______________ Is the relation positive, negative, or neutral?
- ______________ Calculate the correlation coefficient r for the data.
- ______________ Is the correlation none, weak/low, moderate, strong/high, or perfect?
- ______________ Determine the coefficient of determination.
- ______________ Use the slope and intercept to predict the number of views at 24 hours on line.
- ______________ Use the slope and intercept to predict the hours on line at which the number of views was 750.

*Sapou in Polle, Epin on Paata*

Webcam Child Sex Tourism (WCST)flourishes in the Philippines in part because of a combination of poverty and broadband Internet access. One way to protect children is through education. Education is perhaps the most important long term solution to reducing poverty and the conditions that allow WCST to flourish. While the Philippines is far away, the possibility of the exploitation of youth exists even here in the FSM. In an ongoing case in Guam, young Chuukese women, including some underage women, were taken from Chuuk by human traffickers and forced into prostitution at the Blue House in Guam. Fear and a lack of knowing what to do - a lack of education - kept these young women from seeking help.

One of the weaknesses that has been identified in the education system in Chuuk is teacher attendance. Teachers are often absent from the their classes. The following table provides data for elementary schools in Faichuuk. The data comes from the Chuuk State School Facility Repair and Construction Master Plan, Version 1.0, 31 May 2012 available from the
PITI-VITI web site. The region, name of the island, and name of the school, are in the first column. The second column is the Chuuk
State Junior High Entrance Test (JHET) percent correct. The third column is the percentage of the total possible days of attendance for which teachers attended school. Perfect attendance would be 100%. There are a number of problems with using this data, not the least of which is the percentage nature of the data. There is not, however, a lot of publicly available data for the schools in Chuuk state. **Provide numeric support for answers to the following questions.**

- Are any schools unusually low or high on the JHET test?
- Over all elementary schools in Faichuuk, is the JHET percent correct indicating good, well functioning schools?
- Are there any schools with unusually low or high teacher attendance rates?
- Is there a relationship between the JHET % correct and the teacher attendance rate?
- What is the strength of that relationship?

Region Island School | JHET % Correct | Teacher attendance rate |
---|---|---|

Faichuuk Eot Eot | 0.25 | 0.67 |

Faichuuk Fanapanges Fanapanges | 0.27 | 0.82 |

Faichuuk Patta Epin | 0.35 | 0.79 |

Faichuuk Patta Nukaf | 0.28 | 0.64 |

Faichuuk Polle Manaio | 0.25 | 0.81 |

Faichuuk Polle Sapou | 0.39 | 0.79 |

Faichuuk Romanum Romanum | 0.46 | 0.94 |

Faichuuk Tolensom Central Wonip | 0.64 | 0.98 |

Faichuuk Tolensom East Wonip | 0.29 | 0.89 |

Faichuuk Tolensom Fason | 0.29 | 0.87 |

Faichuuk Tolensom Munien | 0.43 | 0.80 |

Faichuuk Tolensom Wichukuno | 0.24 | 0.97 |

Faichuuk Udot Udot | 0.47 | 0.92 |

Mortlocks Lower Lekinioch | 0.33 | 0.81 |

Mortlocks Lower Oneop | 0.38 | 0.70 |

Mortlocks Lower Satowan | 0.36 | 0.91 |

Mortlocks Lower Ta | 0.34 | 0.72 |

Mortlocks Mid Kuttu | 0.36 | 0.81 |

Mortlocks Mid Moch | 0.84 | 0.95 |

Mortlocks Mid Namoluk | 0.51 | 0.91 |

Mortlocks Upper Losap | 0.25 | 0.46 |

Mortlocks Upper Nema | 0.41 | 0.85 |

Mortlocks Upper Piisemwar | 0.36 | 0.69 |

Northern Noumeneas Fonoton Fonoton | 0.27 | 0.94 |

Northern Noumeneas Weno Iras Demo | 0.31 | 0.92 |

Northern Noumeneas Weno Mechitiw | 0.57 | 0.91 |

Northern Noumeneas Weno Mwan | 0.49 | 0.97 |

Northern Noumeneas Weno Neauo | 0.52 | 0.91 |

Northern Noumeneas Weno P&P | 0.31 | 0.71 |

Northern Noumeneas Weno PiisPaneu | 0.44 | 0.98 |

Northern Noumeneas Weno Sapuk | 0.45 | 0.98 |

Northwest Halls Fananu | 0.25 | 0.72 |

Northwest Halls Murilo | 0.49 | 0.87 |

Northwest Halls Nomwin | 0.41 | 0.75 |

Northwest Halls Ruo | 0.38 | 0.86 |

Northwest Numon Pattiw Houk | 0.26 | 0.70 |

Northwest Numon Pattiw Pollap | 0.44 | 0.59 |

Northwest Numon Pattiw Polowat | 0.34 | 0.86 |

Northwest Numon Pattiw Tamatam | 0.78 | 0.94 |

Northwest Numon Weito Makur | 0.31 | 0.94 |

Northwest Numon Weito Onoun | 0.27 | 0.70 |

Northwest Numon Weito Piherarh | 0.43 | 0.93 |

Northwest Numon Weito Unanu | 0.27 | 0.88 |

Southen Noumeneas Fefen Inaka | 0.29 | 0.91 |

Southen Noumeneas Fefen Kukku | 0.26 | 0.99 |

Southen Noumeneas Fefen Messa | 0.41 | 0.96 |

Southen Noumeneas Fefen Sapore | 0.38 | 0.97 |

Southen Noumeneas Fefen UFO | 0.36 | 0.98 |

Southen Noumeneas Fefen West Fefen | 0.28 | 0.79 |

Southen Noumeneas Parem Parem | 0.39 | 0.74 |

Southen Noumeneas Siis Siis | 0.27 | 1.00 |

Southen Noumeneas Tonoas Kuchuwa | 0.35 | 0.82 |

Southen Noumeneas Tonoas Nechap | 0.30 | 0.95 |

Southen Noumeneas Tonoas Nukuno | 0.47 | 0.82 |

Southen Noumeneas Tonoas Sino Mel | 0.36 | 0.94 |

Southen Noumeneas Uman Kuchu | 0.28 | 0.87 |

Southen Noumeneas Uman Panitiw | 0.41 | 0.98 |

Southen Noumeneas Uman Sapota SN | 0.38 | 0.75 |