ECN129 ass 2

ECN129 Kish Idoko Assignment-II

Question-1 Imports and Exports Year Exports Imports Net Imports 1981 156,781 140,560 16,221 1982 154,668 118,272 36,396 1983 163,578 130,319 33,259 1984 194,089 153,061 41,028 1985 202,901 165,816 37,085 1986 212,083 176,915 35,168 1987 218,874 186,473 32,401 1988 238,757 211,619 27,138 1989 240,888 223,832 17,056 1990 251,976 227,928 24,048 1991 256,174 233,828 22,346 1992 275,351 246,020 29,331 1993 305,074 264,453 40,621 1994 344,195 286,426 57,769 1995 374,722 303,102 71,620 1996 397,037 319,457 77,580 1997 431,304 365,456 65,848 1998 472,363 384,861 87,502 1999 523,342 415,943 107,399 2000 570,261 451,399 118,862 2001 554,899 429,373 125,526 2002 561,560 437,454 124,106 2003 552,060 456,010 96,050 2004 582,748 494,865 87,883 2005 596,037 531,188 64,849 2006 601,322 559,426 41,896 2007 607,838 591,781 16,057 2008 580,158 597,182 -17,024 2009 505,026 523,058 -18,032 2010 538,741 595,157 -56,416 2011 564,585 628,440 -63,855 2012 580,192 651,552 -71,360 2013 594,426 665,112 -70,686 2014 631,988 681,850 -49,862 2015 653,469 687,031 -33,562 2016 663,436 687,389 -23,953 2017 673,326 720,254 -46,928 2018 697,392 745,447 -48,055 2019 713,338 744,641 -31,303 Table 1.1

https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=3610022201 Question-2 Employment and Inflation Rate Year Average of Unemployement % Average of Inflation

% 1991 10.32 5.6 1992 11.19 1.5 1993 11.4 1.9 1994 10.42 0.2 1995 9.51 2.1 1996 9.61 1.6 1997 9.12 1.6 1998 8.28 1 1999 7.59 1.7 2000 6.82 2.7 2001 7.22 2.5 2002 7.67 2.3 2003 7.58 2.8 2004 7.19 1.9 2005 6.76 2.2 2006 6.47 2 2007 6.17 2.1 2008 6.29 2.4 2009 8.45 0.3 2010 8.18 1.8 2011 7.63 2.9 2012 7.4 1.5 2013 7.15 0.9 2014 7.03 1.9 2015 6.94 1.1 2016 7.03 1.4 2017 6.42 1.6 2018 5.84 2.3 2019 5.69 1.9 Table 2.1 The table above summarizes the employment and inflation rate every year since 1991. Using excel, the coefficient of correlation is -0.00332 which is approximately 0 meaning they are not correlated at all.

Questions-3 Game of Craps a. The probability of winning 5 or more games out of 10 is 1 – the probability of winning less than 5 games. Which is 0.605528 meaning there is a 60.6% chance of getting 5 or more wins. b. The expected number of wins out of 100 games is 49.2 which means one is slightly more likely to lose than to win.

Questions-4 a. The probability that only one car will arrive within the next hour when the mean is 5 is 0.03369, or 3.37%. b. The probability that more than 20 cars will arrive within 3 hours given a mean of 15 is 0.082971 or 8.3%. This is found by finding the probability of getting 20 or less cars in 3 hours and subtracting that number by 1

Question-6 (10 Points) 1 2 3 4 5 6 0 5 10 15 20 25 30 35 40 45 Informal Unemployement rates by age Columbia Brazil Egypt Age Group percentage I apologize the chart was not how I wanted it to be. In the chart the following is true: - 2 represents ages 15-24 - 3 represents ages 24-29 - 4 represents ages 30-34 - 5 represents ages 35-54 - 6 represents ages 55-64 - 7 represents ages 65+ From this chart we can draw several conclusions: 1. The three countries have a similar rate of informal employment. 2. The biggest anomaly is Egyptians under 30. This group has a noticeably higher informal employment rate compared to the others. 3. The age group 35-54 has by far the highest informal employment rates with the percentage of labor being around 40% in this age group in all the above countries. There are many reasons for informal work, looking at it through the economic context of the countries above paints a clear picture. These countries are neither poor nor rich but also face economic challenges not found in the first world. The factors I suspect influence the informal employeent rates are s labor laws that make formal employment costly for employers and a lack of jobs in the formal sector.

Economic necessity also plays a significant role; many individuals enter the informal sector because they have no other means of livelihood. https://stats.oecd.org/Index.aspx?DataSetCode=KIIBIH_B3#

Questions-8 (10 Points) The formula for the exponential distribution of x is f(x) = λe ^ −λx we can find all variables by plugging all x’s into that formula given that λ=0.25 Numbers distribution 0 0.25 2 0.151632665 4 0.09196986 6 0.05578254 8 0.033833821 10 0.02052125 15 0.005879436 20 0.001684487 Table 8.1 0 2 4 6 8 10 12 14 16 0 0.05 0.1 0.15 0.2 0.25 0.3 distribution distribution Exponential (distribution) Numbers distribution Table 8.2

Questions-9 (10 Points) a. Given the mean checkout time is 6 minutes which means λ = 1/6. The exponential distribution's cumulative distribution is given by F(x)= e ^ −λx. To find the proportion of customers that need more than 10 minutes to check out, we plug in 10 as x and 1/6 as lambda. Thus, the proportion of customers who require more than 10 minutes to check out is approximately 0.1889 or 18.89%.

https://data.oecd.org/conversion/exchange-rates.htm Works Cited

“Informal Workers by Status in Employment (Percentage of Informal Workers).” Stats.oecd.org , stats.oecd.org/Index.aspx?DataSetCode=KIIBIH_B3#. Accessed 24 Nov. 2023. OECD. “Conversion Rates - Exchange Rates - OECD Data.” TheOECD , 2012, data.oecd.org/conversion/exchange-rates.htm. ---. “Prices - Inflation (CPI) - OECD Data.” The OECD , 2023, data.oecd.org/price/inflation-cpi.htm. “STAN: OECD Structural Analysis Statistics 2020 | READ Online.” Oecd-Ilibrary.org , read.oecd- ilibrary.org/industry-and-services/stan-oecd-structural-analysis-statistics-2020_cba41dd8- en#page9. Accessed 24 Nov. 2023. Statcan.gc.ca , 2020, www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=3610022201.