628 SAFMEDS Week 2 Assignment

. Primary Data Source and Secondary Data Source ?

Raw Data:  {3.5,2.7,1.6,2.9,1.7,5.3,7.5,8.2,4.6,1.3,4.7,9.4,7.6,3.9,3.2,8.1,4.9,5.7,2.6,3.2,6.5,4.8,3.5,4.8,9.2,4.9,1.1,2,6.4,7.1}{3.5,2.7,1.6,2.9,1.7,5.3,7.5,8.2,4.6,1.3,4.7,9.4,7.6,3.9,3.2,8.1,4.9,5.7,2.6,3.2,6.5,4.8,3.5,4.8,9.2,4.9,1.1,2,6.4,7.1} The gap between the first and second class is 0.1. What number should you subtract from each lower limit and add to each upper limit to find the class boundaries? 0.12=0.12=Answer Class Lower Class Boundary  Upper Class Boundary 1.1−2.71.1−2.7 1.1−0.05=1.051.1−0.05=1.05 2.7+0.05=2.752.7+0.05=2.75 2.8−4.42.8−4.4 2.8−0.05=2.8−0.05= Answer 4.4+0.05=4.454.4+0.05=4.45 4.5−6.14.5−6.1 Answer −0.05=4.45−0.05=4.45 6.1+0.05=6.156.1+0.05=6.15 6.2−7.86.2−7.8 6.2−6.2− Answer =6.15=6.15 7.8+0.05=7.8+0.05= Answer 7.9−9.57.9−9.5 Answer Answer Answer =7.85=7.85 Answer +0.05=9.55+0.05=9.55

Month Number of Tables Produced EA 10. LO 2.3 This cost data from Hickory Furniture is for the year 2017. Factory Utility Expenses January 550 $2,063 February 710 2,663 March 650 2,438 April 470 1,823 May 512 1,920 June 625 2,344 July 805 3,019 August 750 2,813 September 675 2,531 October 525 1,969 November 875 3,281 December 685 2,569 A. Using the high-low method, express the company's utility costs as an equation where X represents number of tables produced. B. Predict the utility costs if 800 tables are produced. C. Predict the utility costs if 600 tables are produced. D. Using Excel, create a scatter graph of the cost data and explain the relationship between number of tables produced and utility expenses.

The table below contains real data for the first two decades of AIDS reporting. Year # AIDS cases diagnosed # AIDS deaths Pre–1981 91 29 1981 319 121 1982 1,170 453 1983 3,076 1,482 1984 6,240 3,466 1985 11,776 6,878 1986 19,032 11,987 1987 28,564 16,162 1988 35,447 20,868 1989 42,674 27,591 1990 48,634 31,335 1991 59,660 36,560 1992 78,530 41,055 1993 78,834 44,730 1994 71,874 49,095 1995 68,505 49,456 1996 59,347 38,510 1997 47,149 20,736 1998 38,393 19,005 1999 25,174 18,454 2000 25,522 17,347 2001 25,643 17,402 2002 26,464 16,371 Total 802,118 489,093 Graph "year" vs. "# AIDS deaths." Do not include pre-1981. Label both axes with words. Scale both axes. Calculate the following. (Round your answers to the nearest whole number. Round the correlation coefficient r to four decimal places.) (a)    a = (b)    b = (c)    r = (d)    n =

Is the scatterplot informative?

Handwritten only

The personnel files of all eight employees at the Pawnee location of Acme Carpet Cleaners Inc. revealed that during the last 6-month period they lost the following number of days due to illness: 5 5 4 4 1 2 All eight employees during the same period at the Chickpee location of Acme Carpets revealed they lost the following number of days due to illness: Range Mean 2 1 0 10 2 2 3 0 0 6 Click here for the Excel Data File Required: a. Calculate the range and mean for the Pawnee location and the Chickpee location. (Round the "Mean" to 2 decimal places.) Pawnee location O Chickpee location O Pawnee location Chickpee location b-1. Based on the data which location has fewer lost days?

The table below contains real data for the first two decades of AIDS reporting. Year # AIDS cases diagnosed # AIDS deaths Pre-1981 91 29 1981 319 121 1982 1,170 453 1983 3,076 1,482 1984 6,240 3,466 1985 11,776 6,878 1986 19,032 11,987 1987 28,564 16,162 1988 35,447 20,868 1989 42,674 27,591 1990 48,634 31,335 1991 59,660 36,560 1992 78,530 41,055 1993 78,834 44,730 1994 71,874 49,095 1995 68,505 49,456 1996 59,347 38,510 1997 47,149 20,736 1998 38,393 19,005 1999 25,174 18,454 2000 25,522 17,347 2001 25,643 17,402 2002 26,464 16,371 Total 802,118 489,093 Graph "year" versus "# AIDS cases diagnosed" (plot the scatter plot). Do not include pre-1981 data. Perform linear regression. Write the equations. (Round your answers to the nearest whole number. Round r to four decimal places.) (a) Linear Equation: 9 - (b) a = (c) b= (d) (e) n-

Laker Company reported the following January purchases and sales data for its only product. For specific identification, ending inventory consists of 180 units from the January 30 purchase, 5 units from the January 20 purchase, and 15 units from beginning inventory. Date January 1 Activities Beginning inventory 140 units Units Acquired at Cost @ $ 6.00 = Units sold at Retail $ 840 January 10 Sales 100 units @ $ 15 January 20 January 25 Purchase Sales 60 units @ $ 5.00 = 300 80 units @ $ 15 January 30 Purchase Totals 180 units @ $ 4.50 = 810 380 units $ 1,950 180 units Assume the perpetual inventory system is used. Required: 1. Complete the table to determine the cost assigned to ending inventory and cost of goods sold using specific identification. 2. Determine the cost assigned to ending inventory and to cost of goods sold using weighted average. 3. Determine the cost assigned to ending inventory and to cost of goods sold using FIFO. 4. Determine the cost assigned to ending inventory…

You may need to use the appropriate appendix table or technology to answer this question. Suppose that a recent issue of a magazine reported that the average weekly earnings for workers who have not received a high school diploma is $494. Suppose you would like to determine if the average weekly for workers who have received a high school diploma is significantly greater than average weekly earnings for workers who have not received a high school diploma. Data providing the weekly pay for a sample of 50 workers are available in the file named WeeklyHSGradPay. These data are consistent with the findings reported in the article. Weekly Pay 687.73 543.15 789.45 442.26 684.85 661.43 478.3 629.62 486.95 786.47 652.15 652.82 669.81 641.13 577.24 845.68 541.59 553.36 743.25 468.61 821.71 757.82 657.34 506.95 744.93 553.2 827.92 663.85 685.9 637.25 530.54 515.85 588.77 506.62 720.84 503.01 583.18 7,980.24 465.55 593.12 605.33 701.56 491.86 763.4 711.19 631.73 605.89 828.37 477.81…

Please help. Thank you. CSV file data is below. TSERofReturn AcmeRofReturn -1.99167 -1.03712 2.64815 3.04528 -0.58856 0.44802 -0.76395 0.60781 -0.81178 2.51735 -0.14212 1.70972 0.17677 -0.27609 0.54349 1.18672 -0.09428 0.49632 0.3681 -3.08347 0.60727 1.4182 1.3726 0.1878 -0.8915 -1.81699 1.8031 0.975 -0.26967 1.85853 2.42493 2.33005 -0.95528 -0.48742 -0.28562 -0.15591 -2.13517 -1.67924 -0.85961 1.57905 1.0856 -4.09194 -1.06689 -0.43368 0.04922 1.22281 3.2381 -0.55675 1.05371 -0.23124 -1.1785 -5.10525 1.11749 0.5909 -0.01456 1.70857 1.13344 0.93883 2.6641 0.92507 -1.33795 0.9294 -1.65683 -1.93668 -2.21489 -5.10648 -1.19445 0.47456 -0.461 0.19373 0.6551 -0.44915 1.5161 -1.11084 3.42943 2.58471 -0.3175 1.17337 -0.47695 -1.08238 -1.13067…

Use the population data in Table 1.8 to estimate the population for the year 2000. Com-pare the result with the actual 2000 population of approximately 281.4 million.

Light Conditions   Weather Daylight ​Dark, but Lighted Dark ​Dawn/Dusk Other   Normal ​14,307 5875 8151 1183 65   Rain 875 497 681 87 8   ​Snow/Sleet 219 51 156 17 2   Other 125 54 220 40 9   Unknown 810 255 548 71 133

The quality manager believes there may be a relationship between the experience level of an inspector and whether a product passes or fails inspection. Inspection records were reviewed for 628 units of a particular product, and the number of units which passed and failed inspection was determined based on three inspector experience levels. The results are shown in the following table. Experience Level Medium (2-8 years) 285 High (> 8 years) 102 26 Low (< 2 years) 153 16 Decision Pass Fail 46 a. Select the competing hypotheses to determine whether the inspector pass/fail decision depends on experience level. Ho: Inspector pass/fail decision and experience level are independent; HA: Inspector pass/fail decision and experience level are dependent. O Ho Inspector pass/fail decision and experience level are dependent; HA Inspector pass/fail decision and experience level are independent. b. Calculate the value of the test statistic. (Round the intermediate calculations to at least 4 decimal…