Monthly Profit of an Auto Repair Shop Month Jan-14 Feb-14 Mar-14 Apr-14 May-14 Jun-14 Jul-14 Aug-14 Sep-14 Profit ($) 17,12317,123 17,27317,273 16,05516,055 18,13818,138 19,76319,763 17,31017,310 19,13119,131 18,57818,578 20,37320,373   Step 1 of 4 :   Determine the three-period moving average for the next time period. If necessary, round your answer to one decimal place.

58, 66, 97, 89, 86, 72, 81, 70, 92, 95, 73, 79, 88, 68, 90, 82, 78, 93, 89, 71, 72, 84, 98, 59, 86, 90, 74, 82, 58, 64. Interval 50 - 59 Frequency Relative Frequency Cumulative Frequency Cumulative Relative Frequency

Walmart Revenue The annual revenue of Walmart is given in the table below (source ). Walmart Annual Revenue (Billions of US dollars) 559.151 Year 2021 2020 2019 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 523.964 514.405 500.343 485.873 482.130 485.651 476.294 468.651 446.509 421.849 408.085 404.254 377.023 348.368 312.101 284.310 Apply linear regression to the data in the table to find a model y = mx + b, where y is Walmart's annual revenue in billions of US dollars, and a is the number of years since 2000. Use the model y = mx + b with m rounded to the nearest tenth and 6 rounded to the nearest

Earnings class Frequency Relative Frequency Cumulative Relative Frequency $0 ≤ Bill < $60 99 0.5294 0.5294 $60 ≤ Bill < $120 79 0.4225 0.9519 $120 ≤ Bill < $180 3 0.0160 0.9679 $180 ≤ Bill < $240 2 0.0107 0.9786 $240 ≤ Bill < $300 0 0.0000 0.9786 $300 ≤ Bill 4 0.0214 1 Construct a relative frequency histogram and an ogive for the bill data of male students, using the frequency distribution table

Floor Space (sq. ft.) 6,060 5,230 4,280 5,580 5,670 5,020 5,410 4,990 4,220 4,168 4,870 5,470 weekly Sales (dollars) 16,380 14,400 13,820 18,230 14,200 12,800 15,840 16,610 13,610 10,050 15,320 13,270 A Click here for the Excel Data File (a) Using the table above, select the most appropriate scatter plot from the given cholces. Scatter Plot A Scatter Plot B Scatter Plot C Floor Space and We ekly Sales Floor Space and Weekly Sales Floor Space and We ekly Sales 20,000 18,000 16,000 14.000 12.000 10,000 8,000 6,000 4,000 2,000 20,000 18,000 16,000 14,000 12.000 10,000 8,000 6,000 4.000 2,000 20,000 18,000 16,000 14,000 12,000 10,000 8,000 6,000 4,000 2,000 1,000 2,000 3,000 4,000 5,000 6,000 7,000 1,000 2,000 3,000 4,000 5,000 6,000 7,000 1,000 2,000 3,000 4,000 5,000 6,000 7,000 FLOOR SPACE FLOOR SPACE FLOOR SPACE O Scatter Plot A O Scatter Plot B O Scatter Plot C (b) Define the relationship between X and Y. (You may select more than one answer. Click the box with a check mark for the…

You want to assess the differences in frequency counts for four different groups. You know there are 150 people total. Without any additional information about how the data is distributed, what would you use for the "expected frequency" in each group?     a.1/4 b.37.5 c.25 d..375

Lib x A ALEKS - Chantel Willia i X G rounding calculator O Round 3.400286944 tx £ Slope Calculator - (23,722 unread) - cha X b Home | bart /Isl.exe/10 u-lgNslkasNW8D8A9PVVfHVpam8LJfqFyOvYqF2RGUkxKmoBaXOYhy-WYCE-BbpvMLI7sejOT9oPIkUehmGOQpajA6nmjTfAiAuiTgdlAJtEi2BGBibo?1oBw7QYjlbavbSP O REVIEW OF ESSENTIAL SKILLS AND PROBLEM SOLVING Computing unit prices to find dhe better bury 0/5 Amanda paid $11.88 for a 2.38-pound bag of shrimp at one store. The following week, she paid $26.47 for a 5.08-pound bag at another store. Find the unit price for each bag. Then state which bag is the better buy based on the unit price. Round your answers to the nearest cent. Unit price for the 2.38-pound bag: $per pound Unit price for the 5.08-pound bag: Sper pound The better buy: O The 2.38-pound bag O The 5.08-pound bag O Neither (They have the same unit price)

Ages Frequency 42-45 2 46-49 7 50-53 8 54-57 16 58-61 5 62-65 4 66-69 2 identify any possible outliers

Mid-career Salary (in thousands of dollars) (y) Yearly Tuition (in thousands of dollars) (x) 21 87 21 72 33 92 19 83 17 68 19 98 13 57 31 102 14 58 26 101 11 86 15 45 x: 21, 21, 33, 19, 17, 19, 13, 31, 14, 26, 11, 15 y: 87, 72, 92, 83, 68, 98, 57, 102, 58, 101, 86, 45 1. Find the best fit line for the data. y = + 2. Graph the scatter plot of the data together with the best fit line using R. (This portion of the problem is not graded.) 3. Predict the mid-career salary of a student attending a college with an annual tuition of $33 thousand. %24 thousand

End of month S&P 500 End of month S&P 500 End of month S&P 500 End of month S&P 500 September-77 96.53 April-80 106.29 November-82 138.53 July-85 191.85 October-77 92.34 May-80 111.24 December-82 140.64 August-85 190.92 November-77 94.83 June-80 114.24 January-83 145.30 September-85 188.63 December-77 95.10 July-80 121.67 February-83 148.06 October-85 182.08 January-78 89.25 August-80 122.38 March-83 152.96 November-85 189.82 February-78 87.04 September-80 125.46 April-83 164.43 December-85 202.17 March-78 89.21 October-80 127.47 May-83 162.39 January-86 211.28 April-78 96.83 November-80 140.52 June-83 167.64 February-86 226.92 May-78 97.24 December-80 135.76 July-83 162.56 March-86 238.90 June-78 95.53 January-81 129.55 August-83 164.40 April-86 235.52 July-78 100.68 February-81 131.27 September-83 166.07 May-86 247.35 August-78 103.29 March-81 136.00 October-83 163.55 June-86 250.84 September-78 102.54 April-81 132.81 November-83 166.40…