Problem 1 The following data recaps the number of portions of each menu item sold on Friday evening for the past five weeks: Week 1 Week 2 Week 3 Week 4 Week 5 Last Friday Chicken 71 60 55 59 90 Pork Chops 60 43 57 61 81 Prime Rib 90 71 51 59 107 Lobster 82 63 75 80 91 Veal Cutlet 79 40 68 79 90 382 277 306 338 459 What is the percentage of total items sold for each menu item averaged over the past five Fridays? а. b. The manager notes that sales on the second Friday were lower than normal because of a weather problem. Sales on the last Friday were higher than normal because of an in-town sporting event. He believes the number of menu items to be sold this Friday will be about "average"; that is, they will exclude the one lower- than-normal Friday and one higher-than-normal Friday. 1. What is the total number of entrées expected to be served this Friday?
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- Import Illinois.xls as a table. Using logical indexing to select the years with more than 2800 cases of Diabetes. Then plot all of the data on the same axis. F1 fx Homicide B C E Year Accidents Cancer Diabetes Heart Disease Homicide| Suicide 1999 4125 25024 3004 33387 1023 1020 3 2000 4041 25365 2995 31844 991 1003 4. 2001 4077 24778 3092 30990 1087 1139 2002 4222 24737 3011 30821 1016 1145 2003 3942 24464 3044 29816 966 1011 7. 2004 4133 24289 3069 28284 871 1028 8. 2005 4182 24250 3034 28226 866 1086 9. 2006 4451 24084 2795 27007 865 1010 10 2007 4367 24115 2851 25813 863 1108 11 2008 4218 24300 2846 26078 872 1198 12 2009 3961 24185 2741 24931 881 1177 13 2010 3997 24070 2507 24959 783 1178 14 2011 4166 24007 2693 24987 812 1226 15 2012 4488 24562 2706 24667 832 1292 16 2013 4511 24491 2798 17 24839 792 1321 2014 4644 24501 2712 18 25024 792 1398 2015 4850 24713 2817 25652 19 863 1363 20 21Here are the numbers of robberies in New York City, according to the New York Police Department (NYPD), for 2000 through 2017. Display these data in a graph. Year: 2000 2001 2002 2003 2004 Count: 32,562 28,202 27,229 25,989 24,373 Year: 2005 2006 2007 2008 2009 Count: 24,722 23,739 21,809 22,401 18,601 Year: 2010 2011 2012 2013 Count: 19,486 19,717 20,144 19,128 Year: 2014 2015 2016 2017 Count: 16,539 16,931 15,500 13,956 Click to download the data in your preferred format. CSV Excel JMP Mac-Text Minitab PC-Text R SPSS TI CrunchIt! What are the most important facts that the data show? The crime rate appears to be leveling off. The largest percentage decrease in the crime rate was between 2000 and 2001. In another 17 years, the crime rate will be close to zero. There were less than half as many robberies in 2017 than there were in 2000. Robberies decreased overall from 2000 to 2017, with occasional…QOCH.B The number of cell phones per 100 residents in countries in Europe is given in Table #1 for the year 2010. The number of cell phones per 100 residents in countries of the Americas is given in Table #2 also for the year 2010 ("Population reference bureau," 2013). Table #1: Number of Cell Phones per 100 Residents in Europe 100 76 100 130 75 84 112 84 138 133 118 134 126 188 129 93 64 128 124 122 109 121 127 152 96 63 99 95 151 147 123 95 67 67 118 125 110 115 140 115 141 77 98 102 102 112 118 118 54 23 121 126 47 Table #2: Number of Cell Phones per 100 Residents in the Americas 158 117 106 159 53 50 78 66 88 92 42 3 150 72 86 113 50 58 70 109 37 32 85 101 75 69 55 115 95 73 86 157 100 119 81 113 87 105 96 Let μ1 = mean number of cell phones…
- The following table gives the annual revenue for the Microsoft Corp. in billions of dollars for a ten-year period. Year Microsoft 2007 2008 51 60 2009 2010 58 62 2011 2012 70 73 2013 2014 2015 2016 78 86 94 85 Construct and upload a boxplot for the Microsoft data. Be sure to label all the important numbers for the box plot.Pyramid Lake, Nevada, is described as the pride of the Paiute Indian Nation. It is a beautiful desert lake famous for very large trout. The elevation of the lake surface (feet above sea level) varies according to the annual flow of the Truckee River from Lake Tahoe. Assume that the U.S. Geological Survey provided the following data: Year 1986 1987 1988 1989 1990 1991 1992 1993 Elevation 3817 3815 3810 3812 3808 3803 3798 3797 Year 1994 1995 1996 1997 1998 1999 2000 Elevation 3795 3797 3802 3807 3811 3816 3817 Make a time series graph.A statistics instructor at a large western university would like to examine the relationship (if any) between the number of optional homework problems students do during the semester and their final course grade. She randomly selects 12 students for study and asks them to keep track of the number of these problems completed during the course of the semester. At the end of the class each student's total marks is recorded along with their final grade. The data follow in Table 2. Table 2 Problem Course Grade 51 62 58 68 62 66 65 66 67 68 76 72 77 73 78 72 78 78 84 73 85 76 91 75 For this setting identify the response variable. i. i. For this setting, identify the predictor variable. Compute the linear correlation coefficient for this data set iv. ii. Classify the direction and strength of the correlation Test the hypothesis for a significant linear correlation, a = 0.05 What is the valid prediction range for this setting? Use the regression equation to predict a student's final course…
- QOCH.C The number of cell phones per 100 residents in countries in Europe is given in Table #1 for the year 2010. The number of cell phones per 100 residents in countries of the Americas is given in Table #2 also for the year 2010 ("Population reference bureau," 2013). Table #1: Number of Cell Phones per 100 Residents in Europe 100 76 100 130 75 84 112 84 138 133 118 134 126 188 129 93 64 128 124 122 109 121 127 152 96 63 99 95 151 147 123 95 67 67 118 125 110 115 140 115 141 77 98 102 102 112 118 118 54 23 121 126 47 Table #2: Number of Cell Phones per 100 Residents in the Americas 158 117 106 159 53 50 78 66 88 92 42 3 150 72 86 113 50 58 70 109 37 32 85 101 75 69 55 115 95 73 86 157 100 119 81 113 87 105 96 Let μ1 = mean number of cell phones…The following table shows the square footage of houses in an area that sold recently along with the selling price. Sq. Ft. Price 2096, 295000, 3160, 338000, 2320, 265000, 3150, 365000, 2760, 330000, 3650, 412000, 2125, 320000, 3085, 342000, 4750, 485000, 2100, 320000, 3100, 316000, 2240, 321000, 3300, 347000, 2800, 350000, 2825, 330000, 3275, 420000 1. Find the equation of the regression line (line of best fit). 2. Determine if there is a strong linear correlation. 3. If there is a strong linear correlation predict the selling price of a 3333 sq. ft. homeA statistics instructor at a large western university would like to examine the relationship (if any) between the number of optional homework problems students do during the semester and their final course grade. She randomly selects 12 students for study and asks them to keep track of the number of these problems completed during the course of the semester. At the end of the class each student's total is recorded along with their final grade. Problems 57 85 91 78 72 58 62 65 68 76 77 78 84 78 73 76 75 Grade 62 68 66 66 67 72 73 1. For this setting identify the response variable. For this setting, identify the predictor variable. 2. Find the following a. Compute the linear correlation coefficient r for this data set. b. Test for a significant linear correlation. c. Classify the direction and strength of the correlation. i. Direction: ii. Strength: d. Equation of the least-squares regression line. What is the valid prediction range for this setting? 000 e. f. Test the significant of the…
- The manager of a trendy downtown café in Columbus, Ohio, collects weekly data on the number of customers it serves. The accompanying file contains the data. Week Customers 1 944 2 997 3 962 4 956 5 1045 6 1120 7 1069 8 1000 9 923 10 835 11 840 12 784 13 793 14 851 15 903 16 854 17 918 18 991 19 986 20 930 21 983 22 1008 23 962 24 888 25 895 26 978 27 1047 28 1050 29 1136 30 1225 31 1205 32 1195 33 1188 34 1177 35 1097 36 1074 37 1017 38 967 39 1007 40 949 41 930 42 1010 43 984 44 1091 45 1189 46 1254 47 1182 48 1235 49 1323 50 1305 51 1381 52 1365 1. Use the simple exponential smoothing technique with α = 0.2 to make a forecast for Week 53. Note: Do not round intermediate calculations. Round final answer to 2 decimal places. 2. Use the simple exponential smoothing technique with α = 0.4 to make a forecast for Week 53. Note: Do not round intermediate calculations. Round final…Year No. of Eastern Bluebird 1970 200 1975 300 1980 125 1985 250 1990 425 1995 450 2000 575 2005 675 2010 500 can you please solve f ,g and h a) Make a scatter plot of the number of birds vs. year record. b) Create a table with this data that compares Years Since 1900 vs. the number of birds. Fill in extra columns for Years-Since-Squared and Years*Birds. Complete the table by adding rows for column totals and column averages. c) Calculate the linear regression for this model. e) Calculate the correlation coefficient for this model. f) Translate your linear regression so that the model is now Year vs. Number of birds. g) Add the model to your scatter plot. h) Compute the residual errors for your model. i) Plot your residual errors. j) Interpolate your model to find the number of birds in 1983 and 2001.The table to the right shows the arrival data for two airlines in five cities. Complete parts (a) through (c) below. Excelsior Airlines Percentage Number of on-time arrivals Destination Los Angeles 94.5% Phoenix 95.7% San Diego 94.4% San Francisco 83.5% 85.9% Seattle Total 440 277 101 631 2183 3632 Paradise Airlines Percentage Number of on-time arrivals 87.9% 94.6% 88.6% 75.6% 72.8% 821 5177 406 405 259 7068 a. Which airline has the higher percentage of on-time flights to the five cities? Excelsior Airlines has the higher percentage of on-time flights. b. Compute the percentage of on-time flights for the two airlines over all five cities. Over all five cities, Excelsior Airlines had an on-time percentage of % and Paradise Airlines had an on-time percentage of %. (Round to the nearest tenth as needed.)