Consider the following data: 1 1.6 2.9 3. 4.1 4.4 5.8 6.5 7.1 7.2 7.5 y 3. 3.3 4 4.1 4.8 5.4 5.6 5.9 5.2 4.9 4.7 4.3 a) Create a scatterplot, print, and attach to the worksheet. b) Clearly, this data is not linear. Guess how this scatter plot suggests that the data should be transformed. 75
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- The regional transit authority for a major metropolitan area wants to determine whether there is any relationship between the age of a bus and the annual maintenance cost. A sample of 10 buses resulted in the data in Worksheet 2. Worksheet 2 Age of a Bus (years) Maintenance Cost ($) 1 350 2 370 2 480 2 520 2 590 3 550 4 750 4 800 5 790 5 950 At the 0.05 level of significance, is there evidence of a linear relationship between the age of a bus and the annual maintenance cost.Given the following data for 25 male students, build a modified box plot and identify the required statistics. Weight (lb): 123 134 140 148 149 150 150 150 155 158 160 160 163 170 170 175 175 175 180 185 190 195 223 231 -Identify the median for this data -identify the interquartile range -identify the value of the upper limit -identify the value of the adjacent Ppoint -is the minimum the adjacent point?17) On this worksheet, make an XY scatter plot linked to the following data: X Y 1.01 2.8482 1.48 4.2772 1.8 4.788 1.81 5.3757 1.07 2.5252 1.53 3.0906 1.46 4.3362 1.38 3.2016 1.77 4.3542 1.88 4.8692 1.32 3.8676 1.75 3.9375 1.94 5.7424 1.19 2.4752 1.31 26.2 1.56 4.5708 1.16 2.842 1.22 2.44 1.72 5.1256 1.45 4.3355 1.43 4.2471 1.19 3.5343 2 5.46…
- An agent for a property management company would like to be able to predict the monthly rental cost for apartments based on the size of the apartment as defined by square footage. A sample of the rent of 25 apartments in a college rental neighborhood was selected, and the information collected revealed the following: Apartment Size (Sq. Ft.) Monthly Rent ($) 1 850 950 2 1,450 1,600 3 1,085 1,200 4 1,232 1,500 5 718 950 6 1,485 1,700 7 1,136 1,650 8 726 935 9 700 875 10 956 1,150 11 1,100 1,400 12 1,285 1,650 13 1,985 2,300 14 1,369 1,800 15 1,175 1,400 16 1,225 1,450 17 1,245 1,100 18 1,259 1,700 19 1,150 1,200 20 896 1,150 21 1,361 1,600 22 1,040 1,650 23 755 1,200 24 1,000 800 25 1,200 1,750 e) Determine the coefficient of determination r2 and then completely interpret…An agent for a property management company would like to be able to predict the monthly rental cost for apartments based on the size of the apartment as defined by square footage. A sample of the rent of 25 apartments in a college rental neighborhood was selected, and the information collected revealed the following: Apartment Size (Sq. Ft.) Monthly Rent ($) 1 850 950 2 1,450 1,600 3 1,085 1,200 4 1,232 1,500 5 718 950 6 1,485 1,700 7 1,136 1,650 8 726 935 9 700 875 10 956 1,150 11 1,100 1,400 12 1,285 1,650 13 1,985 2,300 14 1,369 1,800 15 1,175 1,400 16 1,225 1,450 17 1,245 1,100 18 1,259 1,700 19 1,150 1,200 20 896 1,150 21 1,361 1,600 22 1,040 1,650 23 755 1,200 24 1,000 800 25 1,200 1,750 i) Determine a 95% interval estimate for the average rent of apartments with 1000…The following data give the number of defective motors received in 20 differentshipments. 8 12 10 16 10 25 21 15 17 526 21 29 8 6 21 10 17 15 13 Construct a dot plot for these data.
- Which of the scatter diagrams below suggests a strong positive linear relationship between the x and y variables?Here's the dataset: Golfer Distance Accuracy Index Woods 316.1 54.6 3.58 Perry 304.7 63.4 3.48 Gutschewski 310.5 57.9 3.27 Wetterich 311.7 56.6 3.18 Hearn 295.2 68.5 2.82 Gronberg 301.4 63.2 2.74 Frazar 301 63.5 2.74 Warren 299.2 64.2 2.55 Glover 302.2 60.7 2.27 MacKenzie 300.2 62.1 2.22 Love III 305.4 57.9 2.21 Garcia 303.5 59.4 2.21 Durant 289.2 70.9 2.2 O'Hair 300.1 61.4 2.02 Singh 301.1 60.2 1.92 Long 298.3 62.4 1.9 Smith 300.8 60.2 1.85 Hend 318.9 45.4 1.89 Hughes 291.3 67.5 1.76 Stadler 300.1 60.4 1.76 Allenby 297.7 62.3 1.75 Mayfair 288.2 69.8 1.71 Appleby 300.6 59.3 1.58 Snyder III 291.8 66.3 1.56 Purdy 295.2 63.4 1.52 Brigman 295.5 63.1 1.5 Bryant 283.2 73 1.49 Rollins 294.4 63.7 1.43 Jobe 302.3 57.3 1.42 Brehaut 286.6 69.9 1.4 Ogilvy 298 60.7 1.4 Henry 297.6 61 1.4 Rose 294.1 63.7 1.37 Westwood 296.8 61.5 1.36 Johnson 290 66.9 1.34 Senden 291 66 1.31 Mickelson 300 58.7 1.3 Watney 298.9 59.4 1.26…Which model—the one for parliaments or the one for ministries (or cabinets)—presented in the article has the greater explanatory power? How can you tell?
- For a table of national information regarding a specific country, it is found that the correlation with Internet use is 0.545 for GDP, 0.734 for cellular-phone use, 0.664 for literacy, −0.893 for fertility, and 0.854 for CO2 emissions. Which variable has the weakest linear association with Internet use? a. GDP has the weakest linear association with Internet use. b. Cellular-phone use has the weakest linear association with Internet use. c. Fertility has the weakest linear association with Internet use. d. CO2 emissions has the weakest linear association with Internet use. e. Literacy has the weakest linear association with Internet use.Given the following data set, 10 8 13 9 11 14 6 4 12 7 5 9.14 8.14 8.74 8.77 9.26 8.10 6.13 3.10 9.13 7.26 4.74 (a) Construct a scatter plot. (b) Find the value of the linear coefficient and then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. (c) Identify the feature of the data that would be missed if part (b) was completed without constructing the scatter plot.