Description
i have 4 questions math pre calc please help
User generated content is uploaded by users for the purposes of learning and should be used following Studypool's honor code & terms of service.
Explanation & Answer
Review
Review
Anonymous
Really helped me to better understand my coursework. Super recommended.
Studypool
4.7
Trustpilot
4.5
Sitejabber
4.4
24/7 Homework Help
Stuck on a homework question? Our verified tutors can answer all questions, from basic math to advanced rocket science!
Most Popular Content
Week 5 Problem Set Correlation and Regression Techniques from an SPSS data set
Locate the data set "Bank.sav" and open it with SPSS. Follow the steps in section 10.15 Learning Activity as written. Answ ...
Week 5 Problem Set Correlation and Regression Techniques from an SPSS data set
Locate the data set "Bank.sav" and open it with SPSS. Follow the steps in section 10.15 Learning Activity as written. Answer questions 1-3 in the activity based on your observations of the SPSS output.Type your answers into a Word document. Copy and paste the full SPSS output including any supporting graphs and tables directly from SPSS into the Word document for submission to the instructor. The SPSS output must be submitted with the problem set answers in order to receive full credit for the assignment.Locate the data set "Census.sav" and open it with SPSS. Follow the steps in section 11.16 Learning Activity as written. Answer questions 1, 2, 3, and 5 in the activity based on your observations of the SPSS output. Type your answers into a Word document. Copy and paste the full SPSS output including any supporting graphs and tables directly from SPSS into the Word document for submission to the instructor. The SPSS output must be submitted with the problem set answers in order to receive full credit for the assignment.
4 pages
Expectedpayofftable
The pay off tables enable the hotel owner to that would lead to higher sales in each case. For the given number of full pr ...
Expectedpayofftable
The pay off tables enable the hotel owner to that would lead to higher sales in each case. For the given number of full price rooms, the
SNHU Healthy People Data Visualization Discussion
I'm working on a science discussion question and need an explanation and answer to help me learn.For this discussion, you ...
SNHU Healthy People Data Visualization Discussion
I'm working on a science discussion question and need an explanation and answer to help me learn.For this discussion, you will obtain monitoring data analyzed within a Healthy People objective, and then interpret this information for its influence on the decision-making process.Step 1—Healthy People Data Visualization: Visit the DATA2020database for Healthy People (i.e., the Data Search tab on www.HealthyPeople.gov ). From the Topic Area drop-down menu, select any area of interest. Click the Searchbutton to review search results. On the results page, scroll through the entries and select one (1) Healthy People Objective that has a View Chart button. This will open a new page that depicts a visual representation of this Healthy People objective's data. Take a screenshot of this data visualization (you will insert this into your initial post).Step 2—Public Health Research, Policy, or Practice: Use the Shapiro Library and identify a peer-reviewed journal article pertaining to the topic area you selected in Step 1. The article should be published in a public-health specific (i.e., nonmedical) journal and should involve research, policy, or practice within the topic area. Download the full text of this article and review it carefully.Using the data visualization (from Step 1) and the journal article (from Step 2), please proceed with your initial discussion post.In your discussion post, please address the following:Part 1—Explanation of Topic Area and Data Visualization (100 words): First, summarize the topic area and indicate the selected Healthy People Objective. Interpret the findings/trends from the data visualization. Is progress being made towards the desired outcome? Please explain your rationale for interpreting the data in this manner. Include a screenshot of the visual with your submission.Part 2—Summary of Journal Article (100 words): Discuss the public health research, policy, or practice and its relationship to the Healthy People Objective identified in Part 1.Part 3—Connecting Data Trends and Decision Making (100 words): Imagine that you are a health professional who (co)authored the selected journal article. How would the Healthy People data visualization inform the decisions you make? What would you have done differently compared to the actual author(s)? Please explain your rationale and provide examples.In response to your peers, ask questions to increase the clarity of their response and your understanding. Also, provide your thoughts on how a public health organization could respond to the findings to help improve the corresponding health issue in their community. Is further research necessary? Is there a program addressing this issue in place? Does a new program or policy need to be created? Think about how a public professional would try to address the issue this data has identified.To complete this assignment, review the Discussion Rubric PDFdocument.
3 pages
Trigonometry Problems 1 12
Solve △ABC using the given measurements. Round measures of sides to the nearest tenth and measures of angles to the near ...
Trigonometry Problems 1 12
Solve △ABC using the given measurements. Round measures of sides to the nearest tenth and measures of angles to the nearest
University of Wisconsin Milwaukee Regression Analysis R Code on R Studio Problems
Regression Analysis. Show all work and output to all code. I dont need just output, i need it to show how to use the outpu ...
University of Wisconsin Milwaukee Regression Analysis R Code on R Studio Problems
Regression Analysis. Show all work and output to all code. I dont need just output, i need it to show how to use the output.- You only need to do the LOF test for the reduced model on the project. All kinds of problems arise when you try to do it for the full model.- In the Fish set data, the weight is measured in grams. Everything else is measured in centimeters- First, for the lack of fit test, it would seem that a lot of you are running into an issue that I had not, but I am not sure why. If you do the lack of fit test for the full model, I am having a lot of people say that R gives a fatal error. This looks to be due to exceeding memory limitations when everything is broken down into factors. The remedy to this seems to be that we should do the LOF test only for the reduced model, so just do that.Using the “Fish.txt” data set, specify and completely analyze a multiple linear regression model that relates
weight to length1, length2, length3, height, and width. Carry out a full analysis of the model, including tests
for each coefficient (with the significance level adjusted for multiple tests) and confidence intervals for each
coefficient. If any are not significant to the model, drop them, fit the reduced model, and repeat the full
analysis. Do not forget to examine multicollinearity among predictors, and for each model you fit, carry out a
formal test for a lack of fit.Fish.txt :"Weight" "Length1" "Length2" "Length3" "Height" "Width""1" 242 23.2 25.4 30 11.52 4.02"2" 290 24 26.3 31.2 12.48 4.3056"3" 340 23.9 26.5 31.1 12.3778 4.6961"4" 363 26.3 29 33.5 12.73 4.4555"5" 430 26.5 29 34 12.444 5.134"6" 450 26.8 29.7 34.7 13.6024 4.9274"7" 500 26.8 29.7 34.5 14.1795 5.2785"8" 390 27.6 30 35 12.67 4.69"9" 450 27.6 30 35.1 14.0049 4.8438"10" 500 28.5 30.7 36.2 14.2266 4.9594"11" 475 28.4 31 36.2 14.2628 5.1042"12" 500 28.7 31 36.2 14.3714 4.8146"13" 500 29.1 31.5 36.4 13.7592 4.368"14" 340 29.5 32 37.3 13.9129 5.0728"15" 600 29.4 32 37.2 14.9544 5.1708"16" 600 29.4 32 37.2 15.438 5.58"17" 700 30.4 33 38.3 14.8604 5.2854"18" 700 30.4 33 38.5 14.938 5.1975"19" 610 30.9 33.5 38.6 15.633 5.1338"20" 650 31 33.5 38.7 14.4738 5.7276"21" 575 31.3 34 39.5 15.1285 5.5695"22" 685 31.4 34 39.2 15.9936 5.3704"23" 620 31.5 34.5 39.7 15.5227 5.2801"24" 680 31.8 35 40.6 15.4686 6.1306"25" 700 31.9 35 40.5 16.2405 5.589"26" 725 31.8 35 40.9 16.36 6.0532"27" 720 32 35 40.6 16.3618 6.09"28" 714 32.7 36 41.5 16.517 5.8515"29" 850 32.8 36 41.6 16.8896 6.1984"30" 1000 33.5 37 42.6 18.957 6.603"31" 920 35 38.5 44.1 18.0369 6.3063"32" 955 35 38.5 44 18.084 6.292"33" 925 36.2 39.5 45.3 18.7542 6.7497"34" 975 37.4 41 45.9 18.6354 6.7473"35" 950 38 41 46.5 17.6235 6.3705"36" 40 12.9 14.1 16.2 4.1472 2.268"37" 69 16.5 18.2 20.3 5.2983 2.8217"38" 78 17.5 18.8 21.2 5.5756 2.9044"39" 87 18.2 19.8 22.2 5.6166 3.1746"40" 120 18.6 20 22.2 6.216 3.5742"41" 0 19 20.5 22.8 6.4752 3.3516"42" 110 19.1 20.8 23.1 6.1677 3.3957"43" 120 19.4 21 23.7 6.1146 3.2943"44" 150 20.4 22 24.7 5.8045 3.7544"45" 145 20.5 22 24.3 6.6339 3.5478"46" 160 20.5 22.5 25.3 7.0334 3.8203"47" 140 21 22.5 25 6.55 3.325"48" 160 21.1 22.5 25 6.4 3.8"49" 169 22 24 27.2 7.5344 3.8352"50" 161 22 23.4 26.7 6.9153 3.6312"51" 200 22.1 23.5 26.8 7.3968 4.1272"52" 180 23.6 25.2 27.9 7.0866 3.906"53" 290 24 26 29.2 8.8768 4.4968"54" 272 25 27 30.6 8.568 4.7736"55" 390 29.5 31.7 35 9.485 5.355"56" 270 23.6 26 28.7 8.3804 4.2476"57" 270 24.1 26.5 29.3 8.1454 4.2485"58" 306 25.6 28 30.8 8.778 4.6816"59" 540 28.5 31 34 10.744 6.562"60" 800 33.7 36.4 39.6 11.7612 6.5736"61" 1000 37.3 40 43.5 12.354 6.525"62" 55 13.5 14.7 16.5 6.8475 2.3265"63" 60 14.3 15.5 17.4 6.5772 2.3142"64" 90 16.3 17.7 19.8 7.4052 2.673"65" 120 17.5 19 21.3 8.3922 2.9181"66" 150 18.4 20 22.4 8.8928 3.2928"67" 140 19 20.7 23.2 8.5376 3.2944"68" 170 19 20.7 23.2 9.396 3.4104"69" 145 19.8 21.5 24.1 9.7364 3.1571"70" 200 21.2 23 25.8 10.3458 3.6636"71" 273 23 25 28 11.088 4.144"72" 300 24 26 29 11.368 4.234"73" 5.9 7.5 8.4 8.8 2.112 1.408"74" 32 12.5 13.7 14.7 3.528 1.9992"75" 40 13.8 15 16 3.824 2.432"76" 51.5 15 16.2 17.2 4.5924 2.6316"77" 70 15.7 17.4 18.5 4.588 2.9415"78" 100 16.2 18 19.2 5.2224 3.3216"79" 78 16.8 18.7 19.4 5.1992 3.1234"80" 80 17.2 19 20.2 5.6358 3.0502"81" 85 17.8 19.6 20.8 5.1376 3.0368"82" 85 18.2 20 21 5.082 2.772"83" 110 19 21 22.5 5.6925 3.555"84" 115 19 21 22.5 5.9175 3.3075"85" 125 19 21 22.5 5.6925 3.6675"86" 130 19.3 21.3 22.8 6.384 3.534"87" 120 20 22 23.5 6.11 3.4075"88" 120 20 22 23.5 5.64 3.525"89" 130 20 22 23.5 6.11 3.525"90" 135 20 22 23.5 5.875 3.525"91" 110 20 22 23.5 5.5225 3.995"92" 130 20.5 22.5 24 5.856 3.624"93" 150 20.5 22.5 24 5.856 3.624"94" 145 20.7 22.7 24.2 5.9532 3.63"95" 150 21 23 24.5 5.2185 3.626"96" 170 21.5 23.5 25 6.275 3.725"97" 225 22 24 25.5 7.293 3.723"98" 145 22 24 25.5 6.375 3.825"99" 188 22.6 24.6 26.2 6.7334 4.1658"100" 180 23 25 26.5 6.4395 3.6835"101" 197 23.5 25.6 27 6.561 4.239"102" 218 25 26.5 28 7.168 4.144"103" 300 25.2 27.3 28.7 8.323 5.1373"104" 260 25.4 27.5 28.9 7.1672 4.335"105" 265 25.4 27.5 28.9 7.1672 4.335"106" 250 25.4 27.5 28.9 7.2828 4.5662"107" 250 25.9 28 29.4 7.8204 4.2042"108" 300 26.9 28.7 30.1 7.5852 4.6354"109" 320 27.8 30 31.6 7.6156 4.7716"110" 514 30.5 32.8 34 10.03 6.018"111" 556 32 34.5 36.5 10.2565 6.3875"112" 840 32.5 35 37.3 11.4884 7.7957"113" 685 34 36.5 39 10.881 6.864"114" 700 34 36 38.3 10.6091 6.7408"115" 700 34.5 37 39.4 10.835 6.2646"116" 690 34.6 37 39.3 10.5717 6.3666"117" 900 36.5 39 41.4 11.1366 7.4934"118" 650 36.5 39 41.4 11.1366 6.003"119" 820 36.6 39 41.3 12.4313 7.3514"120" 850 36.9 40 42.3 11.9286 7.1064"121" 900 37 40 42.5 11.73 7.225"122" 1015 37 40 42.4 12.3808 7.4624"123" 820 37.1 40 42.5 11.135 6.63"124" 1100 39 42 44.6 12.8002 6.8684"125" 1000 39.8 43 45.2 11.9328 7.2772"126" 1100 40.1 43 45.5 12.5125 7.4165"127" 1000 40.2 43.5 46 12.604 8.142"128" 1000 41.1 44 46.6 12.4888 7.5958"129" 200 30 32.3 34.8 5.568 3.3756"130" 300 31.7 34 37.8 5.7078 4.158"131" 300 32.7 35 38.8 5.9364 4.3844"132" 300 34.8 37.3 39.8 6.2884 4.0198"133" 430 35.5 38 40.5 7.29 4.5765"134" 345 36 38.5 41 6.396 3.977"135" 456 40 42.5 45.5 7.28 4.3225"136" 510 40 42.5 45.5 6.825 4.459"137" 540 40.1 43 45.8 7.786 5.1296"138" 500 42 45 48 6.96 4.896"139" 567 43.2 46 48.7 7.792 4.87"140" 770 44.8 48 51.2 7.68 5.376"141" 950 48.3 51.7 55.1 8.9262 6.1712"142" 1250 52 56 59.7 10.6863 6.9849"143" 1600 56 60 64 9.6 6.144"144" 1550 56 60 64 9.6 6.144"145" 1650 59 63.4 68 10.812 7.48"146" 6.7 9.3 9.8 10.8 1.7388 1.0476"147" 7.5 10 10.5 11.6 1.972 1.16"148" 7 10.1 10.6 11.6 1.7284 1.1484"149" 9.7 10.4 11 12 2.196 1.38"150" 9.8 10.7 11.2 12.4 2.0832 1.2772"151" 8.7 10.8 11.3 12.6 1.9782 1.2852"152" 10 11.3 11.8 13.1 2.2139 1.2838"153" 9.9 11.3 11.8 13.1 2.2139 1.1659"154" 9.8 11.4 12 13.2 2.2044 1.1484"155" 12.2 11.5 12.2 13.4 2.0904 1.3936"156" 13.4 11.7 12.4 13.5 2.43 1.269"157" 12.2 12.1 13 13.8 2.277 1.2558"158" 19.7 13.2 14.3 15.2 2.8728 2.0672"159" 19.9 13.8 15 16.2 2.9322 1.8792
Similar Content
Arcs and chords help please :) Thanks
...
Advanced Calculus questions
Questions.docx ...
Quadratic Equations Pre cal
Show all work. please don't skip any steps FullSizeRender (22).jpg FullSizeRender (23).jpg FullSizeRender (...
Policy Memorandum Final Writing Assignment
please complete this memorandum regarding to the rubric I attached. Also I attached a peer review if you want to look at.P...
Two questions on graphs
Week 2.docx...
Central Limit Theorem and Rent Paid by 30 Students Analysis
I need help choosing from two of my classmates’ data set, taking 30 random samples of 5 data points each (one way: Past ...
Related Tags
Book Guides
Anthem
by Ayn Rand
The Restless Wave
by John McCain
Bridge to Terabithia
by Katherine Paterson
The Prince
by Niccolò Machiavelli
Good Kids Bad City
by Kyle Swenson
The Atlantis Gene
by S. A. Beck
The Grapes of Wrath
by John Steinbeck
The Point of it All - A Lifetime of Great Loves and Endeavors
by Charles Krauthammer
Little Women
by Louisa May Alcott
Get 24/7
Homework help
Our tutors provide high quality explanations & answers.
Post question
Most Popular Content
Week 5 Problem Set Correlation and Regression Techniques from an SPSS data set
Locate the data set "Bank.sav" and open it with SPSS. Follow the steps in section 10.15 Learning Activity as written. Answ ...
Week 5 Problem Set Correlation and Regression Techniques from an SPSS data set
Locate the data set "Bank.sav" and open it with SPSS. Follow the steps in section 10.15 Learning Activity as written. Answer questions 1-3 in the activity based on your observations of the SPSS output.Type your answers into a Word document. Copy and paste the full SPSS output including any supporting graphs and tables directly from SPSS into the Word document for submission to the instructor. The SPSS output must be submitted with the problem set answers in order to receive full credit for the assignment.Locate the data set "Census.sav" and open it with SPSS. Follow the steps in section 11.16 Learning Activity as written. Answer questions 1, 2, 3, and 5 in the activity based on your observations of the SPSS output. Type your answers into a Word document. Copy and paste the full SPSS output including any supporting graphs and tables directly from SPSS into the Word document for submission to the instructor. The SPSS output must be submitted with the problem set answers in order to receive full credit for the assignment.
4 pages
Expectedpayofftable
The pay off tables enable the hotel owner to that would lead to higher sales in each case. For the given number of full pr ...
Expectedpayofftable
The pay off tables enable the hotel owner to that would lead to higher sales in each case. For the given number of full price rooms, the
SNHU Healthy People Data Visualization Discussion
I'm working on a science discussion question and need an explanation and answer to help me learn.For this discussion, you ...
SNHU Healthy People Data Visualization Discussion
I'm working on a science discussion question and need an explanation and answer to help me learn.For this discussion, you will obtain monitoring data analyzed within a Healthy People objective, and then interpret this information for its influence on the decision-making process.Step 1—Healthy People Data Visualization: Visit the DATA2020database for Healthy People (i.e., the Data Search tab on www.HealthyPeople.gov ). From the Topic Area drop-down menu, select any area of interest. Click the Searchbutton to review search results. On the results page, scroll through the entries and select one (1) Healthy People Objective that has a View Chart button. This will open a new page that depicts a visual representation of this Healthy People objective's data. Take a screenshot of this data visualization (you will insert this into your initial post).Step 2—Public Health Research, Policy, or Practice: Use the Shapiro Library and identify a peer-reviewed journal article pertaining to the topic area you selected in Step 1. The article should be published in a public-health specific (i.e., nonmedical) journal and should involve research, policy, or practice within the topic area. Download the full text of this article and review it carefully.Using the data visualization (from Step 1) and the journal article (from Step 2), please proceed with your initial discussion post.In your discussion post, please address the following:Part 1—Explanation of Topic Area and Data Visualization (100 words): First, summarize the topic area and indicate the selected Healthy People Objective. Interpret the findings/trends from the data visualization. Is progress being made towards the desired outcome? Please explain your rationale for interpreting the data in this manner. Include a screenshot of the visual with your submission.Part 2—Summary of Journal Article (100 words): Discuss the public health research, policy, or practice and its relationship to the Healthy People Objective identified in Part 1.Part 3—Connecting Data Trends and Decision Making (100 words): Imagine that you are a health professional who (co)authored the selected journal article. How would the Healthy People data visualization inform the decisions you make? What would you have done differently compared to the actual author(s)? Please explain your rationale and provide examples.In response to your peers, ask questions to increase the clarity of their response and your understanding. Also, provide your thoughts on how a public health organization could respond to the findings to help improve the corresponding health issue in their community. Is further research necessary? Is there a program addressing this issue in place? Does a new program or policy need to be created? Think about how a public professional would try to address the issue this data has identified.To complete this assignment, review the Discussion Rubric PDFdocument.
3 pages
Trigonometry Problems 1 12
Solve △ABC using the given measurements. Round measures of sides to the nearest tenth and measures of angles to the near ...
Trigonometry Problems 1 12
Solve △ABC using the given measurements. Round measures of sides to the nearest tenth and measures of angles to the nearest
University of Wisconsin Milwaukee Regression Analysis R Code on R Studio Problems
Regression Analysis. Show all work and output to all code. I dont need just output, i need it to show how to use the outpu ...
University of Wisconsin Milwaukee Regression Analysis R Code on R Studio Problems
Regression Analysis. Show all work and output to all code. I dont need just output, i need it to show how to use the output.- You only need to do the LOF test for the reduced model on the project. All kinds of problems arise when you try to do it for the full model.- In the Fish set data, the weight is measured in grams. Everything else is measured in centimeters- First, for the lack of fit test, it would seem that a lot of you are running into an issue that I had not, but I am not sure why. If you do the lack of fit test for the full model, I am having a lot of people say that R gives a fatal error. This looks to be due to exceeding memory limitations when everything is broken down into factors. The remedy to this seems to be that we should do the LOF test only for the reduced model, so just do that.Using the “Fish.txt” data set, specify and completely analyze a multiple linear regression model that relates
weight to length1, length2, length3, height, and width. Carry out a full analysis of the model, including tests
for each coefficient (with the significance level adjusted for multiple tests) and confidence intervals for each
coefficient. If any are not significant to the model, drop them, fit the reduced model, and repeat the full
analysis. Do not forget to examine multicollinearity among predictors, and for each model you fit, carry out a
formal test for a lack of fit.Fish.txt :"Weight" "Length1" "Length2" "Length3" "Height" "Width""1" 242 23.2 25.4 30 11.52 4.02"2" 290 24 26.3 31.2 12.48 4.3056"3" 340 23.9 26.5 31.1 12.3778 4.6961"4" 363 26.3 29 33.5 12.73 4.4555"5" 430 26.5 29 34 12.444 5.134"6" 450 26.8 29.7 34.7 13.6024 4.9274"7" 500 26.8 29.7 34.5 14.1795 5.2785"8" 390 27.6 30 35 12.67 4.69"9" 450 27.6 30 35.1 14.0049 4.8438"10" 500 28.5 30.7 36.2 14.2266 4.9594"11" 475 28.4 31 36.2 14.2628 5.1042"12" 500 28.7 31 36.2 14.3714 4.8146"13" 500 29.1 31.5 36.4 13.7592 4.368"14" 340 29.5 32 37.3 13.9129 5.0728"15" 600 29.4 32 37.2 14.9544 5.1708"16" 600 29.4 32 37.2 15.438 5.58"17" 700 30.4 33 38.3 14.8604 5.2854"18" 700 30.4 33 38.5 14.938 5.1975"19" 610 30.9 33.5 38.6 15.633 5.1338"20" 650 31 33.5 38.7 14.4738 5.7276"21" 575 31.3 34 39.5 15.1285 5.5695"22" 685 31.4 34 39.2 15.9936 5.3704"23" 620 31.5 34.5 39.7 15.5227 5.2801"24" 680 31.8 35 40.6 15.4686 6.1306"25" 700 31.9 35 40.5 16.2405 5.589"26" 725 31.8 35 40.9 16.36 6.0532"27" 720 32 35 40.6 16.3618 6.09"28" 714 32.7 36 41.5 16.517 5.8515"29" 850 32.8 36 41.6 16.8896 6.1984"30" 1000 33.5 37 42.6 18.957 6.603"31" 920 35 38.5 44.1 18.0369 6.3063"32" 955 35 38.5 44 18.084 6.292"33" 925 36.2 39.5 45.3 18.7542 6.7497"34" 975 37.4 41 45.9 18.6354 6.7473"35" 950 38 41 46.5 17.6235 6.3705"36" 40 12.9 14.1 16.2 4.1472 2.268"37" 69 16.5 18.2 20.3 5.2983 2.8217"38" 78 17.5 18.8 21.2 5.5756 2.9044"39" 87 18.2 19.8 22.2 5.6166 3.1746"40" 120 18.6 20 22.2 6.216 3.5742"41" 0 19 20.5 22.8 6.4752 3.3516"42" 110 19.1 20.8 23.1 6.1677 3.3957"43" 120 19.4 21 23.7 6.1146 3.2943"44" 150 20.4 22 24.7 5.8045 3.7544"45" 145 20.5 22 24.3 6.6339 3.5478"46" 160 20.5 22.5 25.3 7.0334 3.8203"47" 140 21 22.5 25 6.55 3.325"48" 160 21.1 22.5 25 6.4 3.8"49" 169 22 24 27.2 7.5344 3.8352"50" 161 22 23.4 26.7 6.9153 3.6312"51" 200 22.1 23.5 26.8 7.3968 4.1272"52" 180 23.6 25.2 27.9 7.0866 3.906"53" 290 24 26 29.2 8.8768 4.4968"54" 272 25 27 30.6 8.568 4.7736"55" 390 29.5 31.7 35 9.485 5.355"56" 270 23.6 26 28.7 8.3804 4.2476"57" 270 24.1 26.5 29.3 8.1454 4.2485"58" 306 25.6 28 30.8 8.778 4.6816"59" 540 28.5 31 34 10.744 6.562"60" 800 33.7 36.4 39.6 11.7612 6.5736"61" 1000 37.3 40 43.5 12.354 6.525"62" 55 13.5 14.7 16.5 6.8475 2.3265"63" 60 14.3 15.5 17.4 6.5772 2.3142"64" 90 16.3 17.7 19.8 7.4052 2.673"65" 120 17.5 19 21.3 8.3922 2.9181"66" 150 18.4 20 22.4 8.8928 3.2928"67" 140 19 20.7 23.2 8.5376 3.2944"68" 170 19 20.7 23.2 9.396 3.4104"69" 145 19.8 21.5 24.1 9.7364 3.1571"70" 200 21.2 23 25.8 10.3458 3.6636"71" 273 23 25 28 11.088 4.144"72" 300 24 26 29 11.368 4.234"73" 5.9 7.5 8.4 8.8 2.112 1.408"74" 32 12.5 13.7 14.7 3.528 1.9992"75" 40 13.8 15 16 3.824 2.432"76" 51.5 15 16.2 17.2 4.5924 2.6316"77" 70 15.7 17.4 18.5 4.588 2.9415"78" 100 16.2 18 19.2 5.2224 3.3216"79" 78 16.8 18.7 19.4 5.1992 3.1234"80" 80 17.2 19 20.2 5.6358 3.0502"81" 85 17.8 19.6 20.8 5.1376 3.0368"82" 85 18.2 20 21 5.082 2.772"83" 110 19 21 22.5 5.6925 3.555"84" 115 19 21 22.5 5.9175 3.3075"85" 125 19 21 22.5 5.6925 3.6675"86" 130 19.3 21.3 22.8 6.384 3.534"87" 120 20 22 23.5 6.11 3.4075"88" 120 20 22 23.5 5.64 3.525"89" 130 20 22 23.5 6.11 3.525"90" 135 20 22 23.5 5.875 3.525"91" 110 20 22 23.5 5.5225 3.995"92" 130 20.5 22.5 24 5.856 3.624"93" 150 20.5 22.5 24 5.856 3.624"94" 145 20.7 22.7 24.2 5.9532 3.63"95" 150 21 23 24.5 5.2185 3.626"96" 170 21.5 23.5 25 6.275 3.725"97" 225 22 24 25.5 7.293 3.723"98" 145 22 24 25.5 6.375 3.825"99" 188 22.6 24.6 26.2 6.7334 4.1658"100" 180 23 25 26.5 6.4395 3.6835"101" 197 23.5 25.6 27 6.561 4.239"102" 218 25 26.5 28 7.168 4.144"103" 300 25.2 27.3 28.7 8.323 5.1373"104" 260 25.4 27.5 28.9 7.1672 4.335"105" 265 25.4 27.5 28.9 7.1672 4.335"106" 250 25.4 27.5 28.9 7.2828 4.5662"107" 250 25.9 28 29.4 7.8204 4.2042"108" 300 26.9 28.7 30.1 7.5852 4.6354"109" 320 27.8 30 31.6 7.6156 4.7716"110" 514 30.5 32.8 34 10.03 6.018"111" 556 32 34.5 36.5 10.2565 6.3875"112" 840 32.5 35 37.3 11.4884 7.7957"113" 685 34 36.5 39 10.881 6.864"114" 700 34 36 38.3 10.6091 6.7408"115" 700 34.5 37 39.4 10.835 6.2646"116" 690 34.6 37 39.3 10.5717 6.3666"117" 900 36.5 39 41.4 11.1366 7.4934"118" 650 36.5 39 41.4 11.1366 6.003"119" 820 36.6 39 41.3 12.4313 7.3514"120" 850 36.9 40 42.3 11.9286 7.1064"121" 900 37 40 42.5 11.73 7.225"122" 1015 37 40 42.4 12.3808 7.4624"123" 820 37.1 40 42.5 11.135 6.63"124" 1100 39 42 44.6 12.8002 6.8684"125" 1000 39.8 43 45.2 11.9328 7.2772"126" 1100 40.1 43 45.5 12.5125 7.4165"127" 1000 40.2 43.5 46 12.604 8.142"128" 1000 41.1 44 46.6 12.4888 7.5958"129" 200 30 32.3 34.8 5.568 3.3756"130" 300 31.7 34 37.8 5.7078 4.158"131" 300 32.7 35 38.8 5.9364 4.3844"132" 300 34.8 37.3 39.8 6.2884 4.0198"133" 430 35.5 38 40.5 7.29 4.5765"134" 345 36 38.5 41 6.396 3.977"135" 456 40 42.5 45.5 7.28 4.3225"136" 510 40 42.5 45.5 6.825 4.459"137" 540 40.1 43 45.8 7.786 5.1296"138" 500 42 45 48 6.96 4.896"139" 567 43.2 46 48.7 7.792 4.87"140" 770 44.8 48 51.2 7.68 5.376"141" 950 48.3 51.7 55.1 8.9262 6.1712"142" 1250 52 56 59.7 10.6863 6.9849"143" 1600 56 60 64 9.6 6.144"144" 1550 56 60 64 9.6 6.144"145" 1650 59 63.4 68 10.812 7.48"146" 6.7 9.3 9.8 10.8 1.7388 1.0476"147" 7.5 10 10.5 11.6 1.972 1.16"148" 7 10.1 10.6 11.6 1.7284 1.1484"149" 9.7 10.4 11 12 2.196 1.38"150" 9.8 10.7 11.2 12.4 2.0832 1.2772"151" 8.7 10.8 11.3 12.6 1.9782 1.2852"152" 10 11.3 11.8 13.1 2.2139 1.2838"153" 9.9 11.3 11.8 13.1 2.2139 1.1659"154" 9.8 11.4 12 13.2 2.2044 1.1484"155" 12.2 11.5 12.2 13.4 2.0904 1.3936"156" 13.4 11.7 12.4 13.5 2.43 1.269"157" 12.2 12.1 13 13.8 2.277 1.2558"158" 19.7 13.2 14.3 15.2 2.8728 2.0672"159" 19.9 13.8 15 16.2 2.9322 1.8792
Earn money selling
your Study Documents