COMPUTING ACTUAL AREAS FROM A SCALE DRAWING
User Generated
FAF114629829911568132659
Mathematics
Description
Icant do this. The student govertment liked your half-court basketball plan.They have asked you to calculate the actual area of the court so that theu can stimate the cost of the project, base on your drawing below whAT IS THE AREA OF THE PLANNED COURT GOING TO BE?1INCH=15 FEET THE DRAWING IS 2INCHES BY 1 2/3 INCHES
User generated content is uploaded by users for the purposes of learning and should be used following Studypool's honor code & terms of service.
This question has not been answered.
Create a free account to get help with this and any other question!
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
2 pages
Chi Squared
1. A Chi-square test is used to determine if there is a statistically significant difference between groups of a categoric ...
Chi Squared
1. A Chi-square test is used to determine if there is a statistically significant difference between groups of a categorical variable. It can be used ...
Strayer University Week 3 SIPOC Elements & Process Measurements Paper 3
Homework Assignment 3Due in Week 3 and worth 30 pointsTouring a Process. Select a place of your choice (e.g. supermarket, ...
Strayer University Week 3 SIPOC Elements & Process Measurements Paper 3
Homework Assignment 3Due in Week 3 and worth 30 pointsTouring a Process. Select a place of your choice (e.g. supermarket, doctor’s office, library, Post Office, department store, etc.) and observe one or more key processes, the associated suppliers, inputs, process steps, outputs, customers, the measurement systems, and how the measurements are used to manage and improve the process. Report your findings as a document. Include these items:1. Company visited2. Process observed3. SIPOC elements4. Process measurements5. Process management systems used
Inferential Statistics test, QNT/561 week 5 assignment help
Create an inferential statistics (hypothesis) test usingthe research question and two variables your learning team develop ...
Inferential Statistics test, QNT/561 week 5 assignment help
Create an inferential statistics (hypothesis) test usingthe research question and two variables your learning team developed for the Week 2 Business Research Project Part 1 assignment. Include:The research questionMock data for the independent and dependent variablesDetermine the appropriate statistical tool to test the hypothesis based on the research question.Conduct a hypothesis test with a 95% confidence level, using the statistical tool.Writean interpretation of no more than 350-words of the results and provide your findings.Format your paper consistent with APA guidelines.Submit both the spreadsheet and the paper to the Assignment Files tab.
GCCCD Techniques for Developing Probability Model for Gosset Seed Plot Data Questions
ContextGosset's Seed Plot DataWilliam S. Gosset was employed by the Guinness brewing company of Dublin. Sample sizes avail ...
GCCCD Techniques for Developing Probability Model for Gosset Seed Plot Data Questions
ContextGosset's Seed Plot DataWilliam S. Gosset was employed by the Guinness brewing company of Dublin. Sample sizes available for experimentation in brewing were necessarily small. At that time, Gosset contacted a famous statistician Karl Pearson (1857-1936) and was told that there were no techniques for developing probability models for small data sets. Gosset studied under Pearson, and the outcome of his study was perhaps the most famous paper in statistical literature, "The Probable Error of a Mean" (1908), which introduced the T-distribution.Since Gosset was employed by Guinness, any work he produced would be owned by Guinness, so he published under a pseudonym, "Student"; hence, the T-distribution is often referred to as Student's T-distribution.To illustrate his analysis, Gosset used the results of seeding 11 different plots of land with two different types of seed: regular and kiln-dried. He wanted to determine if drying seeds before planting increased plant yield. Since different plots of soil may be naturally more fertile, this confounding variable was eliminated by using the matched pairs design and planting both types of seed in all 11 plots.The resulting data (corn yield in pounds per acre) are as follows.PlotRegular seedKiln-dried Seed11903200921935191531910201142496246352108218061961192572060212281444148291612154210131614431115111535We use these data to test the hypothesis that kiln-dried seed yields more corn than regular seed.Because of the nature of the experimental design (matched pairs), we are testing the difference in yield.PlotRegular seedKiln-dried SeedDifference119032009–10621935191520319102011–10142496246333521082180–7261961192536720602122–62814441482–38916121542701013161443–1271115111535–24Note that the differences were calculated: regular − kiln-dried.VariablesRegular seed: regular seeds that were traditionally used for plantingkiln-dried: seed that were kiln-dried before plantingDataDownload the seed (Links to an external site.) data file, and then upload the file into StatCrunch. PromptState the hypotheses and define the parameter.Checking conditions: Since Gosset invented the T-distribution, we will assume that his sample meets the conditions and proceed with the T-test. Regardless, answer these questions to demonstrate your understanding of the conditions for use of the T-model.But first you will need to review the dotplots for the data (opens in a new tab).
Which graph is used to check conditions? Why?What do we look for in the graph to verify that conditions are met?What else do we need to know about the sample of seeds before using the T-test?Use StatCrunch to find the T-score and the P-value. Hint: as you work through the StatCrunch directions, keep in mind that we want to calculate the differences as regular − kiln-dried . So you will choose Regular seed for Sample 1 and kiln-dried seed for Sample 2. (directions)Copy and paste the information in the StatCrunch output window into your initial post.State a conclusion based on the context of this scenario.
Linear Project, math homework help
For this assignment you will implement a project involving linear curve-fitting and interpretation. You will assess the ap ...
Linear Project, math homework help
For this assignment you will implement a project involving linear curve-fitting and interpretation. You will assess the appropriateness of a linear model, and explore the predictive power of the model. You will use appropriate technology to perform the modeling tasks.For this assignment, collect data exhibiting a relatively linear trend, find the line of best fit, plot the data and the line, interpret the slope, and use the linear equation to make a prediction. Also, find r2 (coefficient of determination) and r (correlation coefficient). Discuss your findings. Your topic may be that is related to sports, your work, a hobby, or something you find interesting. If you choose, you may use the suggestions described below. A Linear Model Example and Technology Tips are provided in separate documents.Tasks for Linear Regression Model (LR)(LR-1) Describe your topic, provide your data, and cite your source. Collect at least 8 data points. Label appropriately. (Highly recommended: Post this information in the Linear Model Project discussion as well as in your completed project. Include a brief informative description in the title of your posting. Each student must use different data.) The idea with the discussion posting is two-fold: (1) To share your interesting project idea with your classmates, and (2) To give me a chance to give you a brief thumbs-up or thumbs-down about your proposed topic and data. Sometimes students get off on the wrong foot or misunderstand the intent of the project, and your posting provides an opportunity for some feedback. Remark: Students may choose similar topics, but must have different data sets. For example, several students may be interested in a particular Olympic sport, and that is fine, but they must collect different data, perhaps from different events or different gender.(LR-2) Plot the points (x, y) to obtain a scatterplot. Use an appropriate scale on the horizontal and vertical axes and be sure to label carefully. Visually judge whether the data points exhibit a relatively linear trend. (If so, proceed. If not, try a different topic or data set.)(LR-3) Find the line of best fit (regression line) and graph it on the scatterplot. State the equation of the line.(LR-4) State the slope of the line of best fit. Carefully interpret the meaning of the slope in a sentence or two.(LR-5) Find and state the value of r2, the coefficient of determination, and r, the correlation coefficient. Discuss your findings in a few sentences. Is r positive or negative? Why? Is a line a good curve to fit to this data? Why or why not? Is the linear relationship very strong, moderately strong, weak, or nonexistent?(LR-6) Choose a value of interest and use the line of best fit to make an estimate or prediction. Show calculation work.(LR-7) Write a brief narrative of a paragraph or two. Summarize your findings and be sure to mention any aspect of the linear model project (topic, data, scatterplot, line, r, or estimate, etc.) that you found particularly important or interesting. You may submit all of your project in one document or a combination of documents, which may consist of word processing documents or spreadsheets or scanned handwritten work, provided it is clearly labeled where each task can be found. Be sure to include your name. Projects are graded on the basis of completeness, correctness, ease in locating all of the checklist items, and strength of the narrative portions.Here are some possible topics: Choose an Olympic sport -- an event that interests you. Go to http://www.databaseolympics.com/ and collect data for winners in the event for at least 8 Olympic games (dating back to at least 1980). (Example: Winning times in Men's 400 m dash). Make a quick plot for yourself to "eyeball" whether the data points exhibit a relatively linear trend. (If so, proceed. If not, try a different event.) After you find the line of best fit, use your line to make a prediction for the next Olympics (2014 for a winter event, 2016 for a summer event ).Choose a particular type of food. (Examples: Fish sandwich at fast-food chains, cheese pizza, breakfast cereal) For at least 8 brands, look up the fat content and the associated calorie total per serving. Make a quick plot for yourself to "eyeball" whether the data exhibit a relatively linear trend. (If so, proceed. If not, try a different type of food.) After you find the line of best fit, use your line to make a prediction corresponding to a fat amount not occurring in your data set.) Alternative: Look up carbohydrate content and associated calorie total per serving.Choose a sport that particularly interests you and find two variables that may exhibit a linear relationship. For instance, for each team for a particular season in baseball, find the total runs scored and the number of wins. Excellent websites: http://www.databasesports.com/ and http://www.baseball-reference.com/
Northern Star Online Tree Diagrams and Probability Models Analysis Paper
Exercises 2.4 Complete problems #1 and #7. Show work. For problem #1, you should have four outcomes in your tree diagr ...
Northern Star Online Tree Diagrams and Probability Models Analysis Paper
Exercises 2.4 Complete problems #1 and #7. Show work. For problem #1, you should have four outcomes in your tree diagram but only three outcomes listed in your probability model (two outcomes are the same). For problem #7, you should have 8 outcomes in your tree diagram but only four outcomes in your probability model (some outcomes are technically the same). Be sure that you create a tree diagram for each problem.Label the each diagram correctly (with both titles & probabilities)Include a probability model for each problem.Round decimals to three places in your probability models.1. Fourteen red marbles and sixteen green marbles are in a bag. Two marbles are picked out one at a time and replaced after they are picked. Build a tree diagram and probability model to show the different combinations of marbles that could be pulled out of the bag.7. A baseball player is a .400 hitter. This means that he gets a hit (single, double, triple, or home run) 40% of the time he has an at-bat. Use a tree diagram to build a probability model that shows the probability of the player having 0, 1, 2, or 3 hits if he has 3 at-bats in one game.
Similar Content
Algebra Question
simpliffy radical expressions...
Academy of Chinese Culture and Health Sciences Simple Statistics Questionnaire
1. If the standard deviation (s) of one group is 3.8 and for a second group s = 2.3, which group is more homogeneous?2. Wi...
Recursions and Pigeonhole Problems in Discrete Math Questions
Hi Paola! It's me again. Looking to you because I need help with Recursion, explicit formula, pigeonholes, etc. Hope you g...
Related Tags
Book Guides
Get 24/7
Homework help
Our tutors provide high quality explanations & answers.
Post question
Most Popular Content
2 pages
Chi Squared
1. A Chi-square test is used to determine if there is a statistically significant difference between groups of a categoric ...
Chi Squared
1. A Chi-square test is used to determine if there is a statistically significant difference between groups of a categorical variable. It can be used ...
Strayer University Week 3 SIPOC Elements & Process Measurements Paper 3
Homework Assignment 3Due in Week 3 and worth 30 pointsTouring a Process. Select a place of your choice (e.g. supermarket, ...
Strayer University Week 3 SIPOC Elements & Process Measurements Paper 3
Homework Assignment 3Due in Week 3 and worth 30 pointsTouring a Process. Select a place of your choice (e.g. supermarket, doctor’s office, library, Post Office, department store, etc.) and observe one or more key processes, the associated suppliers, inputs, process steps, outputs, customers, the measurement systems, and how the measurements are used to manage and improve the process. Report your findings as a document. Include these items:1. Company visited2. Process observed3. SIPOC elements4. Process measurements5. Process management systems used
Inferential Statistics test, QNT/561 week 5 assignment help
Create an inferential statistics (hypothesis) test usingthe research question and two variables your learning team develop ...
Inferential Statistics test, QNT/561 week 5 assignment help
Create an inferential statistics (hypothesis) test usingthe research question and two variables your learning team developed for the Week 2 Business Research Project Part 1 assignment. Include:The research questionMock data for the independent and dependent variablesDetermine the appropriate statistical tool to test the hypothesis based on the research question.Conduct a hypothesis test with a 95% confidence level, using the statistical tool.Writean interpretation of no more than 350-words of the results and provide your findings.Format your paper consistent with APA guidelines.Submit both the spreadsheet and the paper to the Assignment Files tab.
GCCCD Techniques for Developing Probability Model for Gosset Seed Plot Data Questions
ContextGosset's Seed Plot DataWilliam S. Gosset was employed by the Guinness brewing company of Dublin. Sample sizes avail ...
GCCCD Techniques for Developing Probability Model for Gosset Seed Plot Data Questions
ContextGosset's Seed Plot DataWilliam S. Gosset was employed by the Guinness brewing company of Dublin. Sample sizes available for experimentation in brewing were necessarily small. At that time, Gosset contacted a famous statistician Karl Pearson (1857-1936) and was told that there were no techniques for developing probability models for small data sets. Gosset studied under Pearson, and the outcome of his study was perhaps the most famous paper in statistical literature, "The Probable Error of a Mean" (1908), which introduced the T-distribution.Since Gosset was employed by Guinness, any work he produced would be owned by Guinness, so he published under a pseudonym, "Student"; hence, the T-distribution is often referred to as Student's T-distribution.To illustrate his analysis, Gosset used the results of seeding 11 different plots of land with two different types of seed: regular and kiln-dried. He wanted to determine if drying seeds before planting increased plant yield. Since different plots of soil may be naturally more fertile, this confounding variable was eliminated by using the matched pairs design and planting both types of seed in all 11 plots.The resulting data (corn yield in pounds per acre) are as follows.PlotRegular seedKiln-dried Seed11903200921935191531910201142496246352108218061961192572060212281444148291612154210131614431115111535We use these data to test the hypothesis that kiln-dried seed yields more corn than regular seed.Because of the nature of the experimental design (matched pairs), we are testing the difference in yield.PlotRegular seedKiln-dried SeedDifference119032009–10621935191520319102011–10142496246333521082180–7261961192536720602122–62814441482–38916121542701013161443–1271115111535–24Note that the differences were calculated: regular − kiln-dried.VariablesRegular seed: regular seeds that were traditionally used for plantingkiln-dried: seed that were kiln-dried before plantingDataDownload the seed (Links to an external site.) data file, and then upload the file into StatCrunch. PromptState the hypotheses and define the parameter.Checking conditions: Since Gosset invented the T-distribution, we will assume that his sample meets the conditions and proceed with the T-test. Regardless, answer these questions to demonstrate your understanding of the conditions for use of the T-model.But first you will need to review the dotplots for the data (opens in a new tab).
Which graph is used to check conditions? Why?What do we look for in the graph to verify that conditions are met?What else do we need to know about the sample of seeds before using the T-test?Use StatCrunch to find the T-score and the P-value. Hint: as you work through the StatCrunch directions, keep in mind that we want to calculate the differences as regular − kiln-dried . So you will choose Regular seed for Sample 1 and kiln-dried seed for Sample 2. (directions)Copy and paste the information in the StatCrunch output window into your initial post.State a conclusion based on the context of this scenario.
Linear Project, math homework help
For this assignment you will implement a project involving linear curve-fitting and interpretation. You will assess the ap ...
Linear Project, math homework help
For this assignment you will implement a project involving linear curve-fitting and interpretation. You will assess the appropriateness of a linear model, and explore the predictive power of the model. You will use appropriate technology to perform the modeling tasks.For this assignment, collect data exhibiting a relatively linear trend, find the line of best fit, plot the data and the line, interpret the slope, and use the linear equation to make a prediction. Also, find r2 (coefficient of determination) and r (correlation coefficient). Discuss your findings. Your topic may be that is related to sports, your work, a hobby, or something you find interesting. If you choose, you may use the suggestions described below. A Linear Model Example and Technology Tips are provided in separate documents.Tasks for Linear Regression Model (LR)(LR-1) Describe your topic, provide your data, and cite your source. Collect at least 8 data points. Label appropriately. (Highly recommended: Post this information in the Linear Model Project discussion as well as in your completed project. Include a brief informative description in the title of your posting. Each student must use different data.) The idea with the discussion posting is two-fold: (1) To share your interesting project idea with your classmates, and (2) To give me a chance to give you a brief thumbs-up or thumbs-down about your proposed topic and data. Sometimes students get off on the wrong foot or misunderstand the intent of the project, and your posting provides an opportunity for some feedback. Remark: Students may choose similar topics, but must have different data sets. For example, several students may be interested in a particular Olympic sport, and that is fine, but they must collect different data, perhaps from different events or different gender.(LR-2) Plot the points (x, y) to obtain a scatterplot. Use an appropriate scale on the horizontal and vertical axes and be sure to label carefully. Visually judge whether the data points exhibit a relatively linear trend. (If so, proceed. If not, try a different topic or data set.)(LR-3) Find the line of best fit (regression line) and graph it on the scatterplot. State the equation of the line.(LR-4) State the slope of the line of best fit. Carefully interpret the meaning of the slope in a sentence or two.(LR-5) Find and state the value of r2, the coefficient of determination, and r, the correlation coefficient. Discuss your findings in a few sentences. Is r positive or negative? Why? Is a line a good curve to fit to this data? Why or why not? Is the linear relationship very strong, moderately strong, weak, or nonexistent?(LR-6) Choose a value of interest and use the line of best fit to make an estimate or prediction. Show calculation work.(LR-7) Write a brief narrative of a paragraph or two. Summarize your findings and be sure to mention any aspect of the linear model project (topic, data, scatterplot, line, r, or estimate, etc.) that you found particularly important or interesting. You may submit all of your project in one document or a combination of documents, which may consist of word processing documents or spreadsheets or scanned handwritten work, provided it is clearly labeled where each task can be found. Be sure to include your name. Projects are graded on the basis of completeness, correctness, ease in locating all of the checklist items, and strength of the narrative portions.Here are some possible topics: Choose an Olympic sport -- an event that interests you. Go to http://www.databaseolympics.com/ and collect data for winners in the event for at least 8 Olympic games (dating back to at least 1980). (Example: Winning times in Men's 400 m dash). Make a quick plot for yourself to "eyeball" whether the data points exhibit a relatively linear trend. (If so, proceed. If not, try a different event.) After you find the line of best fit, use your line to make a prediction for the next Olympics (2014 for a winter event, 2016 for a summer event ).Choose a particular type of food. (Examples: Fish sandwich at fast-food chains, cheese pizza, breakfast cereal) For at least 8 brands, look up the fat content and the associated calorie total per serving. Make a quick plot for yourself to "eyeball" whether the data exhibit a relatively linear trend. (If so, proceed. If not, try a different type of food.) After you find the line of best fit, use your line to make a prediction corresponding to a fat amount not occurring in your data set.) Alternative: Look up carbohydrate content and associated calorie total per serving.Choose a sport that particularly interests you and find two variables that may exhibit a linear relationship. For instance, for each team for a particular season in baseball, find the total runs scored and the number of wins. Excellent websites: http://www.databasesports.com/ and http://www.baseball-reference.com/
Northern Star Online Tree Diagrams and Probability Models Analysis Paper
Exercises 2.4 Complete problems #1 and #7. Show work. For problem #1, you should have four outcomes in your tree diagr ...
Northern Star Online Tree Diagrams and Probability Models Analysis Paper
Exercises 2.4 Complete problems #1 and #7. Show work. For problem #1, you should have four outcomes in your tree diagram but only three outcomes listed in your probability model (two outcomes are the same). For problem #7, you should have 8 outcomes in your tree diagram but only four outcomes in your probability model (some outcomes are technically the same). Be sure that you create a tree diagram for each problem.Label the each diagram correctly (with both titles & probabilities)Include a probability model for each problem.Round decimals to three places in your probability models.1. Fourteen red marbles and sixteen green marbles are in a bag. Two marbles are picked out one at a time and replaced after they are picked. Build a tree diagram and probability model to show the different combinations of marbles that could be pulled out of the bag.7. A baseball player is a .400 hitter. This means that he gets a hit (single, double, triple, or home run) 40% of the time he has an at-bat. Use a tree diagram to build a probability model that shows the probability of the player having 0, 1, 2, or 3 hits if he has 3 at-bats in one game.
Earn money selling
your Study Documents