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2 pages

Statistics Question

1. Tell me what would happen to the mean, median and mode values for Friday night (that you calculated for your individual ...

Statistics Question

1. Tell me what would happen to the mean, median and mode values for Friday night (that you calculated for your individual Assignment) if I added a ...

MAT 154 Grand Canyon University Modeling a Problem Statistics Project

: Consider one way of modeling a problem. Say you have a device an in any given year there is about a 1 in 6 chance that t ...

MAT 154 Grand Canyon University Modeling a Problem Statistics Project

: Consider one way of modeling a problem. Say you have a device an in any given year there is about a 1 in 6 chance that the device will fail. A question is, “On average, how long will it be before such a device fails?” This sort of problem is what will be modeled and analyzed here.

7 pages

Linear Algebra Factorization And Eigenvectors

i.e., (1-x)*[(4-x)*(9-x)-6*6]-2*[2*(9-x)-6*3]+3*[2*6-3*(4-x)] = 0 i.e., (1-x)*[36-13x+x2-36]-2*[18-2x-18]+3*[12-12+3x] = 0

Linear Algebra Factorization And Eigenvectors

i.e., (1-x)*[(4-x)*(9-x)-6*6]-2*[2*(9-x)-6*3]+3*[2*6-3*(4-x)] = 0 i.e., (1-x)*[36-13x+x2-36]-2*[18-2x-18]+3*[12-12+3x] = 0

MTH 245 George Mason High School Exploratory Data Analysis Project

Purpose:
This project is to help you apply concepts to real world, real data analysis. In the real-world computers do most ...

MTH 245 George Mason High School Exploratory Data Analysis Project

Purpose:
This project is to help you apply concepts to real world, real data analysis. In the real-world computers do most of the hard work for statisticians. This project will help you understand how an informative decision is made using data analysis. After completing this project, you should be able to determine which statistical procedures are appropriate; use StatCrunch to carry out the procedures and interpret the output
The Database of UVA (Excel file) students contains information on the undergraduate students at University of Virginia. This list contains the data for different Qualitative and Quantitative variable. Your project is to obtain the results based on the following questions using StatCrunch. Copy the StatCrunch results (graph plus answer) into summary document using the guidelines in section C.
Directions:
Do all of the work below with the Database of MATH ACT SCORES Download MATH ACT SCORES
Data: The Data set is on the project page on canvas(MATH ACT SCORES). Use StatCrunch to obtain results for the following questions.
A) Exploratory Data Analysis
Obtain the mean and standard deviation for ACT Math scores for each class level (freshmen, sophomores, juniors, seniors) and interpret the results
Obtain the five number summary of ACT Math score for each class levels. Do any of these class levels have outliers?
Construct a boxplot and use it to investigate the data for outliers
Construct a histogram, and normal probability plot (QQ Plot) for ACT Math score for each class level.
B) Inferential Statistics
Construct and interpret a 95% confidence interval for µ, for the mean ACT Math score for each class level.
Using regression analysis (hint, use scatter plot, r, r2 ) , investigate if there is a relationship between Age and performance in ACT Math score.; . provide an equation can be used to predict ACT math score based on age,
Write a Summary and Findings of the Project
C) Write-up
Write a brief introduction of the project.
o Interpret the mean, and standard deviation in context of the data given.
o Compare the measures of center and comment on which measure of center would best describe the data given.
o Comment on the shape of the distribution, which class level appears to be more approximately normal
o Are there any outliers in the data? Include results of your investigation for outliers. Identify which class level has an outlier
o Comment on your assessment of normality.
o Which test will be most appropriate for the inferential statistics (confidence Interval)? Z-test or t-test? Why?
o Write an interpretation for the confidence interval estimate in context of the data.
o State the summary, interpretation and conclusion of your Investigation if there is a relationship between Age and performance in ACT Math score of undergraduate student at UVA.; Provide an equation can be used to predict ACT math score based on age; how reliable would the prediction be?

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/

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Most Popular Content

2 pages

Statistics Question

1. Tell me what would happen to the mean, median and mode values for Friday night (that you calculated for your individual ...

Statistics Question

1. Tell me what would happen to the mean, median and mode values for Friday night (that you calculated for your individual Assignment) if I added a ...

MAT 154 Grand Canyon University Modeling a Problem Statistics Project

: Consider one way of modeling a problem. Say you have a device an in any given year there is about a 1 in 6 chance that t ...

MAT 154 Grand Canyon University Modeling a Problem Statistics Project

: Consider one way of modeling a problem. Say you have a device an in any given year there is about a 1 in 6 chance that the device will fail. A question is, “On average, how long will it be before such a device fails?” This sort of problem is what will be modeled and analyzed here.

7 pages

Linear Algebra Factorization And Eigenvectors

i.e., (1-x)*[(4-x)*(9-x)-6*6]-2*[2*(9-x)-6*3]+3*[2*6-3*(4-x)] = 0 i.e., (1-x)*[36-13x+x2-36]-2*[18-2x-18]+3*[12-12+3x] = 0

Linear Algebra Factorization And Eigenvectors

MTH 245 George Mason High School Exploratory Data Analysis Project

Purpose:
This project is to help you apply concepts to real world, real data analysis. In the real-world computers do most ...

MTH 245 George Mason High School Exploratory Data Analysis Project

Purpose:
This project is to help you apply concepts to real world, real data analysis. In the real-world computers do most of the hard work for statisticians. This project will help you understand how an informative decision is made using data analysis. After completing this project, you should be able to determine which statistical procedures are appropriate; use StatCrunch to carry out the procedures and interpret the output
The Database of UVA (Excel file) students contains information on the undergraduate students at University of Virginia. This list contains the data for different Qualitative and Quantitative variable. Your project is to obtain the results based on the following questions using StatCrunch. Copy the StatCrunch results (graph plus answer) into summary document using the guidelines in section C.
Directions:
Do all of the work below with the Database of MATH ACT SCORES Download MATH ACT SCORES
Data: The Data set is on the project page on canvas(MATH ACT SCORES). Use StatCrunch to obtain results for the following questions.
A) Exploratory Data Analysis
Obtain the mean and standard deviation for ACT Math scores for each class level (freshmen, sophomores, juniors, seniors) and interpret the results
Obtain the five number summary of ACT Math score for each class levels. Do any of these class levels have outliers?
Construct a boxplot and use it to investigate the data for outliers
Construct a histogram, and normal probability plot (QQ Plot) for ACT Math score for each class level.
B) Inferential Statistics
Construct and interpret a 95% confidence interval for µ, for the mean ACT Math score for each class level.
Using regression analysis (hint, use scatter plot, r, r2 ) , investigate if there is a relationship between Age and performance in ACT Math score.; . provide an equation can be used to predict ACT math score based on age,
Write a Summary and Findings of the Project
C) Write-up
Write a brief introduction of the project.
o Interpret the mean, and standard deviation in context of the data given.
o Compare the measures of center and comment on which measure of center would best describe the data given.
o Comment on the shape of the distribution, which class level appears to be more approximately normal
o Are there any outliers in the data? Include results of your investigation for outliers. Identify which class level has an outlier
o Comment on your assessment of normality.
o Which test will be most appropriate for the inferential statistics (confidence Interval)? Z-test or t-test? Why?
o Write an interpretation for the confidence interval estimate in context of the data.
o State the summary, interpretation and conclusion of your Investigation if there is a relationship between Age and performance in ACT Math score of undergraduate student at UVA.; Provide an equation can be used to predict ACT math score based on age; how reliable would the prediction be?

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/

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