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Updated Stat Assignment 4
Note: You are required to fill your full name, ID and CRN. 1. Find the best predicted systolic blood pressure in the left ...
Updated Stat Assignment 4
Note: You are required to fill your full name, ID and CRN. 1. Find the best predicted systolic blood pressure in the left arm given that the systolic
2 pages
Analysis Tally Results 1
1. Please calculate descriptive statistics on the following quantitative numbers AND create either a bar chart, stem and l ...
Analysis Tally Results 1
1. Please calculate descriptive statistics on the following quantitative numbers AND create either a bar chart, stem and leaf plot, or frequency table ...
MAT 243 SNHU Python Scripts for the Module Six And Python Script Discussion
DISCUSSION 1: In this discussion you will be interpreting output from your Python Scripts for the Module Six Discussion. I ...
MAT 243 SNHU Python Scripts for the Module Six And Python Script Discussion
DISCUSSION 1: In this discussion you will be interpreting output from your Python Scripts for the Module Six Discussion. If you did not complete the Module Six discussion, please complete that before working on this assignment.Last week’s discussion involved development of a multiple regression model that used miles per gallon as a response variable. Weight and horsepower were predictor variables. You performed an overall F-test to evaluate the significance of your model. This week, you will evaluate the significance of individual predictors. You will use output of Python script from Module Six to perform individual t-tests for each predictor variable. Specifically, you will look at Step 5 of the Python script to answer all questions in the discussion this week.In your initial post, address the following items:Is at least one of the two variables (weight and horsepower) significant in the model? Run the overall F-test and provide your interpretation at 5% level of significance. See Step 5 in the Python script. Include the following in your analysis:Define the null and alternative hypothesis in mathematical terms and in words.Report the level of significance.Include the test statistic and the P-value. (Hint: F-Statistic and Prob (F-Statistic) in the output).Provide your conclusion and interpretation of the test. Should the null hypothesis be rejected? Why or why not?What is the slope coefficient for the weight variable? Is this coefficient significant at 5% level of significance (alpha=0.05)? (Hint: Check the P-value, , for weight in Python output. Recall that this is the individual t-test for the beta parameter.) See Step 5 in the Python script.What is the slope coefficient for the horsepower variable? Is this coefficient significant at 5% level of significance (alpha=0.05)? (Hint: Check the P-value, , for horsepower in Python output. Recall that this is the individual t-test for the beta parameter.) See Step 5 in the Python script.What is the purpose of performing individual t-tests after carrying out the overall F-test? What are the differences in the interpretation of the two tests?What is the coefficient of determination of your multiple regression model from Module Six? Provide appropriate interpretation of this statistic. Be sure to clearly communicate your ideas using appropriate terminology. DISCUSSION 2Use the link in the Jupyter Notebook activity to access your MODULE 8 DISCUSSION Python script. In this discussion, you will apply the statistical concepts and techniques covered in this week's reading about one-way analysis of variance (ANOVA). An investment analyst is evaluating the 10-year mean return on investment for industry-specific exchange-traded funds (ETFs) for three sectors: financial, energy, and technology. The analyst obtains a random sample of 30 ETFs for each sector and calculates the 10-year return of each ETF. The analyst has provided you with this data set. Run Step 1 in the Python script to upload the data file.Using the sample data, perform one-way analysis of variance (ANOVA). Evaluate whether the average return of at least one of the industry-specific ETFs is significantly different. Use a 5% level of significance.In your initial post, address the following items:Define the null and alternative hypothesis in mathematical terms and in words.Report the level of significance.Include the test statistic and the P-value. See Step 2 in the Python script.Provide your conclusion and interpretation of the test. Should the null hypothesis be rejected? Why or why not?Does a side-by-side boxplot of the 10-year returns of ETFs from the three sectors confirm your conclusion of the hypothesis test? Why or why not? See Step 3 in the Python script.Finally, be sure to review the Discussion Rubric (ATTACHED) to understand how you will be graded on this assignment.
9 pages
Cryptography
Judson summarizes the definition of cryptography as the “study of sending and receiving secret messages” (Ch.7). Crypt ...
Cryptography
Judson summarizes the definition of cryptography as the “study of sending and receiving secret messages” (Ch.7). Cryptographic ciphers/algorithms ...
Need algebra help for Solving systems of equations
1. Complete the table below to solve the equation 2.5x – 10.5 = 64(0.5x).2. A newspaper started an online version of its ...
Need algebra help for Solving systems of equations
1. Complete the table below to solve the equation 2.5x – 10.5 = 64(0.5x).2. A newspaper started an online version of its paper 14 years ago. In a recent presentation to stockholders, the lead marketing executive states that the revenues for online ads have more than doubled that of the revenues for printed ads since starting the online version of the paper. Use the graph below to justify the lead executive’s statement and to determine the approximate year that the two ad revenues were equal.3. Two ocean beaches are being affected by erosion. The table shows the width, in feet, of each beach at high tide measured where 1995 is represented by year 0. A Describe the patterns shown by the erosion data measurements shown for each of the beaches in the tableB Between which years will the beaches have approximately the same width?C Assuming these rates remain constant, what can you do to get a better approximation of when the two beaches will have the same width?4. A wooded area in a state park has a mixture of different types of trees. There are 800 pine trees and 50 oak trees. The number of pine trees is decreasing at a rate of 5% per year. The number of oak trees is increasing at a rate of 15% per year. If these trends continue:A Write two functions to model this situation, and graph those two functions on the same coordinate grid.B During what year in the future will the park have approximately the same number of pine and oak trees? C How many of each type of tree will there be at that time?
MATH 107 UMGC Wk 5 College Algebra Linear Model Example & Technology Tips Essay
Curve-fitting Project - Linear Model (due at the end of Week 5)InstructionsFor this assignment, collect data exhibiting a ...
MATH 107 UMGC Wk 5 College Algebra Linear Model Example & Technology Tips Essay
Curve-fitting Project - Linear Model (due at the end of Week 5)InstructionsFor 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. 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.
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8 pages
Updated Stat Assignment 4
Note: You are required to fill your full name, ID and CRN. 1. Find the best predicted systolic blood pressure in the left ...
Updated Stat Assignment 4
Note: You are required to fill your full name, ID and CRN. 1. Find the best predicted systolic blood pressure in the left arm given that the systolic
2 pages
Analysis Tally Results 1
1. Please calculate descriptive statistics on the following quantitative numbers AND create either a bar chart, stem and l ...
Analysis Tally Results 1
1. Please calculate descriptive statistics on the following quantitative numbers AND create either a bar chart, stem and leaf plot, or frequency table ...
MAT 243 SNHU Python Scripts for the Module Six And Python Script Discussion
DISCUSSION 1: In this discussion you will be interpreting output from your Python Scripts for the Module Six Discussion. I ...
MAT 243 SNHU Python Scripts for the Module Six And Python Script Discussion
DISCUSSION 1: In this discussion you will be interpreting output from your Python Scripts for the Module Six Discussion. If you did not complete the Module Six discussion, please complete that before working on this assignment.Last week’s discussion involved development of a multiple regression model that used miles per gallon as a response variable. Weight and horsepower were predictor variables. You performed an overall F-test to evaluate the significance of your model. This week, you will evaluate the significance of individual predictors. You will use output of Python script from Module Six to perform individual t-tests for each predictor variable. Specifically, you will look at Step 5 of the Python script to answer all questions in the discussion this week.In your initial post, address the following items:Is at least one of the two variables (weight and horsepower) significant in the model? Run the overall F-test and provide your interpretation at 5% level of significance. See Step 5 in the Python script. Include the following in your analysis:Define the null and alternative hypothesis in mathematical terms and in words.Report the level of significance.Include the test statistic and the P-value. (Hint: F-Statistic and Prob (F-Statistic) in the output).Provide your conclusion and interpretation of the test. Should the null hypothesis be rejected? Why or why not?What is the slope coefficient for the weight variable? Is this coefficient significant at 5% level of significance (alpha=0.05)? (Hint: Check the P-value, , for weight in Python output. Recall that this is the individual t-test for the beta parameter.) See Step 5 in the Python script.What is the slope coefficient for the horsepower variable? Is this coefficient significant at 5% level of significance (alpha=0.05)? (Hint: Check the P-value, , for horsepower in Python output. Recall that this is the individual t-test for the beta parameter.) See Step 5 in the Python script.What is the purpose of performing individual t-tests after carrying out the overall F-test? What are the differences in the interpretation of the two tests?What is the coefficient of determination of your multiple regression model from Module Six? Provide appropriate interpretation of this statistic. Be sure to clearly communicate your ideas using appropriate terminology. DISCUSSION 2Use the link in the Jupyter Notebook activity to access your MODULE 8 DISCUSSION Python script. In this discussion, you will apply the statistical concepts and techniques covered in this week's reading about one-way analysis of variance (ANOVA). An investment analyst is evaluating the 10-year mean return on investment for industry-specific exchange-traded funds (ETFs) for three sectors: financial, energy, and technology. The analyst obtains a random sample of 30 ETFs for each sector and calculates the 10-year return of each ETF. The analyst has provided you with this data set. Run Step 1 in the Python script to upload the data file.Using the sample data, perform one-way analysis of variance (ANOVA). Evaluate whether the average return of at least one of the industry-specific ETFs is significantly different. Use a 5% level of significance.In your initial post, address the following items:Define the null and alternative hypothesis in mathematical terms and in words.Report the level of significance.Include the test statistic and the P-value. See Step 2 in the Python script.Provide your conclusion and interpretation of the test. Should the null hypothesis be rejected? Why or why not?Does a side-by-side boxplot of the 10-year returns of ETFs from the three sectors confirm your conclusion of the hypothesis test? Why or why not? See Step 3 in the Python script.Finally, be sure to review the Discussion Rubric (ATTACHED) to understand how you will be graded on this assignment.
9 pages
Cryptography
Judson summarizes the definition of cryptography as the “study of sending and receiving secret messages” (Ch.7). Crypt ...
Cryptography
Judson summarizes the definition of cryptography as the “study of sending and receiving secret messages” (Ch.7). Cryptographic ciphers/algorithms ...
Need algebra help for Solving systems of equations
1. Complete the table below to solve the equation 2.5x – 10.5 = 64(0.5x).2. A newspaper started an online version of its ...
Need algebra help for Solving systems of equations
1. Complete the table below to solve the equation 2.5x – 10.5 = 64(0.5x).2. A newspaper started an online version of its paper 14 years ago. In a recent presentation to stockholders, the lead marketing executive states that the revenues for online ads have more than doubled that of the revenues for printed ads since starting the online version of the paper. Use the graph below to justify the lead executive’s statement and to determine the approximate year that the two ad revenues were equal.3. Two ocean beaches are being affected by erosion. The table shows the width, in feet, of each beach at high tide measured where 1995 is represented by year 0. A Describe the patterns shown by the erosion data measurements shown for each of the beaches in the tableB Between which years will the beaches have approximately the same width?C Assuming these rates remain constant, what can you do to get a better approximation of when the two beaches will have the same width?4. A wooded area in a state park has a mixture of different types of trees. There are 800 pine trees and 50 oak trees. The number of pine trees is decreasing at a rate of 5% per year. The number of oak trees is increasing at a rate of 15% per year. If these trends continue:A Write two functions to model this situation, and graph those two functions on the same coordinate grid.B During what year in the future will the park have approximately the same number of pine and oak trees? C How many of each type of tree will there be at that time?
MATH 107 UMGC Wk 5 College Algebra Linear Model Example & Technology Tips Essay
Curve-fitting Project - Linear Model (due at the end of Week 5)InstructionsFor this assignment, collect data exhibiting a ...
MATH 107 UMGC Wk 5 College Algebra Linear Model Example & Technology Tips Essay
Curve-fitting Project - Linear Model (due at the end of Week 5)InstructionsFor 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. 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.
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