My Blog

Category: Mathematics

  • [Solved] MA 2025 MOD 1 ASSN

    ✓ Verified Academic Solution Available

    Executive Solution Overview

    **Overview:** For this assignment, you will utilize statistical technology to work with a series of datasets. You are welcome to use the technology of your choice including Excel, Desmos, and Google Sheets. Please follow the instructions below. Once you have completed the assignment, submit your com…

    Instant Solution Download

    $6.99

    Immediate access to the full model answer, formatted citations, and rubric breakdown.

    Need a Fresh Custom Paper?

    Have this question answered from scratch according to your specific instructions and deadline.

    Order on TutorsGallery →

    Assignment Prompt & Instructions

    **Overview:**

    For this assignment, you will utilize statistical technology to work with a series of datasets. You are welcome to use the technology of your choice including Excel, Desmos, and Google Sheets.  Please follow the instructions below. Once you have completed the assignment, submit your completed document (in .docx or .doc format) using the Submission Link.

    **Instructions:**

    1. Download the file attached to this assignment. This file contains three questions.
    2. Copy and paste the graphs and charts for your answers into the document.
    3. Type your responses to the other questions.
    4. All of your charts, graphs, and responses to questions should be submitted in a single document.

    If you have any questions, please ask your professor.

    [MA 2025 Module 1 Statistics and Technology Assignmen](https://indianatech.instructure.com/courses/22511/files/3896730?wrap=1)

    – [\
    \
    MA2025Module1ASSNINFO2025.docx](https://www.sweetstudy.com/files/ma2025module1assninfo2025-docx "MA2025Module1ASSNINFO2025.docx")

    – a year ago

  • [Solved] Quantitative Reasoning

    ✓ Verified Academic Solution Available

    Executive Solution Overview

    [>Probability homework help](https://www.sweetstudy.com/fields/mathematics-probability) **Instructions:** Show your work or explain in detail how you arrived at your answers. You will upload a separate Excel for the assignment. **EXCEL FILE** The monthly expenditures of four employees at a paper mil…

    Instant Solution Download

    $6.99

    Immediate access to the full model answer, formatted citations, and rubric breakdown.

    Need a Fresh Custom Paper?

    Have this question answered from scratch according to your specific instructions and deadline.

    Order on TutorsGallery →

    Assignment Prompt & Instructions

    [>Probability homework help](https://www.sweetstudy.com/fields/mathematics-probability)

    **Instructions:** Show your work or explain in detail how you arrived at your answers. You will upload a separate Excel for the assignment.

    **EXCEL FILE**

    The monthly expenditures of four employees at a paper mill are shown in the table below. Assume all their monthly income is accounted for. All amounts are in dollars.

    You will use Excel to create a statistical presentation of this data.

    1. Open the attached spreadsheet.
    2. Use Excel’s calculation functions to determine the mean amount all four men spent on each category. ( _Hint: Click in the cell you want the answer to appear. Then click on the Formulas tab, then More Functions > Statistical. Select AVERAGE then select the cells you want to average together. Repeat this process for each category)._
    3. Use Excel’s calculation functions to determine the median amount spent on each category.
    4. Use Excel’s calculation functions to determine the standard deviation in amounts for each category. ( _Hint: Use the STDEVA function)._
    5. Create a pie chart showing what percent of his monthly budget John spends on each category. Be sure to include category labels with percentages. ( _Hint: Select the categories and data, then click on the Insert tab. Select the 2-D pie chart. To add labels, click on your pie chart and click the “+” symbol. Then check “Data Labels” and select “Data Callout_”)
    6. Browse around and scroll through all the different functions available in Excel. Were there functions you may have never seen before that you are now familiar with? Can you think of a situation where the functions and graphing capabilities of Excel would be useful to you in your life or career?

    – [\
    \
    Screenshot2025-04-25081957.png](https://www.sweetstudy.com/files/screenshot2025-04-25081957-png "Screenshot2025-04-25081957.png")
    – [\
    \
    QLWeekEOWData.xlsx](https://www.sweetstudy.com/files/qlweekeowdata-xlsx "QLWeekEOWData.xlsx")

    – a year ago

  • [Solved] Help understanding real world math

    ✓ Verified Academic Solution Available

    Executive Solution Overview

    In-depth study guidance and analytical solution covering Help understanding real world math.

    Instant Solution Download

    $6.99

    Immediate access to the full model answer, formatted citations, and rubric breakdown.

    Need a Fresh Custom Paper?

    Have this question answered from scratch according to your specific instructions and deadline.

    Order on TutorsGallery →

    Assignment Prompt & Instructions

    Full assignment prompt and step-by-step guidance are included in the downloadable solution file.

  • [Solved] Business Statistics Project

    ✓ Verified Academic Solution Available

    Executive Solution Overview

    [>Statistics homework help](https://www.sweetstudy.com/fields/mathematics-statistics) See attached files. – a year ago **files (2)** – ## ProjectTemplate.docx – ## crime.csv **## ProjectTemplate.docx** ### 1. Introduction _Discuss the statement of the problem in terms of the statistical analyses th…

    Instant Solution Download

    $6.99

    Immediate access to the full model answer, formatted citations, and rubric breakdown.

    Need a Fresh Custom Paper?

    Have this question answered from scratch according to your specific instructions and deadline.

    Order on TutorsGallery →

    Assignment Prompt & Instructions

    [>Statistics homework help](https://www.sweetstudy.com/fields/mathematics-statistics)

    See attached files.

    – a year ago

    **files (2)**

    – ## ProjectTemplate.docx

    – ## crime.csv

    **## ProjectTemplate.docx**

    ### 1. Introduction

    _Discuss the statement of the problem in terms of the statistical analyses that are being performed. Be sure to address the following:_

    What is the data set that you are exploring?

    How will your results be used?

    What type of analyses will you be running in this project? Explain.

    _![](https://www.sweetstudy.com/questions/business-statistics-project-20902291) Answer the questions in a paragraph response. Remove all questions and this note before submitting! Do not include R/Excel code in your report._

    ### 2. Data Preparation

    1. What are the variables stored in crime.csv?

    2.
    **Give an overall description about your data set.**

    _![](https://www.sweetstudy.com/questions/business-statistics-project-20902291) Answer the questions in a paragraph response. Remove all questions and this note before submitting! Do not include R/Excel code in your report._

    ### 3. Simple Linear Regression: Create a simple linear regression model to predict the murder rate using single.parent.

    In general, how is a simple linear regression model used to predict the response variable using the predictor variable?

    Why you decide to use linear regression for this data set? Justify your option.

    What is the equation for your model?

    Report the P-value in a formatted table as shown below:

    | | |
    | — | — |
    | **Statistic** | **Value** |
    | P-value | X.XXXX<br>_*Round off to 4 decimal places._ |

    What is the predicted murder rate for a state that has single.paren of 25.4? Round your answer down to the nearest integer.

    _![](https://www.sweetstudy.com/questions/business-statistics-project-20902291) Answer the questions in a paragraph response. Remove all questions and this note (but not the table) before submitting! Do not include R/Excel code in your report._

    ### 3. Multiple Regression: Create a multiple linear regression model to predict the murder rate using all important variables.

    In general, how is a multiple linear regression model used to predict the response variable using predictor variables?

    Report the P-value in a formatted table as shown below:

    | | |
    | — | — |
    | **Statistic** | **Value** |
    | P-value | X.XXXX<br>_*Round off to 4 decimal places._ |

    Based on the results of the overall p- value, is at least one of the predictors statistically significant in predicting the murder rate?

    List all the important variables to predict the murder rate based on p-value.

    Report and interpret the coefficient of determination.

    What is the equation for your model?

    What is the predicted murder rate based on your final multiple regression model (assume some random values for your variables)?

    _![](https://www.sweetstudy.com/questions/business-statistics-project-20902291)__Answer the questions in a paragraph response. Remove all questions and this note (but not the table) before submitting! Do not include R/Excel code in your report._

    ### 4. Conclusion

    _Describe the results of the statistical analyses clearly, using proper descriptions of statistical terms and concepts. Fully describe what these results mean for your scenario._

    Briefly summarize your findings in plain language.

    What is the practical importance of the analyses that were performed?

    ### 5. Citations

    _You were_
    _**not**_ _required to use external resources for this report. If you did not use any resources, you should remove this entire section. However, if you did use any resources to help you with your interpretation, you_
    _**must**_ _cite them. Use proper APA format for citations._

    Insert references here in the following format:

    Author's Last Name, First Initial. Middle Initial. (Year of Publication). Title of book: Subtitle of book, edition. Place of Publication: Publisher.

    _You must use the following template for your report:_

    Section 1. Answers to the specific questions asked

    Section 2: Excel code. No points may be given if a brief look at the code does not tell us what it is

    doing.

    Consider the crime data stored in crime.csv. We would like to understand how murder rate is

    related to the other variables in the dataset.
    (a) Build a linear regression model murder rate vs single.parent and comment on your model.
    (b) Build a multiple linear regression model to predict murder rate based on the other variables.
    The model should have all the important variables and it should not have any unimportant
    variables. Be sure to explore the interactions as well. Perform model diagnostics to check the
    standard model assumptions and perform any transformations needed to obtain a model for
    which the assumptions reasonably hold.
    (c) Use your final model to predict murder rate.

    Context of data

    This dataset compiles crime records from 51 states, featuring a condensed set of fields that center around key attributes like the unemployment rate, single parent rate, college-educated people rate, and more. Your role as a data analyst is to compute the crime rate for each state by leveraging the specified attributes in the dataset. Apply your understanding of both simple and multiple linear regression analysis, acquired in our class, to predict the crime rate effectively.

    **image2.png**

    **## crime.csv**

    | | | | | | | | | |
    | — | — | — | — | — | — | — | — | — |
    | state | murder.rate | poverty | high.school | college | single.parent | unemployed | metropolitan | region |
    | Alabama | 7.4 | 14.7 | 77.5 | 20.4 | 26 | 4.6 | 70.2 | South |
    | Alaska | 4.3 | 8.4 | 90.4 | 28.1 | 23.2 | 6.6 | 41.6 | West |
    | Arizona | 7 | 13.5 | 85.1 | 24.6 | 23.5 | 3.9 | 87.9 | West |
    | Arkansas | 6.3 | 15.8 | 81.7 | 18.4 | 24.7 | 4.4 | 49 | South |
    | California | 6.1 | 14 | 81.2 | 27.5 | 21.8 | 4.9 | 96.7 | West |
    | Colorado | 3.1 | 8.5 | 89.7 | 34.6 | 20.8 | 2.7 | 84 | West |
    | Connecticut | 2.9 | 7.7 | 88.2 | 31.6 | 22.9 | 2.3 | 95.6 | Northeast |
    | Delaware | 3.2 | 9.9 | 86.1 | 24 | 25.6 | 4 | 81.4 | South |
    | Florida | 5.6 | 12 | 84 | 22.8 | 26.5 | 3.6 | 93 | South |
    | Georgia | 8 | 12.5 | 82.6 | 23.1 | 25.5 | 3.7 | 69.1 | South |
    | Hawaii | 2.9 | 10.6 | 87.4 | 26.3 | 19.1 | 4.3 | 72.9 | West |
    | Idaho | 1.2 | 13.3 | 86.2 | 20 | 17.7 | 4.9 | 38.6 | West |
    | Illinois | 7.2 | 10.5 | 85.5 | 27.1 | 21.9 | 4.4 | 84.5 | North Central |
    | Indiana | 5.8 | 8.3 | 84.6 | 17.1 | 22.8 | 3.2 | 71.8 | North Central |
    | Iowa | 1.6 | 7.9 | 89.7 | 25.5 | 19.8 | 2.6 | 44.9 | North Central |
    | Kansas | 6.3 | 10.5 | 88.1 | 27.3 | 20.2 | 3.7 | 56.8 | North Central |
    | Kentucky | 4.8 | 12.5 | 78.7 | 20.5 | 23.2 | 4.1 | 48.4 | South |
    | Lousiana | 12.5 | 18.5 | 80.8 | 22.5 | 29.3 | 5.5 | 75.2 | South |
    | Maine | 1.2 | 9.8 | 89.3 | 24.1 | 23.7 | 3.5 | 36.3 | Northeast |
    | Maryland | 8.1 | 7.3 | 85.7 | 32.3 | 24.5 | 3.9 | 92.7 | South |
    | Massachusetts | 2 | 10.2 | 85.1 | 32.7 | 22.8 | 2.6 | 92.1 | Northeast |
    | Michigan | 6.7 | 10.2 | 86.2 | 23 | 24.5 | 3.6 | 82.5 | North Central |
    | Minnesota | 3.1 | 7.9 | 90.8 | 31.2 | 19.6 | 3.3 | 70.3 | North Central |
    | Mississippi | 9 | 15.5 | 80.3 | 18.7 | 30 | 5.7 | 36.2 | South |
    | Missouri | 6.2 | 9.8 | 86.6 | 26.2 | 24.3 | 3.5 | 68 | North Central |
    | Montana | 1.8 | 16 | 89.6 | 23.8 | 21.4 | 4.9 | 33.4 | West |
    | Nebraska | 3.7 | 10.7 | 90.4 | 24.6 | 19.6 | 3 | 52.2 | North Central |
    | Nevada | 6.5 | 10.1 | 82.8 | 19.3 | 24.2 | 4.1 | 86.6 | West |
    | New_Hampshire | 1.8 | 7.6 | 88.1 | 30.1 | 20 | 2.8 | 60.3 | Northeast |
    | New_Jersey | 3.4 | 8.1 | 87.3 | 30.1 | 20.2 | 3.8 | 100 | Northeast |
    | New_Mexico | 7.4 | 19.3 | 82.2 | 23.6 | 26.6 | 4.9 | 57 | West |
    | New_York | 5 | 14.7 | 82.5 | 28.7 | 26 | 4.6 | 91.9 | Northeast |
    | North_Carolina | 7 | 13.2 | 79.2 | 23.2 | 24.3 | 3.6 | 67.2 | South |
    | North_Dakota | 0.6 | 12.8 | 85.5 | 22.6 | 19.1 | 3 | 43.4 | North Central |
    | Ohio | 3.7 | 11.1 | 87 | 24.6 | 24.6 | 4.1 | 80.9 | North Central |
    | Oklahoma | 5.3 | 14.1 | 86.1 | 22.5 | 23.5 | 3 | 60.6 | South |
    | Oregon | 2 | 12.9 | 88.1 | 27.2 | 22.5 | 4.9 | 72.8 | West |
    | Pennsylvania | 4.9 | 9.8 | 85.7 | 24.3 | 22.8 | 4.2 | 84.5 | Northeast |
    | Rhode_Island | 4.3 | 10.2 | 81.3 | 26.4 | 27.4 | 4.1 | 93.8 | Northeast |
    | South_Carolina | 5.8 | 12 | 83 | 19 | 27.1 | 3.9 | 70.2 | South |
    | South_Dakota | 0.9 | 9.4 | 91.8 | 25.7 | 20.7 | 2.3 | 34.5 | North Central |
    | Tennessee | 7.2 | 13.4 | 79.9 | 22 | 27.9 | 3.9 | 67.9 | South |
    | Texas | 5.9 | 14.9 | 79.2 | 23.9 | 21.5 | 4.2 | 84.6 | South |
    | Utah | 1.9 | 8.1 | 90.7 | 26.4 | 13.6 | 3.2 | 76.4 | West |
    | Vermont | 1.5 | 10.3 | 90 | 28.8 | 22.5 | 2.9 | 27.9 | Northeast |
    | Virginia | 5.7 | 8.1 | 86.6 | 31.9 | 22.2 | 2.2 | 78.2 | South |
    | Washington | 3.3 | 9.5 | 91.8 | 28.6 | 22.1 | 5.2 | 83 | West |
    | West_Virginia | 2.5 | 15.8 | 77.1 | 15.3 | 22.3 | 5.5 | 41.9 | South |
    | Wisconsin | 3.2 | 9 | 86.7 | 23.8 | 21.7 | 3.5 | 67.8 | North Central |
    | Wyoming | 2.4 | 11.1 | 90 | 20.6 | 20.8 | 3.9 | 29.6 | West |

    **## crime.csv**

    | | | | | | | | | |
    | — | — | — | — | — | — | — | — | — |
    | state | murder.rate | poverty | high.school | college | single.parent | unemployed | metropolitan | region |
    | Alabama | 7.4 | 14.7 | 77.5 | 20.4 | 26 | 4.6 | 70.2 | South |
    | Alaska | 4.3 | 8.4 | 90.4 | 28.1 | 23.2 | 6.6 | 41.6 | West |
    | Arizona | 7 | 13.5 | 85.1 | 24.6 | 23.5 | 3.9 | 87.9 | West |
    | Arkansas | 6.3 | 15.8 | 81.7 | 18.4 | 24.7 | 4.4 | 49 | South |
    | California | 6.1 | 14 | 81.2 | 27.5 | 21.8 | 4.9 | 96.7 | West |
    | Colorado | 3.1 | 8.5 | 89.7 | 34.6 | 20.8 | 2.7 | 84 | West |
    | Connecticut | 2.9 | 7.7 | 88.2 | 31.6 | 22.9 | 2.3 | 95.6 | Northeast |
    | Delaware | 3.2 | 9.9 | 86.1 | 24 | 25.6 | 4 | 81.4 | South |
    | Florida | 5.6 | 12 | 84 | 22.8 | 26.5 | 3.6 | 93 | South |
    | Georgia | 8 | 12.5 | 82.6 | 23.1 | 25.5 | 3.7 | 69.1 | South |
    | Hawaii | 2.9 | 10.6 | 87.4 | 26.3 | 19.1 | 4.3 | 72.9 | West |
    | Idaho | 1.2 | 13.3 | 86.2 | 20 | 17.7 | 4.9 | 38.6 | West |
    | Illinois | 7.2 | 10.5 | 85.5 | 27.1 | 21.9 | 4.4 | 84.5 | North Central |
    | Indiana | 5.8 | 8.3 | 84.6 | 17.1 | 22.8 | 3.2 | 71.8 | North Central |
    | Iowa | 1.6 | 7.9 | 89.7 | 25.5 | 19.8 | 2.6 | 44.9 | North Central |
    | Kansas | 6.3 | 10.5 | 88.1 | 27.3 | 20.2 | 3.7 | 56.8 | North Central |
    | Kentucky | 4.8 | 12.5 | 78.7 | 20.5 | 23.2 | 4.1 | 48.4 | South |
    | Lousiana | 12.5 | 18.5 | 80.8 | 22.5 | 29.3 | 5.5 | 75.2 | South |
    | Maine | 1.2 | 9.8 | 89.3 | 24.1 | 23.7 | 3.5 | 36.3 | Northeast |
    | Maryland | 8.1 | 7.3 | 85.7 | 32.3 | 24.5 | 3.9 | 92.7 | South |
    | Massachusetts | 2 | 10.2 | 85.1 | 32.7 | 22.8 | 2.6 | 92.1 | Northeast |
    | Michigan | 6.7 | 10.2 | 86.2 | 23 | 24.5 | 3.6 | 82.5 | North Central |
    | Minnesota | 3.1 | 7.9 | 90.8 | 31.2 | 19.6 | 3.3 | 70.3 | North Central |
    | Mississippi | 9 | 15.5 | 80.3 | 18.7 | 30 | 5.7 | 36.2 | South |
    | Missouri | 6.2 | 9.8 | 86.6 | 26.2 | 24.3 | 3.5 | 68 | North Central |
    | Montana | 1.8 | 16 | 89.6 | 23.8 | 21.4 | 4.9 | 33.4 | West |
    | Nebraska | 3.7 | 10.7 | 90.4 | 24.6 | 19.6 | 3 | 52.2 | North Central |
    | Nevada | 6.5 | 10.1 | 82.8 | 19.3 | 24.2 | 4.1 | 86.6 | West |
    | New_Hampshire | 1.8 | 7.6 | 88.1 | 30.1 | 20 | 2.8 | 60.3 | Northeast |
    | New_Jersey | 3.4 | 8.1 | 87.3 | 30.1 | 20.2 | 3.8 | 100 | Northeast |
    | New_Mexico | 7.4 | 19.3 | 82.2 | 23.6 | 26.6 | 4.9 | 57 | West |
    | New_York | 5 | 14.7 | 82.5 | 28.7 | 26 | 4.6 | 91.9 | Northeast |
    | North_Carolina | 7 | 13.2 | 79.2 | 23.2 | 24.3 | 3.6 | 67.2 | South |
    | North_Dakota | 0.6 | 12.8 | 85.5 | 22.6 | 19.1 | 3 | 43.4 | North Central |
    | Ohio | 3.7 | 11.1 | 87 | 24.6 | 24.6 | 4.1 | 80.9 | North Central |
    | Oklahoma | 5.3 | 14.1 | 86.1 | 22.5 | 23.5 | 3 | 60.6 | South |
    | Oregon | 2 | 12.9 | 88.1 | 27.2 | 22.5 | 4.9 | 72.8 | West |
    | Pennsylvania | 4.9 | 9.8 | 85.7 | 24.3 | 22.8 | 4.2 | 84.5 | Northeast |
    | Rhode_Island | 4.3 | 10.2 | 81.3 | 26.4 | 27.4 | 4.1 | 93.8 | Northeast |
    | South_Carolina | 5.8 | 12 | 83 | 19 | 27.1 | 3.9 | 70.2 | South |
    | South_Dakota | 0.9 | 9.4 | 91.8 | 25.7 | 20.7 | 2.3 | 34.5 | North Central |
    | Tennessee | 7.2 | 13.4 | 79.9 | 22 | 27.9 | 3.9 | 67.9 | South |
    | Texas | 5.9 | 14.9 | 79.2 | 23.9 | 21.5 | 4.2 | 84.6 | South |
    | Utah | 1.9 | 8.1 | 90.7 | 26.4 | 13.6 | 3.2 | 76.4 | West |
    | Vermont | 1.5 | 10.3 | 90 | 28.8 | 22.5 | 2.9 | 27.9 | Northeast |
    | Virginia | 5.7 | 8.1 | 86.6 | 31.9 | 22.2 | 2.2 | 78.2 | South |
    | Washington | 3.3 | 9.5 | 91.8 | 28.6 | 22.1 | 5.2 | 83 | West |
    | West_Virginia | 2.5 | 15.8 | 77.1 | 15.3 | 22.3 | 5.5 | 41.9 | South |
    | Wisconsin | 3.2 | 9 | 86.7 | 23.8 | 21.7 | 3.5 | 67.8 | North Central |
    | Wyoming | 2.4 | 11.1 | 90 | 20.6 | 20.8 | 3.9 | 29.6 | West |

    **## ProjectTemplate.docx**

    ### 1. Introduction

    _Discuss the statement of the problem in terms of the statistical analyses that are being performed. Be sure to address the following:_

    What is the data set that you are exploring?

    How will your results be used?

    What type of analyses will you be running in this project? Explain.

    _![](https://www.sweetstudy.com/questions/business-statistics-project-20902291) Answer the questions in a paragraph response. Remove all questions and this note before submitting! Do not include R/Excel code in your report._

    ### 2. Data Preparation

    1. What are the variables stored in crime.csv?

    2.
    **Give an overall description about your data set.**

    _![](https://www.sweetstudy.com/questions/business-statistics-project-20902291) Answer the questions in a paragraph response. Remove all questions and this note before submitting! Do not include R/Excel code in your report._

    ### 3. Simple Linear Regression: Create a simple linear regression model to predict the murder rate using single.parent.

    In general, how is a simple linear regression model used to predict the response variable using the predictor variable?

    Why you decide to use linear regression for this data set? Justify your option.

    What is the equation for your model?

    Report the P-value in a formatted table as shown below:

    | | |
    | — | — |
    | **Statistic** | **Value** |
    | P-value | X.XXXX<br>_*Round off to 4 decimal places._ |

    What is the predicted murder rate for a state that has single.paren of 25.4? Round your answer down to the nearest integer.

    _![](https://www.sweetstudy.com/questions/business-statistics-project-20902291) Answer the questions in a paragraph response. Remove all questions and this note (but not the table) before submitting! Do not include R/Excel code in your report._

    ### 3. Multiple Regression: Create a multiple linear regression model to predict the murder rate using all important variables.

    In general, how is a multiple linear regression model used to predict the response variable using predictor variables?

    Report the P-value in a formatted table as shown below:

    | | |
    | — | — |
    | **Statistic** | **Value** |
    | P-value | X.XXXX<br>_*Round off to 4 decimal places._ |

    Based on the results of the overall p- value, is at least one of the predictors statistically significant in predicting the murder rate?

    List all the important variables to predict the murder rate based on p-value.

    Report and interpret the coefficient of determination.

    What is the equation for your model?

    What is the predicted murder rate based on your final multiple regression model (assume some random values for your variables)?

    _![](https://www.sweetstudy.com/questions/business-statistics-project-20902291)__Answer the questions in a paragraph response. Remove all questions and this note (but not the table) before submitting! Do not include R/Excel code in your report._

    ### 4. Conclusion

    _Describe the results of the statistical analyses clearly, using proper descriptions of statistical terms and concepts. Fully describe what these results mean for your scenario._

    Briefly summarize your findings in plain language.

    What is the practical importance of the analyses that were performed?

    ### 5. Citations

    _You were_
    _**not**_ _required to use external resources for this report. If you did not use any resources, you should remove this entire section. However, if you did use any resources to help you with your interpretation, you_
    _**must**_ _cite them. Use proper APA format for citations._

    Insert references here in the following format:

    Author's Last Name, First Initial. Middle Initial. (Year of Publication). Title of book: Subtitle of book, edition. Place of Publication: Publisher.

    _You must use the following template for your report:_

    Section 1. Answers to the specific questions asked

    Section 2: Excel code. No points may be given if a brief look at the code does not tell us what it is

    doing.

    Consider the crime data stored in crime.csv. We would like to understand how murder rate is

    related to the other variables in the dataset.
    (a) Build a linear regression model murder rate vs single.parent and comment on your model.
    (b) Build a multiple linear regression model to predict murder rate based on the other variables.
    The model should have all the important variables and it should not have any unimportant
    variables. Be sure to explore the interactions as well. Perform model diagnostics to check the
    standard model assumptions and perform any transformations needed to obtain a model for
    which the assumptions reasonably hold.
    (c) Use your final model to predict murder rate.

    Context of data

    This dataset compiles crime records from 51 states, featuring a condensed set of fields that center around key attributes like the unemployment rate, single parent rate, college-educated people rate, and more. Your role as a data analyst is to compute the crime rate for each state by leveraging the specified attributes in the dataset. Apply your understanding of both simple and multiple linear regression analysis, acquired in our class, to predict the crime rate effectively.

    **image2.png**

    **## crime.csv**

    | | | | | | | | | |
    | — | — | — | — | — | — | — | — | — |
    | state | murder.rate | poverty | high.school | college | single.parent | unemployed | metropolitan | region |
    | Alabama | 7.4 | 14.7 | 77.5 | 20.4 | 26 | 4.6 | 70.2 | South |
    | Alaska | 4.3 | 8.4 | 90.4 | 28.1 | 23.2 | 6.6 | 41.6 | West |
    | Arizona | 7 | 13.5 | 85.1 | 24.6 | 23.5 | 3.9 | 87.9 | West |
    | Arkansas | 6.3 | 15.8 | 81.7 | 18.4 | 24.7 | 4.4 | 49 | South |
    | California | 6.1 | 14 | 81.2 | 27.5 | 21.8 | 4.9 | 96.7 | West |
    | Colorado | 3.1 | 8.5 | 89.7 | 34.6 | 20.8 | 2.7 | 84 | West |
    | Connecticut | 2.9 | 7.7 | 88.2 | 31.6 | 22.9 | 2.3 | 95.6 | Northeast |
    | Delaware | 3.2 | 9.9 | 86.1 | 24 | 25.6 | 4 | 81.4 | South |
    | Florida | 5.6 | 12 | 84 | 22.8 | 26.5 | 3.6 | 93 | South |
    | Georgia | 8 | 12.5 | 82.6 | 23.1 | 25.5 | 3.7 | 69.1 | South |
    | Hawaii | 2.9 | 10.6 | 87.4 | 26.3 | 19.1 | 4.3 | 72.9 | West |
    | Idaho | 1.2 | 13.3 | 86.2 | 20 | 17.7 | 4.9 | 38.6 | West |
    | Illinois | 7.2 | 10.5 | 85.5 | 27.1 | 21.9 | 4.4 | 84.5 | North Central |
    | Indiana | 5.8 | 8.3 | 84.6 | 17.1 | 22.8 | 3.2 | 71.8 | North Central |
    | Iowa | 1.6 | 7.9 | 89.7 | 25.5 | 19.8 | 2.6 | 44.9 | North Central |
    | Kansas | 6.3 | 10.5 | 88.1 | 27.3 | 20.2 | 3.7 | 56.8 | North Central |
    | Kentucky | 4.8 | 12.5 | 78.7 | 20.5 | 23.2 | 4.1 | 48.4 | South |
    | Lousiana | 12.5 | 18.5 | 80.8 | 22.5 | 29.3 | 5.5 | 75.2 | South |
    | Maine | 1.2 | 9.8 | 89.3 | 24.1 | 23.7 | 3.5 | 36.3 | Northeast |
    | Maryland | 8.1 | 7.3 | 85.7 | 32.3 | 24.5 | 3.9 | 92.7 | South |
    | Massachusetts | 2 | 10.2 | 85.1 | 32.7 | 22.8 | 2.6 | 92.1 | Northeast |
    | Michigan | 6.7 | 10.2 | 86.2 | 23 | 24.5 | 3.6 | 82.5 | North Central |
    | Minnesota | 3.1 | 7.9 | 90.8 | 31.2 | 19.6 | 3.3 | 70.3 | North Central |
    | Mississippi | 9 | 15.5 | 80.3 | 18.7 | 30 | 5.7 | 36.2 | South |
    | Missouri | 6.2 | 9.8 | 86.6 | 26.2 | 24.3 | 3.5 | 68 | North Central |
    | Montana | 1.8 | 16 | 89.6 | 23.8 | 21.4 | 4.9 | 33.4 | West |
    | Nebraska | 3.7 | 10.7 | 90.4 | 24.6 | 19.6 | 3 | 52.2 | North Central |
    | Nevada | 6.5 | 10.1 | 82.8 | 19.3 | 24.2 | 4.1 | 86.6 | West |
    | New_Hampshire | 1.8 | 7.6 | 88.1 | 30.1 | 20 | 2.8 | 60.3 | Northeast |
    | New_Jersey | 3.4 | 8.1 | 87.3 | 30.1 | 20.2 | 3.8 | 100 | Northeast |
    | New_Mexico | 7.4 | 19.3 | 82.2 | 23.6 | 26.6 | 4.9 | 57 | West |
    | New_York | 5 | 14.7 | 82.5 | 28.7 | 26 | 4.6 | 91.9 | Northeast |
    | North_Carolina | 7 | 13.2 | 79.2 | 23.2 | 24.3 | 3.6 | 67.2 | South |
    | North_Dakota | 0.6 | 12.8 | 85.5 | 22.6 | 19.1 | 3 | 43.4 | North Central |
    | Ohio | 3.7 | 11.1 | 87 | 24.6 | 24.6 | 4.1 | 80.9 | North Central |
    | Oklahoma | 5.3 | 14.1 | 86.1 | 22.5 | 23.5 | 3 | 60.6 | South |
    | Oregon | 2 | 12.9 | 88.1 | 27.2 | 22.5 | 4.9 | 72.8 | West |
    | Pennsylvania | 4.9 | 9.8 | 85.7 | 24.3 | 22.8 | 4.2 | 84.5 | Northeast |
    | Rhode_Island | 4.3 | 10.2 | 81.3 | 26.4 | 27.4 | 4.1 | 93.8 | Northeast |
    | South_Carolina | 5.8 | 12 | 83 | 19 | 27.1 | 3.9 | 70.2 | South |
    | South_Dakota | 0.9 | 9.4 | 91.8 | 25.7 | 20.7 | 2.3 | 34.5 | North Central |
    | Tennessee | 7.2 | 13.4 | 79.9 | 22 | 27.9 | 3.9 | 67.9 | South |
    | Texas | 5.9 | 14.9 | 79.2 | 23.9 | 21.5 | 4.2 | 84.6 | South |
    | Utah | 1.9 | 8.1 | 90.7 | 26.4 | 13.6 | 3.2 | 76.4 | West |
    | Vermont | 1.5 | 10.3 | 90 | 28.8 | 22.5 | 2.9 | 27.9 | Northeast |
    | Virginia | 5.7 | 8.1 | 86.6 | 31.9 | 22.2 | 2.2 | 78.2 | South |
    | Washington | 3.3 | 9.5 | 91.8 | 28.6 | 22.1 | 5.2 | 83 | West |
    | West_Virginia | 2.5 | 15.8 | 77.1 | 15.3 | 22.3 | 5.5 | 41.9 | South |
    | Wisconsin | 3.2 | 9 | 86.7 | 23.8 | 21.7 | 3.5 | 67.8 | North Central |
    | Wyoming | 2.4 | 11.1 | 90 | 20.6 | 20.8 | 3.9 | 29.6 | West |

    **## ProjectTemplate.docx**

    ### 1. Introduction

    _Discuss the statement of the problem in terms of the statistical analyses that are being performed. Be sure to address the following:_

    What is the data set that you are exploring?

    How will your results be used?

    What type of analyses will you be running in this project? Explain.

    _![](https://www.sweetstudy.com/questions/business-statistics-project-20902291) Answer the questions in a paragraph response. Remove all questions and this note before submitting! Do not include R/Excel code in your report._

    ### 2. Data Preparation

    1. What are the variables stored in crime.csv?

    2.
    **Give an overall description about your data set.**

    _![](https://www.sweetstudy.com/questions/business-statistics-project-20902291) Answer the questions in a paragraph response. Remove all questions and this note before submitting! Do not include R/Excel code in your report._

    ### 3. Simple Linear Regression: Create a simple linear regression model to predict the murder rate using single.parent.

    In general, how is a simple linear regression model used to predict the response variable using the predictor variable?

    Why you decide to use linear regression for this data set? Justify your option.

    What is the equation for your model?

    Report the P-value in a formatted table as shown below:

    | | |
    | — | — |
    | **Statistic** | **Value** |
    | P-value | X.XXXX<br>_*Round off to 4 decimal places._ |

    What is the predicted murder rate for a state that has single.paren of 25.4? Round your answer down to the nearest integer.

    _![](https://www.sweetstudy.com/questions/business-statistics-project-20902291) Answer the questions in a paragraph response. Remove all questions and this note (but not the table) before submitting! Do not include R/Excel code in your report._

    ### 3. Multiple Regression: Create a multiple linear regression model to predict the murder rate using all important variables.

    In general, how is a multiple linear regression model used to predict the response variable using predictor variables?

    Report the P-value in a formatted table as shown below:

    | | |
    | — | — |
    | **Statistic** | **Value** |
    | P-value | X.XXXX<br>_*Round off to 4 decimal places._ |

    Based on the results of the overall p- value, is at least one of the predictors statistically significant in predicting the murder rate?

    List all the important variables to predict the murder rate based on p-value.

    Report and interpret the coefficient of determination.

    What is the equation for your model?

    What is the predicted murder rate based on your final multiple regression model (assume some random values for your variables)?

    _![](https://www.sweetstudy.com/questions/business-statistics-project-20902291)__Answer the questions in a paragraph response. Remove all questions and this note (but not the table) before submitting! Do not include R/Excel code in your report._

    ### 4. Conclusion

    _Describe the results of the statistical analyses clearly, using proper descriptions of statistical terms and concepts. Fully describe what these results mean for your scenario._

    Briefly summarize your findings in plain language.

    What is the practical importance of the analyses that were performed?

    ### 5. Citations

    _You were_
    _**not**_ _required to use external resources for this report. If you did not use any resources, you should remove this entire section. However, if you did use any resources to help you with your interpretation, you_
    _**must**_ _cite them. Use proper APA format for citations._

    Insert references here in the following format:

    Author's Last Name, First Initial. Middle Initial. (Year of Publication). Title of book: Subtitle of book, edition. Place of Publication: Publisher.

    _You must use the following template for your report:_

    Section 1. Answers to the specific questions asked

    Section 2: Excel code. No points may be given if a brief look at the code does not tell us what it is

    doing.

    Consider the crime data stored in crime.csv. We would like to understand how murder rate is

    related to the other variables in the dataset.
    (a) Build a linear regression model murder rate vs single.parent and comment on your model.
    (b) Build a multiple linear regression model to predict murder rate based on the other variables.
    The model should have all the important variables and it should not have any unimportant
    variables. Be sure to explore the interactions as well. Perform model diagnostics to check the
    standard model assumptions and perform any transformations needed to obtain a model for
    which the assumptions reasonably hold.
    (c) Use your final model to predict murder rate.

    Context of data

    This dataset compiles crime records from 51 states, featuring a condensed set of fields that center around key attributes like the unemployment rate, single parent rate, college-educated people rate, and more. Your role as a data analyst is to compute the crime rate for each state by leveraging the specified attributes in the dataset. Apply your understanding of both simple and multiple linear regression analysis, acquired in our class, to predict the crime rate effectively.

    **image2.png**

    **## crime.csv**

    | | | | | | | | | |
    | — | — | — | — | — | — | — | — | — |
    | state | murder.rate | poverty | high.school | college | single.parent | unemployed | metropolitan | region |
    | Alabama | 7.4 | 14.7 | 77.5 | 20.4 | 26 | 4.6 | 70.2 | South |
    | Alaska | 4.3 | 8.4 | 90.4 | 28.1 | 23.2 | 6.6 | 41.6 | West |
    | Arizona | 7 | 13.5 | 85.1 | 24.6 | 23.5 | 3.9 | 87.9 | West |
    | Arkansas | 6.3 | 15.8 | 81.7 | 18.4 | 24.7 | 4.4 | 49 | South |
    | California | 6.1 | 14 | 81.2 | 27.5 | 21.8 | 4.9 | 96.7 | West |
    | Colorado | 3.1 | 8.5 | 89.7 | 34.6 | 20.8 | 2.7 | 84 | West |
    | Connecticut | 2.9 | 7.7 | 88.2 | 31.6 | 22.9 | 2.3 | 95.6 | Northeast |
    | Delaware | 3.2 | 9.9 | 86.1 | 24 | 25.6 | 4 | 81.4 | South |
    | Florida | 5.6 | 12 | 84 | 22.8 | 26.5 | 3.6 | 93 | South |
    | Georgia | 8 | 12.5 | 82.6 | 23.1 | 25.5 | 3.7 | 69.1 | South |
    | Hawaii | 2.9 | 10.6 | 87.4 | 26.3 | 19.1 | 4.3 | 72.9 | West |
    | Idaho | 1.2 | 13.3 | 86.2 | 20 | 17.7 | 4.9 | 38.6 | West |
    | Illinois | 7.2 | 10.5 | 85.5 | 27.1 | 21.9 | 4.4 | 84.5 | North Central |
    | Indiana | 5.8 | 8.3 | 84.6 | 17.1 | 22.8 | 3.2 | 71.8 | North Central |
    | Iowa | 1.6 | 7.9 | 89.7 | 25.5 | 19.8 | 2.6 | 44.9 | North Central |
    | Kansas | 6.3 | 10.5 | 88.1 | 27.3 | 20.2 | 3.7 | 56.8 | North Central |
    | Kentucky | 4.8 | 12.5 | 78.7 | 20.5 | 23.2 | 4.1 | 48.4 | South |
    | Lousiana | 12.5 | 18.5 | 80.8 | 22.5 | 29.3 | 5.5 | 75.2 | South |
    | Maine | 1.2 | 9.8 | 89.3 | 24.1 | 23.7 | 3.5 | 36.3 | Northeast |
    | Maryland | 8.1 | 7.3 | 85.7 | 32.3 | 24.5 | 3.9 | 92.7 | South |
    | Massachusetts | 2 | 10.2 | 85.1 | 32.7 | 22.8 | 2.6 | 92.1 | Northeast |
    | Michigan | 6.7 | 10.2 | 86.2 | 23 | 24.5 | 3.6 | 82.5 | North Central |
    | Minnesota | 3.1 | 7.9 | 90.8 | 31.2 | 19.6 | 3.3 | 70.3 | North Central |
    | Mississippi | 9 | 15.5 | 80.3 | 18.7 | 30 | 5.7 | 36.2 | South |
    | Missouri | 6.2 | 9.8 | 86.6 | 26.2 | 24.3 | 3.5 | 68 | North Central |
    | Montana | 1.8 | 16 | 89.6 | 23.8 | 21.4 | 4.9 | 33.4 | West |
    | Nebraska | 3.7 | 10.7 | 90.4 | 24.6 | 19.6 | 3 | 52.2 | North Central |
    | Nevada | 6.5 | 10.1 | 82.8 | 19.3 | 24.2 | 4.1 | 86.6 | West |
    | New_Hampshire | 1.8 | 7.6 | 88.1 | 30.1 | 20 | 2.8 | 60.3 | Northeast |
    | New_Jersey | 3.4 | 8.1 | 87.3 | 30.1 | 20.2 | 3.8 | 100 | Northeast |
    | New_Mexico | 7.4 | 19.3 | 82.2 | 23.6 | 26.6 | 4.9 | 57 | West |
    | New_York | 5 | 14.7 | 82.5 | 28.7 | 26 | 4.6 | 91.9 | Northeast |
    | North_Carolina | 7 | 13.2 | 79.2 | 23.2 | 24.3 | 3.6 | 67.2 | South |
    | North_Dakota | 0.6 | 12.8 | 85.5 | 22.6 | 19.1 | 3 | 43.4 | North Central |
    | Ohio | 3.7 | 11.1 | 87 | 24.6 | 24.6 | 4.1 | 80.9 | North Central |
    | Oklahoma | 5.3 | 14.1 | 86.1 | 22.5 | 23.5 | 3 | 60.6 | South |
    | Oregon | 2 | 12.9 | 88.1 | 27.2 | 22.5 | 4.9 | 72.8 | West |
    | Pennsylvania | 4.9 | 9.8 | 85.7 | 24.3 | 22.8 | 4.2 | 84.5 | Northeast |
    | Rhode_Island | 4.3 | 10.2 | 81.3 | 26.4 | 27.4 | 4.1 | 93.8 | Northeast |
    | South_Carolina | 5.8 | 12 | 83 | 19 | 27.1 | 3.9 | 70.2 | South |
    | South_Dakota | 0.9 | 9.4 | 91.8 | 25.7 | 20.7 | 2.3 | 34.5 | North Central |
    | Tennessee | 7.2 | 13.4 | 79.9 | 22 | 27.9 | 3.9 | 67.9 | South |
    | Texas | 5.9 | 14.9 | 79.2 | 23.9 | 21.5 | 4.2 | 84.6 | South |
    | Utah | 1.9 | 8.1 | 90.7 | 26.4 | 13.6 | 3.2 | 76.4 | West |
    | Vermont | 1.5 | 10.3 | 90 | 28.8 | 22.5 | 2.9 | 27.9 | Northeast |
    | Virginia | 5.7 | 8.1 | 86.6 | 31.9 | 22.2 | 2.2 | 78.2 | South |
    | Washington | 3.3 | 9.5 | 91.8 | 28.6 | 22.1 | 5.2 | 83 | West |
    | West_Virginia | 2.5 | 15.8 | 77.1 | 15.3 | 22.3 | 5.5 | 41.9 | South |
    | Wisconsin | 3.2 | 9 | 86.7 | 23.8 | 21.7 | 3.5 | 67.8 | North Central |
    | Wyoming | 2.4 | 11.1 | 90 | 20.6 | 20.8 | 3.9 | 29.6 | West |

  • [Solved] R studio

    ✓ Verified Academic Solution Available

    Executive Solution Overview

    [>Statistics homework help](https://www.sweetstudy.com/fields/mathematics-statistics) – a year ago **files (1)** – ## HW6.pdf **## HW6.pdf** MthStat 568/768 �Multivariate Statistical Analysis �Spring 2025 Homework 6 Due Wednesday, April 23 1. Consider the pendigits data set, which are samples of ha…

    Instant Solution Download

    $6.99

    Immediate access to the full model answer, formatted citations, and rubric breakdown.

    Need a Fresh Custom Paper?

    Have this question answered from scratch according to your specific instructions and deadline.

    Order on TutorsGallery →

    Assignment Prompt & Instructions

    [>Statistics homework help](https://www.sweetstudy.com/fields/mathematics-statistics)

    – a year ago

    **files (1)**

    – ## HW6.pdf

    **## HW6.pdf**

    MthStat 568/768 �Multivariate Statistical Analysis �Spring 2025

    Homework 6

    Due Wednesday, April 23

    1. Consider the pendigits data set, which are samples of handwritten digits 0; 1; : : : ; 9.
    The feature variables in this case are the (x; y) coordinates of the pen tip, dis-
    cretized at eight time points (see section 7.2.1 of the book for more details).

    (a) Split the data set into training and test sets (roughly a 70/30 split). Com-
    pute Gaussian-kernel support vector machine classi�ers for several values
    of the tuning parameter
    . For each
    , �nd the misclassi�cation rate on
    the test set. What�s the lowest MCR attained?

    (b) For the optimal
    found in (a), construct the misclassi�cation table for
    the test data. Which digit seems to be the hardest to classify correctly?

    **## HW6.pdf**

    MthStat 568/768 �Multivariate Statistical Analysis �Spring 2025

    Homework 6

    Due Wednesday, April 23

    1. Consider the pendigits data set, which are samples of handwritten digits 0; 1; : : : ; 9.
    The feature variables in this case are the (x; y) coordinates of the pen tip, dis-
    cretized at eight time points (see section 7.2.1 of the book for more details).

    (a) Split the data set into training and test sets (roughly a 70/30 split). Com-
    pute Gaussian-kernel support vector machine classi�ers for several values
    of the tuning parameter
    . For each
    , �nd the misclassi�cation rate on
    the test set. What�s the lowest MCR attained?

    (b) For the optimal
    found in (a), construct the misclassi�cation table for
    the test data. Which digit seems to be the hardest to classify correctly?

  • [Solved] MA 2025 MOD 2 DB

    ✓ Verified Academic Solution Available

    Executive Solution Overview

    INSTRUCTIONS ATTACHED – a year ago **files (1)** – ## MA2025MOD2ASSN2025.docx **## MA2025MOD2ASSN2025.docx** **MA 2025 MOD 2 DB** **Part 1:Discussion Question** Welcome to this week’s discussion! Your task is to find a graph online that shows two variables correlated. This exercise will help you pra…

    Instant Solution Download

    $6.99

    Immediate access to the full model answer, formatted citations, and rubric breakdown.

    Need a Fresh Custom Paper?

    Have this question answered from scratch according to your specific instructions and deadline.

    Order on TutorsGallery →

    Assignment Prompt & Instructions

    INSTRUCTIONS ATTACHED

    – a year ago

    **files (1)**

    – ## MA2025MOD2ASSN2025.docx

    **## MA2025MOD2ASSN2025.docx**

    **MA 2025 MOD 2 DB**
    **Part 1:Discussion Question**

    Welcome to this week’s discussion! Your task is to find a graph online that shows two variables correlated. This exercise will help you practice critical thinking and data analysis skills by identifying potential lurking variables that might influence the observed relationship.

    **Steps to Complete the Discussion:**

    1.
    **Find a Graph**: Search online for a graph that displays a relationship between two variables. This could be from a news article, research paper, or any reputable source. Ensure the graph is clear and the data is well-presented.

    2.
    **Analyze the Graph**: Examine the graph carefully. Identify the two main variables. State which variable is independent and which variable is dependent. For example, a graph might show the relationship between hours of study and exam scores. Where the hours of study would be the independent variable and the exam scores would be the dependent variable.

    3.
    **Identify Lurking Variables**: Think critically about other factors that might influence the relationship between the two variables. Lurking variables are hidden factors that can affect the outcome. For instance, in the study hours vs. exam scores example, lurking variables could include the difficulty of the exam, the student’s prior knowledge, or even their health on the exam day.

    4.
    **Writ Your Analysis**: W a detailed analysis that includes:

    · A brief descri of the graph and the source where you found it.

    · An explanation of the correlation presented.

    · A discussion of at least two potential lurking variables that could influence the relationship.

    · Your thoughts on how these lurking variables might affect the interpretation of the data.

    1.
    **Post Your Analysis**: Share your analysis in the discussion forum. Be sure to include a picture of the graph and a link to the website where you found your data.

    **## MA2025MOD2ASSN2025.docx**

    **MA 2025 MOD 2 DB**
    **Part 1:Discussion Question**

    Welcome to this week’s discussion! Your task is to find a graph online that shows two variables correlated. This exercise will help you practice critical thinking and data analysis skills by identifying potential lurking variables that might influence the observed relationship.

    **Steps to Complete the Discussion:**

    1.
    **Find a Graph**: Search online for a graph that displays a relationship between two variables. This could be from a news article, research paper, or any reputable source. Ensure the graph is clear and the data is well-presented.

    2.
    **Analyze the Graph**: Examine the graph carefully. Identify the two main variables. State which variable is independent and which variable is dependent. For example, a graph might show the relationship between hours of study and exam scores. Where the hours of study would be the independent variable and the exam scores would be the dependent variable.

    3.
    **Identify Lurking Variables**: Think critically about other factors that might influence the relationship between the two variables. Lurking variables are hidden factors that can affect the outcome. For instance, in the study hours vs. exam scores example, lurking variables could include the difficulty of the exam, the student’s prior knowledge, or even their health on the exam day.

    4.
    **Writ Your Analysis**: W a detailed analysis that includes:

    · A brief descri of the graph and the source where you found it.

    · An explanation of the correlation presented.

    · A discussion of at least two potential lurking variables that could influence the relationship.

    · Your thoughts on how these lurking variables might affect the interpretation of the data.

    1.
    **Post Your Analysis**: Share your analysis in the discussion forum. Be sure to include a picture of the graph and a link to the website where you found your data.

  • [Solved] MA 2025 ASSN

    ✓ Verified Academic Solution Available

    Executive Solution Overview

    INSTRUCTIONS ATTACHED – a year ago **files (1)** – ## MA2025MOD2ASSNINFO2025.docx **## MA2025MOD2ASSNINFO2025.docx** ## Module 2 Statistics and Technology Assignment 1. The lengths in minutes of the top 45 movies streamed worldwide in 2023 are in the table below | | | | — | — | | **Movie Title*…

    Instant Solution Download

    $6.99

    Immediate access to the full model answer, formatted citations, and rubric breakdown.

    Need a Fresh Custom Paper?

    Have this question answered from scratch according to your specific instructions and deadline.

    Order on TutorsGallery →

    Assignment Prompt & Instructions

    INSTRUCTIONS ATTACHED

    – a year ago

    **files (1)**

    – ## MA2025MOD2ASSNINFO2025.docx

    **## MA2025MOD2ASSNINFO2025.docx**

    ## Module 2 Statistics and Technology Assignment

    1. The lengths in minutes of the top 45 movies streamed worldwide in 2023 are in the table below

    | | |
    | — | — |
    | **Movie Title** | **Length (minutes)** |
    | Moana | 107 |
    | Encanto | 102 |
    | The Super Mario Bros. Movie | 92 |
    | Elemental | 102 |
    | Minions: The Rise of Gru | 87 |
    | Sing 2 | 110 |
    | Frozen | 102 |
    | Black Panther: Wakanda Forever | 161 |
    | Avatar: The Way of Water | 192 |
    | Glass Onion: A Knives Out Mystery | 139 |
    | Barbie | 114 |
    | Oppenheimer | 180 |
    | John Wick: Chapter 4 | 169 |
    | The Little Mermaid | 135 |
    | Spider-Man: Across the Spider-Verse | 140 |
    | Dungeons & Dragons: Honor Among Thieves | 134 |
    | The Holdovers | 133 |
    | Killers of the Flower Moon | 206 |
    | The Hunger Games: The Ballad of Songbirds & Snakes | 157 |
    | Mission: Impossible – Dead Reckoning Part One | 163 |
    | Indiana Jones and the Dial of Destiny | 154 |
    | Scream VI | 123 |
    | The Artifice Girl | 93 |
    | Poor Things | 141 |
    | The Zone of Interest | 106 |
    | Past Lives | 106 |
    | Wonka | 120 |
    | The Coffee Table | 95 |
    | In the Land of Saints and Sinners | 108 |
    | Tabby McTat | 30 |
    | Saltburn | 131 |
    | Robot Dreams | 110 |
    | Napoleon | 158 |
    | Sisu | 91 |
    | Hit Man | 113 |
    | Missing | 111 |
    | White Bird | 120 |
    | Maestro | 129 |
    | Fair Play | 113 |
    | Rustin | 130 |
    | Chicken Run: Dawn of the Nugget | 97 |
    | Thanksgiving | 107 |
    | Poolman | 100 |
    | Godzilla Minus One | 125 |
    | Talk to Me | 95 |

    Source:
    [List of 2023 Movies and TV Shows | Reelgood](https://reelgood.com/year/2023)

    a. Construct a box-plot for the length of the movies

    b. Find the following values of the movie lengths

    Minimum

    Maximum

    Q1

    Median

    Q3

    IQR

    2. An auto transporter recorded the weights of 30 sports cars

    | | | | | | |
    | — | — | — | — | — | — |
    | 3959 | 2868 | 3577 | 2606 | 3956 | 3384 |
    | 3393 | 3679 | 3867 | 2578 | 2523 | 3834 |
    | 2578 | 3326 | 3504 | 2841 | 2713 | 3457 |
    | 3059 | 2959 | 3714 | 2554 | 3095 | 3771 |
    | 2542 | 3425 | 3942 | 3897 | 3474 | 3594 |

    a. Find the mean of the sample weights. Round to two decimal places.

    b. Find the standard deviation of the sample weights. Round to two decimal places.

    c. Construct one standard deviation of the mean.

    d. What percent of the truck weights were within one standard deviation of the mean?

    3. Members of the House of Representatives are elected in even numbered years to begin office in odd numbered years as shown in the chart below.

    | | | |
    | — | — | — |
    | **Years** | **Year Position Began** | **Number of Men** |
    | 1975–1977 | 1975 | 416 |
    | 1977–1979 | 1977 | 417 |
    | 1979–1981 | 1979 | 419 |
    | 1981–1983 | 1981 | 414 |
    | 1983–1985 | 1983 | 413 |
    | 1985–1987 | 1985 | 412 |
    | 1987–1989 | 1987 | 412 |
    | 1989–1991 | 1989 | 406 |
    | 1991–1993 | 1991 | 405 |
    | 1993–1995 | 1993 | 387 |
    | 1995–1997 | 1995 | 385 |
    | 1997–1999 | 1997 | 379 |
    | 1999–2001 | 1999 | 377 |
    | 2001–2003 | 2001 | 373 |
    | 2003–2005 | 2003 | 372 |
    | 2005–2007 | 2005 | 364 |
    | 2007–2009 | 2007 | 357 |
    | 2009–2011 | 2009 | 356 |
    | 2011–2013 | 2011 | 356 |
    | 2013–2015 | 2013 | 353 |
    | 2015–2017 | 2015 | 347 |
    | 2017–2019 | 2017 | 346 |
    | 2019–2021 | 2019 | 334 |
    | 2021–2023 | 2021 | 309 |
    | 2023–2025 | 2023 | 308 |

    Published by Statista Research Department and 5, J. (2024)
    _House of Representatives Women by Party U.S. 2023_,
    _Statista_. Available at: https://www.statista.com/statistics/1358354/women-house-representatives-party-us/

    a. Produce a scatterplot of the data. Include the line of best fit on the graph.

    b. Give the line of best fit for the data and the correlation coefficient rounded to 4 decimal places. Is the correlation positive, negative, weak, strong?

    c. Is the number of men increasing or decreasing? By how is the number of men changing per year?

    d. Based on the line of best fit, predict the number of men that will be in the House of Representatives in 2027.

    **## MA2025MOD2ASSNINFO2025.docx**

    ## Module 2 Statistics and Technology Assignment

    1. The lengths in minutes of the top 45 movies streamed worldwide in 2023 are in the table below

    | | |
    | — | — |
    | **Movie Title** | **Length (minutes)** |
    | Moana | 107 |
    | Encanto | 102 |
    | The Super Mario Bros. Movie | 92 |
    | Elemental | 102 |
    | Minions: The Rise of Gru | 87 |
    | Sing 2 | 110 |
    | Frozen | 102 |
    | Black Panther: Wakanda Forever | 161 |
    | Avatar: The Way of Water | 192 |
    | Glass Onion: A Knives Out Mystery | 139 |
    | Barbie | 114 |
    | Oppenheimer | 180 |
    | John Wick: Chapter 4 | 169 |
    | The Little Mermaid | 135 |
    | Spider-Man: Across the Spider-Verse | 140 |
    | Dungeons & Dragons: Honor Among Thieves | 134 |
    | The Holdovers | 133 |
    | Killers of the Flower Moon | 206 |
    | The Hunger Games: The Ballad of Songbirds & Snakes | 157 |
    | Mission: Impossible – Dead Reckoning Part One | 163 |
    | Indiana Jones and the Dial of Destiny | 154 |
    | Scream VI | 123 |
    | The Artifice Girl | 93 |
    | Poor Things | 141 |
    | The Zone of Interest | 106 |
    | Past Lives | 106 |
    | Wonka | 120 |
    | The Coffee Table | 95 |
    | In the Land of Saints and Sinners | 108 |
    | Tabby McTat | 30 |
    | Saltburn | 131 |
    | Robot Dreams | 110 |
    | Napoleon | 158 |
    | Sisu | 91 |
    | Hit Man | 113 |
    | Missing | 111 |
    | White Bird | 120 |
    | Maestro | 129 |
    | Fair Play | 113 |
    | Rustin | 130 |
    | Chicken Run: Dawn of the Nugget | 97 |
    | Thanksgiving | 107 |
    | Poolman | 100 |
    | Godzilla Minus One | 125 |
    | Talk to Me | 95 |

    Source:
    [List of 2023 Movies and TV Shows | Reelgood](https://reelgood.com/year/2023)

    a. Construct a box-plot for the length of the movies

    b. Find the following values of the movie lengths

    Minimum

    Maximum

    Q1

    Median

    Q3

    IQR

    2. An auto transporter recorded the weights of 30 sports cars

    | | | | | | |
    | — | — | — | — | — | — |
    | 3959 | 2868 | 3577 | 2606 | 3956 | 3384 |
    | 3393 | 3679 | 3867 | 2578 | 2523 | 3834 |
    | 2578 | 3326 | 3504 | 2841 | 2713 | 3457 |
    | 3059 | 2959 | 3714 | 2554 | 3095 | 3771 |
    | 2542 | 3425 | 3942 | 3897 | 3474 | 3594 |

    a. Find the mean of the sample weights. Round to two decimal places.

    b. Find the standard deviation of the sample weights. Round to two decimal places.

    c. Construct one standard deviation of the mean.

    d. What percent of the truck weights were within one standard deviation of the mean?

    3. Members of the House of Representatives are elected in even numbered years to begin office in odd numbered years as shown in the chart below.

    | | | |
    | — | — | — |
    | **Years** | **Year Position Began** | **Number of Men** |
    | 1975–1977 | 1975 | 416 |
    | 1977–1979 | 1977 | 417 |
    | 1979–1981 | 1979 | 419 |
    | 1981–1983 | 1981 | 414 |
    | 1983–1985 | 1983 | 413 |
    | 1985–1987 | 1985 | 412 |
    | 1987–1989 | 1987 | 412 |
    | 1989–1991 | 1989 | 406 |
    | 1991–1993 | 1991 | 405 |
    | 1993–1995 | 1993 | 387 |
    | 1995–1997 | 1995 | 385 |
    | 1997–1999 | 1997 | 379 |
    | 1999–2001 | 1999 | 377 |
    | 2001–2003 | 2001 | 373 |
    | 2003–2005 | 2003 | 372 |
    | 2005–2007 | 2005 | 364 |
    | 2007–2009 | 2007 | 357 |
    | 2009–2011 | 2009 | 356 |
    | 2011–2013 | 2011 | 356 |
    | 2013–2015 | 2013 | 353 |
    | 2015–2017 | 2015 | 347 |
    | 2017–2019 | 2017 | 346 |
    | 2019–2021 | 2019 | 334 |
    | 2021–2023 | 2021 | 309 |
    | 2023–2025 | 2023 | 308 |

    Published by Statista Research Department and 5, J. (2024)
    _House of Representatives Women by Party U.S. 2023_,
    _Statista_. Available at: https://www.statista.com/statistics/1358354/women-house-representatives-party-us/

    a. Produce a scatterplot of the data. Include the line of best fit on the graph.

    b. Give the line of best fit for the data and the correlation coefficient rounded to 4 decimal places. Is the correlation positive, negative, weak, strong?

    c. Is the number of men increasing or decreasing? By how is the number of men changing per year?

    d. Based on the line of best fit, predict the number of men that will be in the House of Representatives in 2027.

  • [Solved] Mathematics – Statistics An assignment of 4500 words.

    ✓ Verified Academic Solution Available

    Executive Solution Overview

    [>Statistics homework help](https://www.sweetstudy.com/fields/mathematics-statistics) need at least 20 references, and follow my reqiure – a year ago

    Instant Solution Download

    $6.99

    Immediate access to the full model answer, formatted citations, and rubric breakdown.

    Need a Fresh Custom Paper?

    Have this question answered from scratch according to your specific instructions and deadline.

    Order on TutorsGallery →

    Assignment Prompt & Instructions

    [>Statistics homework help](https://www.sweetstudy.com/fields/mathematics-statistics)

    need at least 20 references, and follow my reqiure

    – a year ago