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Tag: Statistics

  • [Solved] MINi PROJECT

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    – ## MiniProject21.html **## MiniProject21.html** 2021Fall_IE342_MiniProject2 5 (Instructor: Azadeh Haghighi) ## Mini Project 2 ### Directions: In this project, you are going to graphically present, study, analyze and evaluate the distributions of a dataset. Upload your whole package (including an…

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    – ## MiniProject21.html

    **## MiniProject21.html**

    2021Fall_IE342_MiniProject2 5 (Instructor: Azadeh Haghighi)

    ## Mini Project 2

    ### Directions:

    In this project, you are going to graphically present, study, analyze and evaluate the distributions of a dataset. Upload your whole package (including any codes, plots, and the report) to the blackboard by the due date.

    ### The Data:

    Collect the size of 1000 files on your computer. Convert all sizes to the same unit (e.g., either KB or MB). You can do a quick search online (or get help form your classmates) to find out how to collect file sizes automatically using windows dir command. You can also decide to manually record the file sizes if you cannot figure out how to do it automatically.

    ### Dataset

    Use the above dataset to plot the necessary graphs and answer the following questions.

    1. Extract the first digit of collected file sizes and collect them in a table. The first digit is defined as the first nonzero digit from the left. For example, 1294 has first digit 1, and 0.34 has first digit 3.
    2. Before ploting the distribution of these first digits, which probability distribution do you think would best represent it? Why?
    3. Now plot the probability distribution of these first digits (vertical axis represents the probability while the horizontal axis represents the digit 1, 2 , 3, 4, 5, 6, 7, 8, 9). Looking at the plot, how does the probability pattern change as you move from digit 1 to 9? (i.e., does it increase or decrease?)
    4. Now use the following function to calculate and plot the probability of digit !.

    "(!) = log!" )1 + 1!, ,

    ! = 1, 2, 3, 4, 5, 6, 7, 8, 9

    5. Merge the plots obtained in part 4 with part 3 so that they are shown side by side as clustered columns (see below for a visualization example, the probability values are just provided randomly in this figure and do not reflect any realistic case). Compare the two plots side by side. What is your observation? Do you see any relation among the two plots?

    1 0.8 0.6 0.4 0.2 0 … 1 Plot from 3 Plot from 4 3 2

    ![](https://www.sweetstudy.com/questions/mini-project-20951943)

    1. Search for “Benford’s law” online and explain what it states.
    2. Using Benford’s law explain what you observe in the plot in part 5?
    3. Find an application of Benford’s law in real life by searching the internet. Explain why this law is useful for that specific application.

    **## MiniProject21.html**

    2021Fall_IE342_MiniProject2 5 (Instructor: Azadeh Haghighi)

    ## Mini Project 2

    ### Directions:

    In this project, you are going to graphically present, study, analyze and evaluate the distributions of a dataset. Upload your whole package (including any codes, plots, and the report) to the blackboard by the due date.

    ### The Data:

    Collect the size of 1000 files on your computer. Convert all sizes to the same unit (e.g., either KB or MB). You can do a quick search online (or get help form your classmates) to find out how to collect file sizes automatically using windows dir command. You can also decide to manually record the file sizes if you cannot figure out how to do it automatically.

    ### Dataset

    Use the above dataset to plot the necessary graphs and answer the following questions.

    1. Extract the first digit of collected file sizes and collect them in a table. The first digit is defined as the first nonzero digit from the left. For example, 1294 has first digit 1, and 0.34 has first digit 3.
    2. Before ploting the distribution of these first digits, which probability distribution do you think would best represent it? Why?
    3. Now plot the probability distribution of these first digits (vertical axis represents the probability while the horizontal axis represents the digit 1, 2 , 3, 4, 5, 6, 7, 8, 9). Looking at the plot, how does the probability pattern change as you move from digit 1 to 9? (i.e., does it increase or decrease?)
    4. Now use the following function to calculate and plot the probability of digit !.

    "(!) = log!" )1 + 1!, ,

    ! = 1, 2, 3, 4, 5, 6, 7, 8, 9

    5. Merge the plots obtained in part 4 with part 3 so that they are shown side by side as clustered columns (see below for a visualization example, the probability values are just provided randomly in this figure and do not reflect any realistic case). Compare the two plots side by side. What is your observation? Do you see any relation among the two plots?

    1 0.8 0.6 0.4 0.2 0 … 1 Plot from 3 Plot from 4 3 2

    ![](https://www.sweetstudy.com/questions/mini-project-20951943)

    1. Search for “Benford’s law” online and explain what it states.
    2. Using Benford’s law explain what you observe in the plot in part 5?
    3. Find an application of Benford’s law in real life by searching the internet. Explain why this law is useful for that specific application.

  • [Solved] Mathematics – Statistics Application Assignment

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    In-depth study guidance and analytical solution covering Mathematics – Statistics Application Assignment.

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    Assignment Prompt & Instructions

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

  • [Solved] Conduct Hypothesis Testing using Bootstrap Methods, Resampling Techniques, and Confidence Intervals

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    ## **Background** Conduct hypothesis testing using bootstrap methods, implement resampling techniques, and compute confidence intervals. The assignment will incorporate a project developed in R, a report presenting the results. It will also incorporate a research review on the current state of Boots…

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    ## **Background**
    Conduct hypothesis testing using bootstrap methods, implement resampling techniques, and compute confidence intervals. The assignment will incorporate a project developed in R, a report presenting the results. It will also incorporate a research review on the current state of Bootstrapping techniques utilization in Data Science.
    ## **Instructions**
    Using this dataset contains physicochemical properties and quality ratings of red and white variants of the Portuguese "Vinho Verde" wine. Features include fixed acidity, volatile acidity, citric acid, residual sugar, chlorides, free sulfur dioxide, total sulfur dioxide, density, pH, sulphates, alcohol content, and a final quality rating from 0 (very bad) to 10 (very excellent).
    **Source**: The UCI Machine Learning Repository – Wine Quality Dataset ( [https://archive.ics.uci.edu/ml/datasets/wine+quality](https://archive.ics.uci.edu/ml/datasets/wine+quality))
    1. Setup and Data Preparation
    1. Install and load necessary R packages: tidyverse for data manipulation and visualization, boot for bootstrap analysis.
    2. Download the Wine Quality Dataset.
    3. Read the data into R using read.csv() and perform initial data exploration with functions like summary() and head().
    2. Exploratory Data Analysis (EDA)
    1. Visualize the distribution of wine quality ratings for both red and white wine samples.
    2. Explore relationships between physicochemical properties and wine quality using scatter plots and correlation analysis.
    3. Formulate a Hypothesis
    1. Example hypothesis: "The average alcohol content of high-quality wine (rating >= 7) is significantly higher than that of lower-quality wine (rating < 7)."
    4. Bootstrap Resampling for Hypothesis Testing
    1. Implement bootstrap resampling to estimate the difference in mean alcohol content between high-quality and low-quality wines.
    2. Draw many resamples with replacement from the observed dataset, compute the mean alcohol content for high-quality and low-quality wines in each resample, and calculate the difference.
    5. Compute Confidence Intervals
    1. Use the bootstrap samples to compute a 95% confidence interval for the mean difference in alcohol content.
    2. Interpret the confidence interval in the context of the hypothesis.
    6. Perform Hypothesis Testing
    1. Determine whether the observed difference in means is statistically significant based on the bootstrap confidence interval.
    2. Discuss the p-value interpretation and whether the null hypothesis can be rejected.
    7. Report Writing
    1. Introduction: Briefly introduce the project, dataset, and hypothesis.
    2. Methods: Describe the bootstrap resampling technique, hypothesis testing approach, and confidence interval computation.
    3. Results: Present the findings from the bootstrap analysis, including visualizations of the confidence interval and the conclusion regarding the hypothesis.
    4. Discussion: Interpret the results, discuss potential limitations of the study, and suggest future research directions.
    5. References: Cite all sources and R packages used.
    **Submit:**
    – **R Script (.R file)**: Containing all the code used for data preparation, EDA, bootstrap analysis, hypothesis testing, and confidence interval computation.
    – **Report (.docx):** A comprehensive report detailing the project's objective, methodology, results, and conclusions.
    **Length**: This assignment must be 5-8 pages (excluding the title and reference page).
    **References:** Include 3 scholarly resources.

  • [Solved] TOPICS IN HEALTHCARE

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    navigating to the **Research, Data,** or **Research, Statistics, Data, and Systems**

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    navigating to the **Research, Data,** or **Research, Statistics, Data, and Systems**

  • [Solved] DATA QUALITY

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    Differentiate high-quality data from low-quality data and compare how low-quality data can adversely affect data analysis

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    Assignment Prompt & Instructions

    Differentiate high-quality data from low-quality data and compare how low-quality data can adversely affect data analysis