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  • What is a variable?

    In programming, variables are used to store information such as numbers, text, or logical values.
    Each variable has a name (identifier) and a value, and we can use this name to access or modify the stored data anytime in the program.

  • R Question

    Question 1

    The data contained in smokers.csv reports the findings of Spilich, June, and Renner (1992), who asked nonsmokers (NS), smokers who had delayed smoking for three hours (DS), and smokers who were actively smoking (AS) to perform a pattern recognition task in which they had to locate a target on a screen. The dependent variable was latency (in seconds).

    Plot the means and 95% confidence intervals of the smokers.csv data.

    Display a data frame that shows the group means, as well as the lower and upper boundaries of the confidence intervals. Do not display any other statistics in the data frame.

    Question 2

    Looking at the plot, what is a potential concern for the smokers.csv data?

    Question 3

    Without using the lm() or aov() function, compute an omnibus F-test. Is there support for the hypothesis that smoking has an effect on performance? Report the:

    • F-statistic
    • Degrees of freedom
    • P-value

    Question 4

    Report an effect size in terms of for the test you ran in the previous question. You should obtain a negative result. What do you think this means in plain English? (You wont lose marks if you are incorrect.)

    Question 5

    Run an ANOVA with planned contrasts that:

    1. compares the combined effect of the active smokers and delayed smokers to the non-smokers, and
    2. compares the active smokers with the delayed smokers.

    Report the test statistic, degrees of freedom, and p-value for those two comparisons. You ARE allowed to use the functions lm() and aov().

    Question 6

    Report an effect size in terms of a partial correlation for each of the contrasts you conducted in the previous question.

    Question 7

    Recall that there is a version of the t-test called a Welchs t-test that is robust to unequal variances. The Welch procedure can actually be extended to One-Way ANOVAs using the function oneway.test().

    Use your excellent sleuthing skills to figure out how to use this function and display its results (Omnibus F-statistic, degrees of freedom, and p-value) for a One-Way analysis of variance that doesnt assume equal variances on the smokers.csv data. Does your interpretation of this ANOVA change from the first one you ran?

    Question 8

    Write some R code that re-creates the following matrix:

         [,1] [,2] [,3]
    [1,]  78   85   92
    [2,]  81   79   88

    Display the matrix and use the is.matrix() function to prove it is a matrix.

    Note: We never learned how to do this in class, so you need to figure it out on your own.

    Question 9

    From the previous question, apply the transpose function t() to the matrix. In plain English, what has this function done specifically?

    Question 10

    Create the following two matrices:

    Matrix A:

         [,1] [,2]
    [1,]   1    3
    [2,]   2    4

    Matrix B:

         [,1] [,2]
    [1,]   5    7
    [2,]   6    8

    Multiply them like this: A * B and then write out how each value in the matrix was calculated.

    Example:

    • [1,1] = … = 5
    • [2,1] = … = 12
    • [1,2] = … = 21
    • [2,2] = … = 32

    (Replace the … with the calculation that was performed.)

    Question 11

    Repeat the previous question, but this time multiply them like this: A %*% B.

    Question 12

    Write some (efficient) R code to re-create the following multiplication table:

          [,1] [,2] ... [,12]
    [1,]    1    2  ...   12
    [2,]    2    4  ...   24
    ...
    [12,]  12   24  ...  144

  • Management Question

    i want solv this Assignment 2 MGT323

  • bagian mata yang berfungsi mengatur banyak dan sedikitnya ca…

    bagian mata yang berfungsi mengatur banyak dan sedikitnya cahaya yang masuk ke mata

    adalah pupil


  • Management Question

    i want solve this assignment MGT311 2

  • All important questions and farmula trigonometry base strong…

    All important questions all topics and formula base strong see all of you and learning

  • Principal Component Analysis

    Principal Component Analysis

    TASK

    Your task is to conduct PCA on the numeric features of the MLData2026 dataset,

    demonstrating the process and interpreting the results in a video presentation.

    The due date for this assessment is Friday of Week 7 on 17 April 2026 before midnight.

    Perform PCA and Visualise Data

    (i) Download the Assignment 2.ipynb file, along with MLData2026.csv from the

    Assignment 1 folder on Canvas. To help you begin your assignment, the Assignment 2

    Google Colab file contains some starter code (the same as for Assignment 1) to

    1. Mount your drive

    2. Import the relevant packages. You may need to add more packages as your

    assignment progresses.

    3. Upload the MLData2026.csv to your Google Colab storage folder, then read and

    convert the data into a dataFrame. Consider this as the Master data set.

    4. Randomly select 600 sub-samples from the Master data set. Make sure to use

    your Student ID to set the random set. This means that every student should

    have their own unique set of sub-samples, i.e. mydata, to work on.

    You are required to perform PCA on the relevant features in mydata using Python on

    Google Colab and report your findings.

    (ii) Extract only the numeric features and the Class feature from mydata and store them

    in a dataFrame. Refer to Assignment 1 for the feature description if needed.

    (iii)Clean the extracted data based on the feedback received from Assignment 1.

    (iv) Remove the incomplete cases, e.g. using dropna(), to make it usable for PCA.

    (v) Perform PCA in Python using Google Colab, but only on the numeric features (i.e.

    ignore Class in this step).

    – Explain why you believe the data should or should not be scaled, i.e.

    standardised, when performing PCA.

    – Display and describe the individual and cumulative proportions of variance (3

    decimal places) explained by each of the principal components.

    – Outline how many principal components are adequate to explain at least 50%

    of the variability in your data.

    Assignment 2 – Video Presentation (35%)

    2 | P a g e

    ECU Internal Information

    – Display and interpret the coefficients (or loadings) to 3 decimal places for PC1,

    PC2 and PC3. Describe which features (based on the loadings) are the key

    drivers for each of these three principal components.

    (vi) Create and display the biplot for PC1 vs. PC2 to visualise the PCA results in the first

    two dimensions. Colour-code the points based on the Class feature. Explain the biplot

    by commenting on the PCA plot and the loadings plot individually, and then both

    plots combined (see Slides 2829 of Module 3 notes). Finally, comment on and justify

    which (if any) features can help distinguish malicious activity.

    (vii) Based on the results from parts (v) and (vi), describe

    – whether PC1 or PC2 (choose one) best assists in classifying malicious activity.

    Hint: Project all points in the PCA plot onto the PC1 axis (i.e. consider the PC1

    scores only) and assess whether there is a clear separation between malicious

    and non-malicious samples. Then, project onto the PC2 axis (i.e. consider the

    PC2 scores only) and evaluate whether the separation is better than in PC1.

    – the key features in this dimension that can drive this process (Hint: based on

    your decision above, examine the loadings from part (v) of your chosen PC and

    choose those whose absolute loading (i.e. disregard the sign) is greater than

    0.3).

    Video Presentation Checklist

    1. In your video presentation, you must

    a. Run your code in Google Colab corresponding to parts (i) to (vii)

    b. Display the relevant output on screen

    c. Interpret the output in response to parts (i) to (vii)

    2. Your video presentation must include a camera shot of yourself in the video

    capture, unless there is an exceptional reason and is supported by a Learning

    Assessment Plan (LAP). 20% is automatically deducted from your final mark if

    this is not included in your video presentation. If you choose to record with

    another application, you must make sure that this feature is included.

    3. Your video presentation must be between 6-8 minutes long.

    4. Submit the recording via the Panopto link on Canvas. Please ensure you follow

    the instructions carefully.

    5. Submit your Python code (Google Colab) using a separate submission link.

    Assignment 2 – Video Presentation (35%)

    3 | P a g e

    ECU Internal Information

    Marking Rubrics

    Criteria Fail 2

    <30%

    Fail 1

    30-49%

    Pass

    50-59%

    Credit

    60-69%

    Distinction

    70-79%

    High Distinction

    80-100%

    Working Code

    (7%)

    Code is substantially

    incomplete, does not

    run or contains

    major flaws,

    preventing any

    meaningful PCA

    analysis.

    Documentation is

    minimal or absent

    Code does not run

    properly or contains

    major flaws, preventing

    meaningful PCA

    analysis.

    Documentation is

    minimal

    Code has significant

    errors or omissions

    that affect PCA output.

    Poor documentation

    and some redundancy.

    Code has a few errors

    and/or does not fully

    achieve intended PCA

    and relevant analyses.

    Documentation is

    present but could be

    improved.

    Code runs with minor

    issues but still

    performs PCA and

    relevant tasks

    correctly. Minimal

    redundancy and good

    documentation.

    Code runs flawlessly,

    correctly performs

    PCA and relevant

    tasks, and produces

    meaningful outputs.

    No errors, redundant

    code, or inefficiencies.

    Interpretation of

    results (18%)

    Fails to interpret the

    PCA results

    meaningfully or

    demonstrate any

    understanding of

    PCA, and draws

    incorrect

    conclusions.

    Fails to interpret the

    PCA results

    meaningfully for the

    most part or provides

    incorrect conclusions.

    Interpretation is vague,

    lacks depth, and/or

    has major inaccuracies

    or errors.

    Provides a basic

    interpretation with

    some inaccuracies or

    missing key insights.

    Provides a strong and

    mostly accurate

    interpretation of PCA

    results with minor

    omissions or

    inaccuracies.

    Provides an in-depth,

    clear, and accurate

    interpretation of PCA

    results, including the

    significance of

    principal components

    and key loadings.

    Justifies conclusions

    with evidence.

    Presentation

    skills (7%)

    The presentation is

    unclear and does

    not engage the

    audience. The

    presenter makes

    little to no attempt at

    expression, and the

    pace and tone

    require substantial

    improvement.

    The presentation is

    unclear. The presenter

    made an attempt at

    expression, but the

    pace and tone need

    improvement to better

    engage the audience.

    The presentation lacks

    structure. Presenter

    made a good attempt,

    but the expression,

    pace, and tone could

    be improved.

    The presentation is

    understandable and

    delivered at a good

    pace. However, there

    is minimal confidence

    in the presentation

    style.

    Clear and structured

    presentation with minor

    pacing or engagement

    issues. Presenter was

    fluent and displayed

    good confidence.

    The presenter was

    dynamic, natural, and

    persuasive, with an

    appropriate tone.

    Delivery was clear,

    confident, and well-

    structured, with

    effective pacing and

    engagement that

    maintained a high

    level of confidence

    throughout.

    Timing (3%) Presentation is less

    than 3 minutes or

    more than 12

    minutes.

    Presentation is

    between 3 and 4

    minutes, or between 11

    and 12 minutes

    Presentation is

    between 4 and 5

    minutes, or between

    10 and 11 minutes

    Presentation is

    between 5 and 6

    minutes, or between 9

    and 10 minutes

    Presentation is

    between 8 and 9

    minutes

    Presentation is

    between 6 and 8

    minutes

    Assignment 2 – Video Presentation (35%)

    4 | P a g e

    ECU Internal Information

    Academic Misconduct

    Edith Cowan University regards academic misconduct of any form as unacceptable.

    Academic misconduct, which includes but is not limited to, plagiarism; unauthorised

    collaboration; cheating in examinations; theft of other students work; collusion;

    inadequate and incorrect referencing; will be dealt with in accordance with the ECU Rule

    40 Academic Misconduct (including Plagiarism) Policy. Ensure that you are familiar with

    the Academic Misconduct Rules.

    Assignment Extensions

    Instructions to apply for extensions are available on the ECU Online Extension Request

    and Tracking System to formally lodge your assignment extension request. The link is

    also available on Canvas in the Assignment section.

    Normal work commitments, family commitments and extra-curricular activities are

    NOT accepted as grounds for granting you an extension of time because you are

    expected to plan ahead for your assessment due dates.

    Where the assignment is submitted not more than 7 days late, the penalty shall, for each

    day that it is late, be 5% of the maximum assessment available for the assignment.

    Where the assignment is more than 7 days late, a mark of zero shall be awarded.

  • AI Assistants as a Strategic Opportunity

    Group Strategic Presentation AI Assistants as a Strategic Opportunity (do only part 1 and 2)

    Value: 30%

    Group or Individual: Group (45 students)

    Deadline:

    Slides should be submitted by 20th April 23:59 (week 7) (week 8)

    Presentations will be delivered in class during Week 7 week 8, 23rd April. Presentation

    order will be given closer to the date.

    Presentation Duration:

    10 minutes presentation

    5 minutes Q&A

    All group members must present

    Unit Learning Outcomes Assessed

    This assessment addresses the following Unit Learning Outcome:

    ULO1: Review the major activities and techniques involved in IT/IS value

    management.

    ULO2: Appraise the role of governance in IT/IS value management.

    ULO3: Construct a business case to support an investment in IT/IS.

    ULO4: Assess the impacts of IT implementation on diverse stakeholders,

    including from an ethical or social perspective.

    ULO5: Communicate and collaborate effectively in project team settings,

    including reflection on your individual performance to identify opportunities for

    future improvement.

    Assessment Context (Scenario)

    Edith Cowan University (ECU) is transitioning to the City Campus and exploring new

    approaches to delivering teaching and learning at scale.

    Senior management is considering the strategic use of Agentic AI teaching assistants

    to:

    Support student learning and engagement

    Reduce academic teaching workload

    Enable staff to focus more on research, industry engagement, and innovation

    Agentic AI refers to AI systems capable of acting autonomously within defined

    boundaries to support tasks such as answering questions, guiding learners, and

    escalating issues when required.

    However, there is resistance from academic staff, including concerns about:

    Student satisfaction

    Teaching quality

    Loss of human interaction

    Ethical and reputational risks

    You are part of the ECU Strategy and Digital Transformation Team.

    Assessment Task

    As a Strategy and Digital Transformation Team, your group will analyse this ECU

    scenario and present a strategic recommendation to senior management.

    Your analysis must be grounded in concepts learned in Weeks 16 of this unit,

    including:

    Strategic alignment

    Procurement practices (high level)

    IT benefits realisation

    IT value creation and decision support

    ICT infrastructure and network design

    Cloud computing

    Do not explain theory. Apply it directly to the ECU context.

    Key Requirement

    This is:

    Not a technology demonstration

    Not a pro- or anti-AI debate

    Instead, this is a strategic, value-focused decision analysis, evaluating whether and how

    AI teaching assistants should be adopted at ECU.

    Required Presentation Structure

    1. Strategic Context

    Overview of ECUs strategic environment

    City Campus transition

    Key pressures facing higher education (scalability, cost, competition, student

    expectations)

    2. Procurement analysis (Week 2)

    3. Opportunity Identification Value & Benefits (Week 3)

    4. Decision Support & Value Justification (Week 4)

    5. Infrastructure & Technology Enablement (Weeks 56)

    6. Strategic Recommendation to Executives

    Present a balanced and defensible recommendation, such as:

    Full adoption

    Pilot program

    Hybrid humanAI teaching model

    Your recommendation must be:

    Evidence-based

    Aligned with ECUs strategic objectives

    Aware of risks and mitigation strategies

    6. References (you do not have to present, show at the end)

    Tips

    If you are aware of relevant real-world examples similar to this case, you may

    briefly reference them to support your argument.

    Focus on judgement and justification, not description.

    Presentation Guidelines

    This is an executive briefing, not a lecture

    Slides must be clear, visual, and concise

    Do not read from slides. Remember you are the expert, don’t expect audience

    know the terms you are talking about.

    Every group member must actively participate

    The 5-minute Q&A will take place at the end of the presentation

    Submission Requirements

    Slides must be uploaded to Canvas before the presentation session

    No changes can be made after submission

    You must rely on the submitted slides during the presentation

    All group members should wear appropriate attire

    References should follow APA 7th Format. Minimum 10 references should

    include.

  • Favorite Scholarly Article

    Choose one article from the three scholarly articles presented below:

    First, on your paper, please identify the title and main topic of your favorite article. Then answer the following prompts:

    1. Describe the key findings or arguments presented in your favorite article. What stood out to you the most?
    2. Why did you choose this particular article as your favorite in comparison to the other two? What was it about the topic, methodology, or writing style that resonated with you?
    3. Reflect on how your understanding of the topic was deepened or challenged by reading your favorite article. Did it change any of your previous assumptions or beliefs?

    Paper Guidelines

    • Write at least 250 words total (for all three questions) roughly one double-spaced page.
    • Double-space.
    • Number your answers 1-3.
    • There is no need to rewrite the questions.
    • Each answer is worth 8 points for a total of 24 points.

    Resource

    The document below will give you tips on how to read/digest a scholarly article with minimal effort. What could be better?

    Learning Outcomes

    These prompts encourage students to critically engage with their favorite scholarly article, analyze its content and methodology, and reflect on its broader implications for their academic and professional growth.

    Rubric

    Favorite Scholarly Article

    Favorite Scholarly Article
    Criteria Ratings Pts

    This criterion is linked to a Learning OutcomeKey FindingsWhat are the key findings and what stood out the most?

    8 ptsFull CreditStudent clearly and thoroughly answered the prompt.3.84 ptsHalf CreditStudent answered prompt but only on a cursory level.

    0 ptsNo CreditStudent did not adequately answer prompt.

    8 pts

    This criterion is linked to a Learning OutcomeArticle ChoiceWhy did you choose this particular article as your favorite in comparison to the other two? What was it about the topic, methodology, or writing style that resonated with you?

    8 ptsFull CreditStudent clearly and thoroughly answered the prompt.4 ptsHalf CreditStudent answered prompt but only on a cursory level.

    0 ptsNo CreditStudent did not adequately answer prompt.

    8 pts

    This criterion is linked to a Learning OutcomeUnderstanding of TopicReflect on how your understanding of the topic was deepened or challenged by reading your favorite article. Did it change any of your previous assumptions or beliefs?

    8 ptsFull CreditStudent clearly and thoroughly answered the prompt.4 ptsHalf CreditStudent answered prompt but only on a cursory level.

    0 ptsNo CreditStudent did not adequately answer prompt.

    8 pts

    Total Points: 24

  • Mechanical Eng Only!

    Design and build a functional mechanical system that demonstrates your engineering skills. The project must include 3D printed components and be documented to a professional standard suitable for your resume and portfolio.(with solidwork parts) Read!