ASSESSMENT BRIEF Subject Code and Title STAT6003 : Statistics for Financial Decisions Assessment Assessment 4 – Case Analysis Individual/Group Individual Length 2000 Words (+/- 10%) Learning Outcomes...

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ASSESSMENT BRIEF Subject Code and Title STAT6003 : Statistics for Financial Decisions Assessment Assessment 4 – Case Analysis Individual/Group Individual Length 2000 Words (+/- 10%) Learning Outcomes a) Analyse and present data graphically using spreadsheet software (Excel). b) Critically evaluate summary statistics against suitable benchmarks. c) Apply judgment to select appropriate methods of data analysis drawing on knowledge of regression analysis, probability, probability distributions and sampling distributions. d) Select and apply a range of data analysis tools to inform problem solving and decision making. e) Conduct quantitative research both individually and as part of a team and articulate and present findings to a wide range of stakeholders, from accounting and non- accounting backgrounds. Submission Module 6.2 (Week 12) Weighting 30% Total Marks 100 marks Context: The main aims to develop students’ competency in statistical literacy for decision making in the local and global business environment. It reviews statistical techniques for the quantitative evaluation of data in Financial applications. Students will develop analytical and statistical skills to enable them to transform data into meaningful information for the purpose of decision making. Objectives:  To more broadly understand the statistical literacy for decision making.  Interpret statistical results and communicate their statistical analysis in business reports. Instructions: This individual assignment requires you to apply statistical knowledge and skills learned from STAT6003 lectures between week 9, 10 and 11.  You will specify a regression model for this assignment. This model can be based on a theory, several theories, your experience, and/or ideas.  Please use Excel for statistical analysis in this assignment. Relevant Excel statistical output must be properly analysed and interpreted.  Please provide a number for every table, graph or figure used and make clear reference to the table/graph/figure in your discussion.  The assessment is to be submitted in a business report format with a word limit of 2,000 words excluding Excel output. Both Excel and the report files are to be submitted. Submit copy of presentation Report in .docx, or .pdf format via the Assessment link in the main navigation menu in STAT6003. The Learning Facilitator will provide feedback with reference to the criteria below via the Grade Centre in the LMS portal. Feedback can be viewed in My Grades. Assignment tasks: The variables for this assignment are as follows: House Price Index (a)(b): Brisbane, Sydney and Melbourne, 2002–03 to 2016–17. V1) Market Price ($000) V2) Sydney price Index V3) Annual % change V4) Total number of square meters V5) Age of house (years) 1) Module 5 topic – Regression Analysis You will specify a regression model for this assignment. This model can be based on a theory, several theories, your experience, and/or ideas from research article(s). Suggest you consider a regression model that is of interest to you or one that is related to your profession or one that you have knowledge about. (a) Using Ordinary Least Square (OLS), estimate the model (below is a template for developing your regression model): Y = 0 + 1 X1 + 2 X2 + 3 X3 + 4 X4 + . In your model, there must be one dependent variable and four independent variables. (b) For statistical analysis involving any hypothesis test in this assignment, you are required to:  Formulate the null and alternative hypotheses.  State your statistical decision using significant value (?) of 5% for each test.  State your conclusion in context. Assignment tasks: (1) Provide an introduction section on the rationale of your model , sample size, and the dependent and independent variables (including their unit of measurement) in this model. (2) Plot the dependent variable against each independent variable using scatter plot/dot function in Excel. Describe the relationship from the plots. (3) Present the full model in your assignment. (4) Write down the least squares regression equation and correctly interpret the equation. (5) Interpret the estimated coefficients of the regression model and discuss their sig values. (6) What is the value of the coefficient of determination for the relationship between the dependent and independent variables. Interpret this value accurately and in a meaningful way. (7) State the 95% confidence intervals for each parameters and interpret these intervals. (8) Estimate the linear regression model to investigate the relationship between the market price and the land size in total number of square meters. (9) Compare the original model (question 1) and re-estimated model (question 2) and evaluate the goodness of fit between them (Hint: Use R2 and Coefficient of determination to evaluate the goodness of fit of the model). (10) Predict the market price of a house (in $) with a building area of 400 square meters. STAT6003_Assessent 2 Page 4 of 6 Learning Rubric: Environmental Scan Report – Part A Assessment Attributes Fail (Unacceptable) (0-49) Pass (Functional) (50-64) Credit (Proficient) (65-74) Distinction (Advanced) (75-84) High Distinction (Exceptional) (85-100) Grade Description (Grading Scheme) Fail grade will be awarded if a student is unable to demonstrate satisfactory academic performance in the subject or has failed to complete required assessment points in accordance with the subject’s required assessment points. Pass is awarded for work showing a satisfactory achievement of all learning outcomes and an adequate understanding of theory and application of skills. A consistent academic referencing system is used and sources are appropriately acknowledged. Credit is awarded for work showing a more than satisfactory achievement of all learning outcomes and a more than adequate understanding of theory and application of skills. A consistent academic referencing system is used and sources are appropriately acknowledged. Distinction is awarded for work of superior quality in achieving all learning outcomes and a superior integration and understanding of theory and application of skills. Evidence of in-depth research, reading, analysis and evaluation is demonstrated. A consistent academic referencing system is used and sources are appropriately acknowledged. High Distinction is awarded for work of outstanding quality in achieving all learning outcomes together with outstanding integration and understanding of theory and application of skills. Evidence of in‐depth research, reading, analysis, original and creative thought is demonstrated. A consistent academic referencing system is used and sources are appropriately acknowledged. http://www.tua.edu.au/media/50742/a240_grading-scheme.pdf STAT6003_Assessent 2 Page 5 of 6 Data Analysis using Excel 45% SLO addressed: a) Examine the statistical analysis through Excel Limited or no understanding of the statistical data analysis. Identifies a proportion of the understanding of the statistical data analysis. Identifies a majority of the understanding of the statistical data analysis. Correctly identifies all of the analytical techniques and understanding of the statistical data analysis. Not only identifies all of the analytical techniques with good understanding of the statistical data analysis. Application of Framework 45% SLO addressed: b) Identify and apply appropriate frameworks and tools to the problems and challenges Demonstrates no understanding of the framework and concepts relevant to the data analysis. Demonstrates little understanding of the framework and concepts relevant to the data analysis. Demonstrates good knowledge of the framework and concepts relevant to the data analysis. Demonstrates correct knowledge of the framework and concepts relevant to the data analysis. Demonstrates correct and complete knowledge of the framework and concepts relevant to the data analysis. STAT6003_Assessent 2 Page 6 of 6 Correct citation of key resources and evidence 10% Overall structure, appearance and referencing of the report are assessed. Effective conclusions were not provided. Specific data or facts necessary to support the analysis and conclusions were not provided. Very badly written, incorrect grammar, inappropriate language used, no proper structure of the document, badly organised with no logical flow of the arguments. The document is missing in text referencing and/or a reference list. Limited conclusions were provided. Specific data or facts necessary to support the analysis and conclusions were not provided. Grammar, spelling, punctuation, professional writing and syntax needs significant improvement. The document is very poorly referenced. Effective conclusions were provided in some areas. Specific data or facts were not referred when necessary to support the analysis and conclusions. Grammar, spelling, punctuation, professional writing, and syntax needs improvement. The document is partially referenced, reference list or in text referencing is missing. Effective conclusions were partially provided. Specific data or facts were occasionally referred when necessary to support the analysis and conclusions.
Answered Same DayAug 20, 2020STAT6003Torrens University Australia

Answer To: ASSESSMENT BRIEF Subject Code and Title STAT6003 : Statistics for Financial Decisions Assessment...

Pooja answered on Aug 21 2020
142 Votes
data_sydney
    Market Price ($000)    Sydney price Index    Annual % change    Total number of square meters    Age of house (years)
    630    78.2    0    160.5    35
    651    87.5    11.9    248.9    45
    699    84.1    3.9    155.3    20
    768    81.6    3    240.4    32
    739    83.6    2.5    188.4    25
    779    89.1    6.6    155.8    14
    749    85.8    3.7    174.8    8
    780    97.8    14    310.5    10
    790    102.2    4.5
    168.2    28
    834    100    2.2    247    30
    795    104.4    4.4    182    2
    839    120.4    15.3    214.3    6
    797    140    16.3    212.1    14
    845    157.3    12.4    248.5    9
    960    175.4    11.5    230    1
    MLR
    SUMMARY OUTPUT
    Regression Statistics
    Multiple R    0.889164809
    R Square    0.7906140576
    Adjusted R Square    0.7068596807
    Standard Error    43.887826148
    Observations    15
    ANOVA
        df    SS    MS    F    Significance F
    Regression    4    72728.5871600699    18182.1467900175    9.4396745146    0.001993481
    Residual    10    19261.4128399301    1926.141283993
    Total    14    91990
        Coefficients    Standard Error    t Stat    P-value    Lower 95%    Upper 95%    Lower 95.0%    Upper 95.0%
    Intercept    548.97810799    81.1315373855    6.7665192314    0.0000494032    368.20577742    729.75043856    368.20577742    729.75043856
    Sydney price Index    1.9634938944    0.5832054715    3.3667274922    0.007160758    0.6640311247    3.2629566641    0.6640311247    3.2629566641
    Annual % change    -5.6222042364    3.2401093568    -1.7351896548    0.1133617291    -12.8416177788    1.5972093061    -12.8416177788    1.5972093061
    Total number of square meters    0.5191456286    0.3239087996    1.60275247    0.1400714583    -0.2025681523    1.2408594095    -0.2025681523    1.2408594095
    Age of house (years)    -2.4878659702    1.129750872    -2.2021368001    0.0522517376    -5.0051077812    0.0293758408    -5.0051077812    0.0293758408
    SLR
    SUMMARY OUTPUT
    Regression Statistics
    Multiple R    0.3132497712
    R Square    0.0981254192
    Adjusted R Square    0.0287504514
    Standard Error    79.8861895699
    Observations    15
    ANOVA
        df    SS    MS    F    Significance F
    Regression    1    9026.5573080297    9026.5573080297    1.4144211136    0.2555933004
    Residual    13    82963.4426919703    6381.8032839977
    Total    14    91990
        Coefficients    Standard Error    t Stat    P-value    Lower 95%    Upper 95%    Lower 95.0%    Upper 95.0%
    Intercept    659.1430407968    101.222089162    6.5118497973    0.000019669    440.4660120295    877.8200695641    440.4660120295    877.8200695641
    Total number of square meters    0.5636032735    0.4738971988    1.1892943764    0.2555933004    -0.4601893812    1.5873959282    -0.4601893812    1.5873959282
scatterplots_sydney
    Market Price ($000)    Sydney price Index    Annual % change    Total number of square meters    Age of house (years)
    630    78.2    0    160.5    35
    651    87.5    11.9    248.9    45
    699    84.1    3.9    155.3    20
    768    81.6    3    240.4    32
    739    83.6    2.5    188.4    25
    779    89.1    6.6    155.8    14
    749    85.8    3.7    174.8    8
    780    97.8    14    310.5    10
    790    102.2    4.5    168.2    28
    834    100    2.2    247    30
    795    104.4    4.4    182    2
    839    120.4    15.3    214.3    6
    797    140    16.3    212.1    14
    845    157.3    12.4    248.5    9
    960    175.4    11.5    230    1
        0.80347    0.40583    0.31325    -0.67792
scatterpot
Market Price ($000)    35    45    20    32    25    14    8    10    28    30    2    6    14    9    1    630    651    699    768    739    779    749    780    790    834    795    839    797    845    960    Age of house (years)
Market Price ($000)
scatterpot
Market Price ($000)    160.5    248.9    155.30000000000001    240.4    188.4    155.80000000000001    174.8    310.5    168.2    247    182    214.3    212.1    248.5    230    630    651    699    768    739    779    749    780    790    834    795    839    797    845    960    Total number of square meters
Market Price ($000)
scatterpot
Market Price...
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