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INU1111 Quantitative Methods Summative Assignment

创建日期：2024-07-08 17:11:08

所属分类：数学mathematics

标签： INU1111

Quantitative Methods Summative Assignment

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International Year One in Business

INU1111

Quantitative Methods Summative Assignment

Assignment Part B: Data Analysis Report (75% of final mark)

Distribution and Submission Details

Please Note:

Ø Late or plagiarised assignments will be penalised, marks will be deducted for late submission.

Assignment guidelines:

· Using the assignment background information, your chosen research question and your Data Analysis Plan carry out your data analysis.

· Maximum report size 16 sides of A4, including graphs but excluding front page, contents page, reference lists and Appendices.

Assignment Part B

Assignment Part B: 75% of the module mark.

In the second larger part of the assignment, you will analyse your data in depth using a variety of methods. This analysis must include the following sections.

1.0 Introduction

Introduce the topic, use the introduction you wrote for Assignment Part A as the basis for this section. Make any amendments that were mentioned in the feedback for Part A.

2.0 Sample Method

Provided a detailed explanation of your sample method. Use the sample method you wrote for Assignment Part A as the basis for this section. Include any adjustments you have made (for example, if you have since added to or changed your data based on feedback from Part A).

Your sample method should discuss

· The sampling methodology you have used.

· Your sample sizes

· How you have controlled your sample (e.g., only used certain locations or property types)

· Any limitations in the data that may influence the results.

3.0 Initial analysis of your data

· This is the first part of your analysis. The purpose of this section is to look at your two numerical variables individually, to discuss what is going on with the data and what it tells you about this business situation.

· Look at the distribution of each variable, the central tendency, the spread and investigate extreme values. Discuss the variable, e.g., what does the mean price per night of your sample tell you about your sample?

· Investigate your key variables using summary (descriptive) statistics and graphs. Use the descriptive statistics and graph that you created for Part A as a starting point.

· Expand to include your second numerical variable and a comparison between two groups (for example, comparing locations or food types).

4.0 Regression and Correlation Analysis

· Use simple linear regression and correlation analysis with accompanying graphs to analyse the relationship between your key variables. Discuss your regression equation.

· Test your regression equation and interpret the results.

· Explain whether your independent variable is a good predictor for your dependent variable. Consider the correlation (r) and the coefficient of determination (the R-square value). If the independent variable does not explain 100% of the variation in the dependent variable suggest reasons why this could be the case.

Important Guidance: use a simple regression model in this section, do not use a Multiple Regression Model. The purpose of this section is for you to demonstrate an understanding of how to evaluate patterns on fitted line plots, how to use the residuals to detect problems and how to link all the pieces of the regression together. The aim here is to investigate a relationship between two variables whilst identifying and discussing the problems, not to find the best model.

5.0 Further Analysis

Carry out the hypothesis test assigned to you in Semester 2 Week 7.

6.0 Conclusion

· Summarise your findings from each of the three analysis sections (Initial Analysis, Regression and Further Analysis)

· Reflect on your analysis; did your analysis go to plan or were there issues which caused you to change your analysis.

7.0 References

Include a range of references. These should be in the Harvard Reference format. Each reference should feature in the report as a citation and each citation must have an accompanying reference.

8.0 Appendix

Include a copy of your raw data as a table in an appendix at the end of the report.

Marking Scheme for the Assignment

· Introduction to the topic and explaining the sample selection process in detail (10 marks)

· Initial analysis of your data using summary statistics and graphs (30 marks)

· Calculating the regression equation and correlation coefficient. Discussing the regression equation. Making appropriate comments about the regression and correlation results. Testing the equation and discussing the validity of the regression equation (30 marks).

· Hypothesis test (25 marks).

· Conclusion discussion (5 marks)

Please refer to the Quantitative Methods module handbook for a breakdown of the grade descriptors (what is required to reach each marking band).

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1300A ENGG 1300 OLET1139 STAT 3503 STAT 206 FEM11149 ELEN 4720 COMP20003 SOLA1070 CS574 C11CS LINB29H3 MAST90083 ECON7200 STAT 610 LINB29 DSM-5 COMP3161 EEEN40010 MATH 4431 K353 STA 3386 IERG4300 COMS W4167 ENG5298 AMME 2302 CS3910 COMPSCI 320 STATS 369 GR5242 COSC 328 CSCI435 MGTS1301 INFS2200 COMP3900 CIS 375 Module AE03 COMP3121 CS260 HAM503 MGMT5050 INT3075 COSC 285 GEOL0029 GEGE2X01 STAT1201 MATH1061 MMF1941H STAT 5060 CS 520 COMP 4320 MSIN0104 000T FINS3648 ECMT2160 ECON4003 Phys 129L CSE 142 CS 3130 MGEB01 EECS 340 Finance (20443/20444) ECMM149 COMP5310 EEEN60180 CSC 111 AT2 CSCI 4430 STAB57 MA/CSC 427 MATH322 D100 CSCI544 CITS3004 CI6227 CSE 565 APCO 1P01 852L1 ELEC S411F COMP3207 STATS330 ECON7530 FIT5149 CSI4104 CMPT 371 COMP201 SEHS4696 FI4003 MATH6182 CG1 WS MATH401 MGT 205 QTM 110 COMP 0137 MACE12201 FIT5210 ECE 544 BISM7206 HUDM 6055 ECON3203 STATS 210 MSCI 570 MATH6173 COMPSCI4039 Accounting COM3503 AOE2024 ECON213 PSYC10004 Control Data 100/200A PHIL2617 PHYS3116 MIE250 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