Statistics
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TaskBrief-Finalassignment-BCO127AppliedManagementStatistics-JordiBallart.docxBCO127 Applied Management Statistics Task brief & rubrics
Task: Final
You are asked to answer all the questions in the proposed case.
This is an individual task. All students must submit their own file in the midterm evaluation submission point.
A regression analysis has been conducted between the annual income (in 1000 euros) and the work experience (in years) of people with 0.05 significance level. The results are summarized below.
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Summary |
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Table 1. |
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Regression Statistics |
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Multiple R |
0,93 |
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R Square |
0,86 |
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Adjusted R Square |
0,82 |
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Standard Error |
2,11 |
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Observations |
6 |
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Table 2. |
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df |
SS |
MS |
F |
Significance F |
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Regression |
1 |
107,603 |
107,603 |
24,276 |
0,008 |
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Residual |
4 |
17,730 |
4,432 |
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Total |
5 |
125,333 |
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Table 3. |
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Coefficients |
Standard Error |
t stat |
p value |
Lower 95% |
Upper 95% |
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Intercept |
17,351 |
3,160 |
5,491 |
0,005 |
8,577 |
26,124 |
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Variable X 1 |
1,362 |
0,276 |
4,927 |
0,008 |
0,595 |
2,130 |
Ex. 1. Define the independent and dependent variables. What can you say about the correlation between them?
Ex. 2. Interpret R Square.
Ex. 3. State the hypotheses tested
Ex. 4. Test whether the independent variable have a significant effect on the dependent variable with 0.05 significance level? Write your conclusion.
Ex. 5. Write the regression model and interpret the coefficients.
Ex. 6. Estimate the average annual income of a person who has 15 years of work experience.
Submission: Week 13 – Due 9th May 2020, 23:59 CEST, Via Moodle (Turnitin)
Weight: This task is a 40% of your total grade for this subject, as indicated in the course outline
Submission file format: Word document with all the answers, clearly identifying all steps, results, and including comments for each step.
Formalities:
· Wordcount: 1000 words aprox
· Font: Arial 12 pts.
· Text alignment: Justified.
· The in-text References and the Bibliography have to be in Harvard’s citation style.
This task assesses the following learning outcomes:
· Design and explain statistical models, perform analysis and solve real-world problems.
· Understand concepts, formulas, and techniques of statistics through applied examples.
· Understand statistical language and develop statistical thinking.
· Interpret results of statistical analysis.
Rubrics
