16 Nov After considering the descriptive statistics the career accelerator team is interested in identifying the factors which affect the marks in the excel certification test
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Assessment 2b: Case Business Report (40%)
1. FixIt! ‘Statistical toolbox’
This section of the report is approximately 700 words (guide only, not a word limit).
· After considering the descriptive statistics the career accelerator team is interested in identifying the factors which affect the marks in the excel certification test (i.e. variable ECT_Score). They are more interested in identifying behavioural traits which could affect these scores. These include:
· Number of attempts ( ECT_Num_Attempt, Practice_Num_Attempt); and
· Score of the attempts ( Practice_Score_Max t, Practice_Score_Mean).
Further details of these variables can be found in “Note about the data” in your Assessment 2a Guide.
· To understand whether these factors play an important role, broadly speaking, you will need to (i) formulate a multiple linear regression model (refer to week explaining your choice of variables) and (ii) explain whether the relationship is statistically and/or economically significant. The use of a multiple linear regression (week 4-8), confidence intervals (week 7) and hypothesis testing would help you address this and thus provide evidence for your arguments.
· More specifically, you need to consider relevant factors to understand the relationship between ECT_Score and the behavioural variables incorporating the any control variables which are relevant.
· In addition to interpreting the results of your analysis you will also need to draw to attention issues of causality (Week 7) and confoundment (Week 4) which can impact the conclusions from the analysis.
· As a part of this assessment, assumptions and limitations need to be explicitly identified. e.g., What variable would you want to have in an ideal situation to measure ability in this analysis? Do you have this variable in the dataset? If not (which is often the case in practice: we often don’t have all the ideal data/variables that we need to perform an analysis, and must rely on the data available to us), what variable in the dataset do you have to use as an ability measure? What are the assumptions and limitations of using this variable?]
· For further information about the data please read “Note about the data” (see page 3) for more information about the dataset.
· Once, you have considered the above issues and analysis, you will need to understand its implications and consider the appropriate recommendations for the career accelerator team as they try to improve scores in the excel certification test (as above) as this is the purpose of this report.
,
ECT_Num_Attempt | Practice_Num_Attempt | Practice_Score_Max | Practice_Score_Mean | ECT_Score | ||||||||||
1 | 4 | 640 | 490 | 863 | ||||||||||
1 | 6 | 1000 | 819 | 633 | SUMMARY OUTPUT | |||||||||
1 | 3 | 923 | 859 | 438 | ||||||||||
1 | 2 | 914 | 886 | 807 | Regression Statistics | |||||||||
1 | 6 | 914 | 666 | 914 | Multiple R | 0.2258 | ||||||||
1 | 12 | 942 | 861 | 908 | R Square | 0.051 | ||||||||
1 | 11 | 942 | 831 | 893 | Adjusted R Square | 0.0248 | ||||||||
1 | 3 | 920 | 893 | 890 | Standard Error | 199.8337 | ||||||||
1 | 3 | 800 | 790 | 420 | Observations | 150 | ||||||||
1 | 5 | 257 | 108 | 433 | ||||||||||
1 | 4 | 960 | 930 | 890 | ANOVA | |||||||||
1 | 1 | 857 | 857 | 166 | df | SS | MS | F | Significance F | |||||
2 | 12 | 920 | 753 | 790 | Regression | 4 | 311217.6759 | 77804.419 | 1.9483 | 0.1056 | ||||
1 | 5 | 840 | 552 | 376 | Residual | 145 | 5790360.964 | 39933.5239 | ||||||
2 | 9 | 971 | 457 | 914 | Total | 149 | 6101578.64 | |||||||
1 | 9 | 1000 | 936 | 871 | ||||||||||
1 | 4 | 971 | 657 | 893 | Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | ||
1 | 9 | 1000 | 957 | 850 | Intercept | 527.6046 | 87.3713 | 6.0387 | 0 | 354.9189 | 700.2904 | 354.9189 | 700.2904 | |
1 | 3 | 971 | 914 | 962 | ECT_Num_Attempt | -0.5768 | 52.3573 | -0.011 | 0.9912 | -104.0589 | 102.9053 | -104.0589 | 102.9053 | |
1 | 2 | 880 | 760 | 836 | Practice_Num_Attempt | 3.132 | 5.1642 | 0.6065 | 0.5451 | -7.0749 | 13.3388 | -7.0749 | 13.3388 | |
1 | 7 | 971 | 355 | 871 | Practice_Score_Max | 0.2377 | 0.1535 | 1.5481 | 0.1238 | -0.0658 | 0.5412 | -0.0658 | 0.5412 | |
1 | 8 | 1000 | 515 | 809 | Practice_Score_Mean | -0.0394 | 0.1366 | -0.2885 | 0.7733 | -0.3094 | 0.2306 | -0.3094 | 0.2306 | |
1 | 2 | 1000 | 914 | 829 | ||||||||||
1 | 5 | 923 | 869 | 646 | ||||||||||
1 | 2 | 885 | 771 | 764 | ||||||||||
1 | 4 | 960 | 450 | 376 | ||||||||||
1 | 18 | 884 | 579 | 538 | ||||||||||
1 | 9 | 961 | 743 | 481 | ||||||||||
1 | 3 | 1000 | 897 | 394 | ||||||||||
1 | 4 | 1000 | 928 | 700 | ||||||||||
1 | 1 | 846 | 846 | 485 | ||||||||||
1 | 3 | 971 | 923 | 742 | ||||||||||
1 | 3 | 1000 | 961 | 377 | ||||||||||
1 | 5 | 857 | 737 | 829 | ||||||||||
1 | 1 | 685 | 685 | 366 | ||||||||||
1 | 2 | 360 | 300 | 592 | ||||||||||
1 | 12 | 960 | 583 | 972 | ||||||||||
1 | 4 | 960 | 920 | 820 | ||||||||||
1 | 8 | 971 | 910 | 807 | ||||||||||
1 | 3 | 742 | 466 | 957 | ||||||||||
1 | 5 | 942 | 691 | 831 | ||||||||||
1 | 7 | 942 | 857 | 936 | ||||||||||
1 | 8 | 1000 | 493 | 742 | ||||||||||
1 | 3 | 1000 | 884 | 862 | ||||||||||
1 | 4 | 942 | 871 | 850 | ||||||||||
1 | 6 | 1000 | 809 | 914 | ||||||||||
1 | 1 | 571 | 571 | 167 | ||||||||||
1 | 2 | 800 | 780 | 550 | ||||||||||
4 | 4 | 1000 | 940 | 820 | ||||||||||
1 | 13 | 960 | 745 | 592 | ||||||||||
1 | 5 | 1000 | 994 | 943 | ||||||||||
1 | 5 | 914 | 497 | 807 | ||||||||||
1 | 1 | 85 | 85 | 807 | ||||||||||
1 | 7 | 971 | 787 | 935 | ||||||||||
1 | 5 | 960 | 912 | 754 | ||||||||||
1 | 16 | 961 | 709 | 746 | ||||||||||
1 | 2 | 942 | 942 | 636 | ||||||||||
1 | 6 | 828 | 776 | 700 | ||||||||||
1 | 3 | 1000 | 961 | 243 | ||||||||||
1 | 4 | 1000 | 798 | 769 | ||||||||||
1 | 1 | 920 | 920 | 650 | ||||||||||
1 | 2 | 771 | 728 | 566 | ||||||||||
1 | 12 | 1000 | 871 | 525 | ||||||||||
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