代做统计问题集 STA130H1F代写 STA课业代写 统计作业代写
457STA130H1F – Week 10 Problem Set 代做统计问题集 Instructions How do I hand in these problems for the 11:59 a.m. ET, November 27th deadline? Your complete .Rmd file that you create for this ...
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统计数据分析作业代写 Background: Exoplanets are planets which orbit other stars, like the Earth orbits the Sun. Exoplanet discovery is currently an exciting and
Exoplanets are planets which orbit other stars, like the Earth orbits the Sun. Exoplanet discovery is currently an exciting and growing area of research in astronomy.
The Royal Astronomical Society (RAS) is an organisation which is interested in data about exoplanets. They have asked some astronomers to do observational research to discover exoplanets orbiting distant stars.
Previous theoretical research suggests that a regular, periodic decrease in light intensity detected from a distant star suggests there might be a planet orbiting the star (an exoplanet).
This study is observational, where telescope and satellite data has been collected. The goal is to compare the real, observational data with the three theoretical predictions mentioned above.
The researcher reported that 1 or 2 of the measurements were taken before a fault was detected (and resolved) in the imaging processing. Your analysis must include all possible anomalies and state their possible impact on any conclusions.
The aims of this study include the identification of any statistical links between the variables for both super-massive and sun-like stars, and to link this data with the theoretical predictions in order to provide a focus for future research into finding and identifying exoplanets.
NOTE: theoretical research means research involving mathematical equations and laws (e.g. model behaviour). Observational research means using telescopes to measure (or observe) a behaviour. The two do not always agree.
Any calculations must only use the methods and techniques described to you on this course.
The goal is to present your recommendations clearly so that the Director of the RAS can easily interpret your report. You MUST assume that the researcher and the Director of the RAS has no prior statistical knowledge, therefore care should be taken to fully explain the reasoning behind any analysis.
You should consider categorizing data in some new way that reveals patterns, and consider re-processing the data, perhaps creating a new variable or new tables. Clearly summarize any findings.
Microsoft Excel must be used for the statistical analysis you will perform below. Use of other software is not permitted.
The following must be completed below:
You must include a full numerical summary of the data, which includes:
You must include a critique and explanation of:
which may be present in the study. You must highlight any possible errors in measurement, and any outliers. You must describe their effect on your conclusions.
You must produce 1 graphical representation (with a maximum of two graphs) of the given data from the following options:
[For example, you may choose to have a maximum of 2 boxplots, but any other graphical summaries after this will not be marked.]
Note: More sophisticated graphs will receive more marks.
You must produce:
I. (no more than) two scatter plots
II. (no more than) two least squares regression lines
III. (no more than) two correlation coefficients, and
IV. (no more than) two residual plots.
You must include:
You must include:
I. How you are categorising the data and what 2-sample confidence interval you will use. That is:
II. You must pick two confidence levels, stating clearly what confidence level you will use and why.
III. Full calculations must be included for each interval.
IV. A discussion on the physical interpretation of the two intervals
V. Comments on how the collection method of the data and the quality of the data effects the validity of the intervals.
End of scenario, the study data is below:
Table 1a: Data Recorded for Sun-Like Stars
Distance from Centre of Galaxy (000’s Lt Yrs.) | Decrease inIntensity (%) | Clusterpresent? (Y/N) |
47.17 | 13.86 | Y |
99.43 | 39.84 | Y |
158.07 | 80.81 | Y |
151.70 | 46.19 | N |
131.30 | 39.84 | N |
26.77 | 9.24 | N |
11.47 | 5.20 | Y |
34.42 | 11.55 | N |
8.92 | 6.35 | N |
53.54 | 13.28 | Y |
82.86 | 29.44 | N |
52.26 | 22.52 | N |
49.72 | 21.94 | N |
20.40 | 16.74 | Y |
177.19 | 43.30 | N |
70.11 | 28.87 | N |
87.96 | 29.44 | Y |
65.01 | 20.21 | N |
15.30 | 6.93 | N |
36.97 | 9.81 | N |
28.04 | 7.51 | Y |
Table 1b: Data Recorded for Super-Massive Stars
Distance fromCentre of Galaxy (000’s Lt Yrs.) | Decrease inIntensity (%) | Clusterpresent? (Y/N) |
86.97 | 53.12 | Y |
43.84 | 38.11 | Y |
18.38 | 19.05 | Y |
20.51 | 21.36 | N |
69.30 | 48.50 | N |
77.78 | 56.58 | N |
69.30 | 45.61 | N |
22.63 | 20.21 | Y |
8.49 | 15.01 | Y |
2.83 | 16.17 | N |
45.96 | 27.71 | Y |
20.51 | 19.05 | Y |
42.43 | 36.37 | N |
12.73 | 11.55 | Y |
26.16 | 19.05 | Y |
47.38 | 35.22 | N |
20.51 | 25.98 | N |
57.28 | 44.46 | N |
16.26 | 8.08 | Y |
55.15 | 40.41 | Y |
40.31 | 31.75 | N |
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