A finished BU 454 Unit 5 distribution and relationship charts set: the shape of a measure shown across records, two measures crossed, and the reading kept honest. Searches like "bu 454 unit 5 assignment example", "bu454 unit 5 sample" and "bu 454 unit 5 example" land here.
What a finished BU 454 Unit 5 distribution and relationship charts looks like
Two families of chart sit in this submission, and each carries a note. The distribution side shows one measure across all the records: a histogram with its interval width stated, or a box summary where several groups have to be compared, and often both when the shape is unusual enough that a summary would hide it. The bin width is treated as a decision rather than a default, and the note says what a wider or narrower choice would have concealed. The relationship side is a scatter of two measures with every point drawn, the axes labeled with units, and no line through the cloud unless the note defends putting one there. Where the points overlap heavily, the design does something about it and says what. A closing paragraph states what the pattern does not establish.
How a BU 454 Unit 5 example is structured
The distribution comes before the relationship because a scatter between two measures whose individual shapes nobody has looked at will be read wrongly, and a single extreme value can bend a cloud that otherwise says nothing. Bin width is declared and its effect demonstrated, since a histogram is the chart most easily made to show whatever the writer wanted, simply by changing where the intervals fall. Box summaries are used where groups are being compared and skipped where a single measure would be better shown in full, because a box hides multiple peaks completely. Every point is plotted on the scatter rather than a summary of them, as the outliers are usually the interesting part of the assignment. Any fitted line is defended in the note or left off. The limits close the document, since a visible pattern is not a cause.
Shape shown before any average
The measure is drawn across all records first, because a mean quoted over a skewed or two peaked measure describes nobody in the file.
Bin width declared as a decision
The interval size is stated and its effect discussed, since moving the boundaries is the easiest way to make a histogram agree.
Box summaries only for group comparison
A box is used where several groups sit side by side and avoided where it would hide a second peak entirely.
Every point drawn on the scatter
Individual records stay visible rather than being summarized away, because the unusual points are normally what the assignment wants noticed.
No fitted line without a defense
A trend line through the cloud appears only when the note argues for it, since the line implies a claim the picture cannot make.
What the pattern cannot establish
The closing states that two measures moving together is a shape on the page and not a demonstrated cause.
Where marks go in BU 454 Unit 5
This one loses points by summarizing the very thing it was asked to show. A table of averages with a chart underneath answers a descriptive question and skips the distribution entirely. Histograms with default intervals, and no comment on what a different width would look like, hand the shape to the software. Box summaries covering a measure with two peaks conceal exactly the finding the assignment planted. Scatter plots drawn from group averages destroy the variation that made the relationship worth looking at. Points removed because they sat far from the cloud discard the observations most likely to carry the point. Trend lines dropped in by default make a claim the writer never argued. Language about one measure driving another crosses into causation. Customer level records taken from work cannot supply the file.
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BU 454 Unit 5 questions, answered
How do I choose the interval width for a histogram?
By trying several and keeping the one that shows the structure without inventing it, then saying in the note what you tried. Very wide intervals flatten a second peak into one hill; very narrow ones turn ordinary variation into spikes. Where your section specifies a rule, follow it and still comment on what the resulting picture does to the shape.
Should I report a correlation figure alongside the scatter?
Only if the instructions ask, and never as a substitute for looking at the cloud. A single coefficient collapses shapes that are nothing alike into the same number, which is why this unit puts the picture first. Where you do report one, put it beside the plot rather than in place of it, and keep the language descriptive.
The clean data I have access to is at work. Can I use it?
Not for a submission. Record level customer or transaction data is the employer's, and the fact that it is convenient and already tidy is exactly why it is protected. Public microdata files published for research give you real distributions with genuine skew and outliers, and the assignment data will usually carry the shape the unit wants examined anyway.