# ANY, U CHOOSE

STEP 1:
● What have you completed since finalizing your project topic and data collection
methodology?
● Have you completed your data collection?
● Did you encounter any unexpected problems?
● What will you be working on between now and when progress report #2 is due?
○ You might need to finish up on your data collection if you have not yet completed
it.
○ For data analysis, you should be planning on some some combination of the
below items to better understand your data but should NOT think you need to use
every one of them:
■ Percents and/or other rates
■ Possible grouping of responses when the variety/range of the answers
you received is too large to be manageable
■ Construction of tables
■ Construction of charts/graphs, some examples of which are:
■ Single-variable graphs include bar/column graphs, pie charts, and
histograms
■ Time series line graphs
■ Two-variable (paired data) graphs include scatter plots,
side-by-side bar/column graphs, and stacked bar/column graphs
■ Calculation of measures of center (mean, median, and/or mode)
■ Calculation of measures of position (percentiles, quartiles)
■ Calculation of measures of variation (range, inter-quartile range, standard
deviation)
■ Calculation of linear correlation and regression coefficients for paired
quantitative variables
The statistical process is described in broad terms in section 1.1 of our course textbook with
literally the rest of the book covering detailed classifications and procedures. So far, how does
your project work compare to what you learned in MyStatLab? Write a paragraph (at least 3
complete sentences) that either summarizes the overall comparison or that highlights some
particular item(s) you found notable. For example, you might describe how your data collection

STEP 2:
At this point you would want to have completed your data analysis and have a reasonable idea
way you “wanted” it to, but that will happen sometimes. Unfortunately, we cannot always be
“right.”

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● What have you completed since submitting progress report 1?
○ Did you complete everything you intended to? If not, was what you completed
enough for you to get to know your data and plan a submission format to share
your data and findings? Is there more you need to do in order to get to know
what your data is telling you?
● What submission format are you most likely to use for the completed project? Instead of the usual research report, have you considered something more exotic, such as a video, a magazine article, or a website? My recommendation is to create a website because of the flexibility it allows you.
○ If you completed your data analysis and have a reasonable understanding of how
your data relates to your project topic, you will need to decide on a format and
put together a project submission.
■ IMPORTANT: You might not need/want to include all of your analysis
items in your submission. For example, if you determined that you
collected data on an irrelevant variable, you might not include any tables
or graphs relating to that variable in your submission. In this case, it
would be best to just to mention somewhere in your submission that you
looked into the variable and did not find it relevant to your topic.
○ If you are not done with your data analysis, what will you do to finish it up then
create a suitable submission by the due date?
■ IMPORTANT: If things did not go the way you “wanted” them to, it is NOT
a good idea to try to re-start your project by collecting new data. For this
class, it is better that you include as a part of your conclusion that the
data collected does not support the position you thought it would.
○ Be sure to take a look at the scoring rubric in the submission and self-evaluation
assignment so you are aware of what is expected in order for you to be eligible
for full credit.
As you did for the first progress report, think about what you have learned in MyStatLab and
what you have learned in your continued work while working on this project. Write a paragraph
(at least 3 complete sentences) that either summarizes the overall comparison or that highlights
some particular item(s) you found notable. For example, you might describe how what you
learned from creating graphs for your data either reinforced or changed your perception of data
presentation as it was covered in chapter 2. Your paragraph might be quite similar to the one
you submitted in the first progress report but since you have going through different parts of the
statistical process, don’t be surprised if you have new insights (and/or frustrations).
work reinforced or changed your perception of sampling as it was covered in MyStatLab.

● All data and variables are correctly described as qualitative or quantitative (SLO 1)
● Where applicable, suspected explanatory and response variables are appropriately
described (SLO 1)
● Appropriate graphs (aka charts) of data for relevant variables are included (SLO 1, 2)
○ For each relevant variable (or pair of variables) there is at least one graph.
○ Graph types are appropriate to the data/variable classifications.
■ Single variable data data can be appropriately displayed in a bar graph,
pie chart, histogram, as well as other types of graphs.
■ Time-series quantitative data can be appropriately displayed in a line
graph as well as other types of graphs.
■ Paired variable data can be appropriately displayed in a scatter plot
(paired quantitative variables), side-by-side or stacked bar graph (paired
qualitative variables), as well as other types of graphs
○ Graphs are constructed and displayed appropriately.
■ Each graph displays the respective data correctly.
■ Each graph is sufficiently and accurately labeled.
■ Each graph is displayed at an appropriate location in the submission.
■ Each graph is adequately described, explained, and/or referenced in the
submission’s narrative.
● Appropriate calculated/identified statistics are included (SLO 1, 3)
○ For each relevant variable, at least one calculated/identified statistic is included.
○ Calculated/identified statistics are appropriate to the data/variable classification.
■ Relative frequencies (equivalently, proportions or percents) are
appropriate for qualitative data.
■ The mean can be an appropriate measure of center for interval and ratio
level data.
■ The median can be an appropriate measure of center for ordinal, interval,
and ratio level data.
■ The mode can be an appropriate measure of center for all data including
grouped data.
■ The range, standard deviation, inter-quartile range, and percentiles are
appropriate for interval and ratio level data.
○ Statistics are calculated/identified and referenced appropriately.
■ Each statistic is correctly calculated/identified using a widely accepted
formula/procedure.
■ Each statistic is appropriately described, explained, and/or referenced in
the submission’s narrative

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