Sample profile first, distributions second: in PHLT 8032's descriptives week, an interpreting paragraph sits beneath each table and names the percentage column behind every quoted figure. Searches like "phlt 8032 week 4 assignment example", "phlt8032 week 4 sample" and "phlt 8032 week 4 example" land here.
What a finished PHLT 8032 Week 4 descriptives write-up looks like
Around three pages, organized by exhibit. The Statistics table opens it, and the paragraph beneath reports valid and missing counts per variable in words, noting that income has the most absent answers. Frequencies output for sex, age group, district, smoking status and insurance follows, gathered into one reformatted table, with the text quoting the Valid Percent column and explaining why: Percent keeps missing answers in the denominator and understates each category. Scale variables come next in a Descriptives table for age, BMI and weekly activity minutes. Activity minutes are heavily right-skewed with a pile at zero, so the paragraph also reports the median and interquartile range from an Explore run and says why the mean alone would mislead. A last paragraph states that the figures describe respondents and are unweighted.
How a PHLT 8032 Week 4 example is structured
The order runs from who is in the file to what their answers look like. A sample paragraph comes first, because every later percentage depends on who answered. Categorical variables follow, then scale variables, then the one variable whose shape changes which summary is honest. Each exhibit sits above the paragraph that reads it, so a reader never meets a table without its sentence. The paragraphs share a pattern: what the table is, the figure that matters, what it means for this county, and anything unusual. The percentage-column explanation appears once, early, and later paragraphs refer back to it. A weighting paragraph closes the write-up, separating a description of respondents from an estimate for the county's adult population, a distinction that returns when the weight is applied in later weeks.
Valid and missing, in words
The Statistics table's counts are restated as sentences. Income's larger missing count is named here, before any income figure appears, so a reader knows those percentages rest on fewer respondents than the rest of the profile.
Which percent is quoted
Frequencies prints Percent and Valid Percent side by side. The write-up quotes Valid Percent throughout and says so once, because counting refusals in the denominator would make every smoking category look smaller than it is.
One table instead of five
Separate Frequencies outputs for five categorical variables are rebuilt as one characteristics table with counts and valid percentages. Raw output moves to an appendix, and the text refers only to the rebuilt table.
Minutes that pile at zero
Weekly activity minutes show a large share of zeros and a long right tail. The paragraph gives the median and interquartile range, reports the mean for comparison, and explains in a sentence why the two sit so far apart.
Respondents, not the county
The closing paragraph says these are unweighted descriptions of people who answered. County prevalence estimates need the survey weight, which is deferred, openly, to a later run.
Where marks go in PHLT 8032 Week 4
Every exhibit is checked for the sentence beneath it, and that check drives much of this week's grade. A write-up with tables pasted in sequence and a summary paragraph at the end has left each table uninterpreted, which most rubrics mark down however accurate the numbers are. Column choice follows closely: quoting Percent when missing values exist produces figures that do not add up across categories, and careful graders test that. The skewed variable carries the analytic share; a mean and standard deviation for activity minutes reported without comment signals that the shape was never examined. Graders favor the rebuilt characteristics table over raw output. The weighting sentence is a smaller criterion, yet claiming county prevalence from unweighted respondent figures is an overreach that draws comment.
Get a PHLT 8032 Week 4 example written to your instructions
Pass along the Week 4 prompt and rubric and list the variables your section wants profiled. A descriptives write-up with a paragraph under every table, and the percent column named, arrives within 24-48h; your first is free. It profiles an invented county sample, so none of its figures will match your output.
PHLT 8032 Week 4 questions, answered
Is the mean worth reporting for a skewed variable at all?
Usually yes, beside the median, with a sentence explaining why they differ. The mean is still useful for totals and for comparison with published figures, and some later procedures work with it. What loses credit is the mean standing alone for a variable where most values sit well below it. Reporting both, and saying which describes a typical respondent, answers the question a reader will ask.
How many decimal places belong in a descriptives table?
Enough to support the comparison and no more. Percentages are commonly given to one decimal and means to one or two, following APA style and the precision of the measure itself. BMI to one decimal is reasonable, while ages rarely need any. Keep decimals consistent within a column, which matters more to a reader than the exact number chosen.
Can the Explore output replace Frequencies and Descriptives?
For scale variables, Explore often gives more of what the write-up needs: median, interquartile range, plots and extreme values in one place. For categorical variables Frequencies remains the natural source. Many strong write-ups use both and say which table each quoted figure comes from, so a reader checking the output can find the number without searching through every panel.