Definition Records

These versioned records supply the short explanations in CEDAR and the user guides. Each record states the population, counting unit, numerator, denominator, campus scope, time window, exclusions, limitations, and implementation references.

The app reads the records shipped with its checkout, not the live website. Its Definition v… links point to that exact version here. Older versions remain available when definitions change. A definition version is not a data snapshot, model version, or certification that every implementation issue has been fixed. Known discrepancies are stated explicitly. Local scope notes still describe the actual filters, data edges, and exclusions for a particular run.

Class-list registered enrollment

Version 1.0.0 (current)

Distinct students still registered in the selected class-list group when the extract was pulled; only RE, RS, and RR statuses count.

Population
Class-list records within the selected course, term, and other filters.
Unit
Student within a course/section and term; adding course counts can count a person more than once.
Numerator
Distinct registered students within each reporting group.
Denominator
Not applicable to this count.
Campus
Course delivery campus, not student home campus.
Time window
The extract date for each term; settled reports use the enrollment-complete edge.
Exclusions
Waitlists and all drops are excluded from registered enrollment.

Limitations and implementation caveats

  • This is a snapshot, not a frozen census count. It describes final enrollment only after the term is complete.

Implementation references (paths relative to the CEDAR repository)

  • R/branches/enrl.R: calc_cl_enrls()

Related user guide →

DESR enrollment and available seats

Version 1.0.0 (current)

Section enrollment and available seats describe the retained DESR snapshot; crosslist handling depends on the displayed grouping.

Population
Selected section records in cedar_sections.
Unit
Section or aggregated course/term group, not institution-wide unique students.
Numerator
DESR enrollment; available seats are scheduled capacity minus enrollment under the section/crosslist rules.
Denominator
Capacity for a fill rate; otherwise not applicable.
Campus
Course delivery campus.
Time window
One retained snapshot per term, dated by as_of_date.
Exclusions
Filters and home/crosslist handling determine which sections contribute; check the local section scope.

Limitations and implementation caveats

  • Current registration and post-term history are different lifecycle snapshots and should not be treated as comparable census freezes.

Implementation references (paths relative to the CEDAR repository)

  • R/branches/enrl.R: get_enrl()

Related user guide →

Reconstructed census enrollment

Version 1.0.0 (current)

Class-list registered enrollment plus late drops (DG/DW) estimates the population that stayed beyond the early-drop period.

Population
Class-list course/term groups within the selected scope.
Unit
Registered and late-drop students within each reporting group.
Numerator
registered + dr_late, using the shared enrollment helper.
Denominator
Not applicable to the count; divide by capacity only for an explicitly labeled fill measure.
Campus
Course delivery campus, kept in the course key.
Time window
Derived from each term's retained class list; the enrollment-complete edge bounds settled reporting.
Exclusions
Early drops (DR/DD) and waitlists are excluded.

Limitations and implementation caveats

  • No census-frozen count exists in the source. This reconstruction does not recover registration dates or actual peak occupancy.

Implementation references (paths relative to the CEDAR repository)

  • R/branches/enrl.R: add_census_enrl(), calc_census_enrl_baselines()

Related user guide →

Course DFW / nonpassing rate

Version 3.0.0 (current)

The share of classified course attempts that did not pass. By default only A+ through C, CR, and passing retake equivalents pass; non-audit late drops count as DFW. AUD is excluded even with late-drop status. Each term's attempt counts separately, even when a section number (CRN) is reused.

Population
Registered or late-drop, non-audit course attempts with an observable outcome in the selected scope.
Unit
One attempt per student, term, delivery campus, college, and section number (CRN); repeats in later terms remain separate.
Numerator
Nonpassing attempts, including C-, D-range, F, W, I, NC, NR, P, S, unfamiliar recorded non-audit grades, and non-audit late drops.
Denominator
Passing plus nonpassing classified attempts; rates are pooled counts rather than an unweighted mean of section percentages.
Campus
Course delivery campus under the visible filters.
Time window
Grade outcomes are bounded by last_graded; later enrollment follow-up uses its own observation edge.
Exclusions
AUD is excluded from numerator and denominator regardless of registration status, including DG/DW. Early drops never count as DFW. Blank/NA grades are excluded unless late-drop status supplies the withdrawal outcome.

Limitations and implementation caveats

  • A visible opt-in control may also count C- and D-range work as passing; it does not make P or S pass.
  • Rates from versions before 2.0.0 may differ because reused section numbers could suppress later-term attempts.
  • Before 3.0.0, some outcome paths counted late-drop AUD as DFW. Saved outcomes must be rebuilt under the corrected policy; older files are rejected rather than silently reused.

Implementation references (paths relative to the CEDAR repository)

  • R/branches/course-attempts.R: prepare_course_attempts(), classify_attempt_outcomes(), get_course_outcome_rates()
  • R/trunk/utils.R: classify_enrollment_outcomes(), validate_cedar_grades_policy()

Related user guide →

Version 2.0.0

The share of classified course attempts that did not pass. By default only A+ through C, CR, and passing retake equivalents pass; late drops count as DFW. Each term's attempt counts separately, even when a section number (CRN) is reused.

Population
Registered or late-drop course attempts with an observable outcome in the selected scope.
Unit
One attempt per student, term, delivery campus, college, and section number (CRN); repeats in later terms remain separate.
Numerator
Nonpassing attempts, including C-, D-range, F, W, I, NC, NR, P, S, unfamiliar recorded non-audit grades, and late drops.
Denominator
Passing plus nonpassing classified attempts; rates are pooled counts rather than an unweighted mean of section percentages.
Campus
Course delivery campus under the visible filters.
Time window
Grade outcomes are bounded by last_graded; later enrollment follow-up uses its own observation edge.
Exclusions
Early drops never count as DFW. Blank grades without a late-drop outcome and audits are excluded by policy.

Limitations and implementation caveats

  • A visible opt-in control may also count C- and D-range work as passing; it does not make P or S pass.
  • Rates from versions before 2.0.0 may differ because reused section numbers could suppress later-term attempts.
  • Audit issue awaiting correction — late-drop AUD handling differs between classifiers. Audit exclusions are not fully reconciled.

Implementation references (paths relative to the CEDAR repository)

  • R/branches/course-attempts.R: prepare_course_attempts(), get_course_outcome_rates()
  • R/trunk/utils.R: classify_enrollment_outcomes()

Related user guide →

Version 1.0.0

The share of classified course attempts that did not pass. By default only A+ through C, CR, and passing retake equivalents pass; late drops count as DFW.

Population
Registered or late-drop course attempts with an observable outcome in the selected scope.
Unit
Course attempt, not unique student across a multi-term history.
Numerator
Nonpassing attempts, including C-, D-range, F, W, I, NC, NR, P, S, unfamiliar recorded non-audit grades, and late drops.
Denominator
Passing plus nonpassing classified attempts; rates are pooled counts rather than an unweighted mean of section percentages.
Campus
Course delivery campus under the visible filters.
Time window
Grade outcomes are bounded by last_graded; later enrollment follow-up uses its own observation edge.
Exclusions
Early drops never count as DFW. Blank grades without a late-drop outcome and audits are excluded by policy.

Limitations and implementation caveats

  • A visible opt-in control may also count C- and D-range work as passing; it does not make P or S pass.
  • Audit issue awaiting correction — course-attempt deduplication omits term, and late-drop AUD handling differs between classifiers. Multi-term rates and audit exclusions are not fully reconciled.

Implementation references (paths relative to the CEDAR repository)

  • R/branches/course-attempts.R: prepare_course_attempts(), get_course_outcome_rates()
  • R/trunk/utils.R: classify_enrollment_outcomes()

Related user guide →

Program headcount

Version 2.0.0 (current)

Unique students with matching Academic Studies program records in each term. Combined major, minor, and concentration filters require membership in the same term.

Population
Program records within the selected student campus, college, department, and displayed level; active major/minor/concentration filters must all match the same student and term.
Unit
Student per term within each displayed program group.
Numerator
Distinct student IDs meeting every active program filter in that term; multiple selections within one filter mean any of those selections.
Denominator
Not applicable to this count.
Campus
Student campus on program records; the dashboard has a separate campus exception.
Time window
Observed program terms within the report's displayed window. A program held only in an earlier or later term does not qualify a student in the displayed term.
Exclusions
Records outside the institutional and program filters are excluded. Active program filters also exclude missing student IDs or terms. Combined filters display the primary selected program type (major, then minor, then concentration); secondary filters restrict membership. Multiple groups are not additive unique headcounts.

Limitations and implementation caveats

  • Department is a program-row filter. Leave Department unselected when combining programs from different departments.
  • Same-term membership means the declarations appear in the same Academic Studies term; it does not establish exact dates of overlap within that term.
  • This is an exploratory program-record count, not a certified institutional headcount.

Implementation references (paths relative to the CEDAR repository)

  • R/branches/headcount.R: filter_programs_by_opt(), get_headcount()

Related user guide →

Version 1.0.0

Unique students with matching Academic Studies program records in each term, rather than students sitting in a department's courses.

Population
Program records selected by department, major, minor, concentration, level, and campus filters.
Unit
Student per term within each displayed program group.
Numerator
Distinct student IDs with matching program records.
Denominator
Not applicable to this count.
Campus
Student campus on program records; the dashboard has a separate campus exception.
Time window
Observed program terms within the report's displayed window.
Exclusions
Records outside the selected program types and filters are excluded. Multiple groups are not additive unique headcounts.

Limitations and implementation caveats

  • Combined major/minor/concentration filters currently intersect students across their available history, not within the same term. They do not establish simultaneous program membership.
  • This is an exploratory program-record count, not a certified institutional headcount.

Implementation references (paths relative to the CEDAR repository)

  • R/branches/headcount.R: filter_programs_by_opt(), get_headcount()

Related user guide →

Dashboard program headcount

Version 1.0.0 (current)

Dashboard headline headcounts describe departmental major and second-major program records in the selected term; course activity is counted separately.

Population
Academic Studies program records mapped to the selected department.
Unit
Distinct student within the displayed level/program category and term.
Numerator
Students with matching Major or Second Major records; degree and second-major breakdowns use their labeled subsets.
Denominator
Not applicable to the headcount; change percentages use the indicated comparison term's count.
Campus
Program headcounts are not filtered by the dashboard's course-campus control. Course metrics are.
Time window
Selected dashboard term and the comparison terms shown on the cards.
Exclusions
Students merely taking departmental courses without a matching program record are not part of these headcounts.

Limitations and implementation caveats

  • A campus change can alter course activity without changing the headline program count.

Implementation references (paths relative to the CEDAR repository)

  • R/features/dept-dashboard.R: get_headcount_summary()

Related user guide →

Pathways population

Version 1.0.0 (current)

A selected group of students built from observed program or demographic records, with outcomes defined relative to the selected programs.

Population
Students matching the selected majors, department, preset group, or demographic criteria.
Unit
Student in the population; downstream analyses can use attempts, terms, or change events.
Numerator
Matched students in the displayed outcome or entry category.
Denominator
The selected population for population percentages, unless the local analysis specifies a different eligible group.
Campus
Student campus defines population membership; course-campus filters separately define course exposure.
Time window
Available program/enrollment history through the analysis edge. relevant_until limits attribution after departure from the selected unit.
Exclusions
Program scope, level, and outcome selections determine inclusion; per-analysis eligibility can further reduce the population.

Limitations and implementation caveats

  • First observed enrollment is not a formal admission date. The coverage panel reports incomplete starts and outcomes still in progress.

Implementation references (paths relative to the CEDAR repository)

  • R/branches/population.R: build_population()
  • R/branches/pathways.R: apply_pathways_population_window()

Related user guide →

Course timing

Version 1.0.0 (current)

When the selected population takes each course, using classification by default, reconstructed attempted-credit bands, or relative enrolled term.

Population
Selected Pathways students with eligible course records and usable positions on the chosen axis.
Unit
Student within a course and timing position.
Numerator
Distinct students taking a course at the displayed position.
Denominator
By default, distinct eligible students reaching that position, computed before subject/course filtering. The explicit population option instead divides by all selected population IDs.
Campus
Population membership uses student campus; course records use the separate course-campus filter.
Time window
Observed course history through the analysis edge, respecting each student's population window.
Exclusions
Credit axes drop unknown/invalid timelines and report the excluded count. The four-way classification axis excludes classifications outside Freshman/Sophomore/Junior/Senior.

Limitations and implementation caveats

  • Relative term measures observed time at UNM, not total degree progress. Starting-classification filters can restrict incomplete histories.
  • The axis-specific note beneath the chart describes the measure used in that run.

Implementation references (paths relative to the CEDAR repository)

  • R/cones/pathway.R: get_course_timing()

Related user guide →

Historical credit position

Version 1.0.0 (current)

Per-term credit positions are reconstructed from class-list credit histories; pull-stamped Banner cumulative totals are not historical positions.

Population
Students with term-credit histories and a valid observed start inside the data window.
Unit
Student and term, explicitly entering or after the term.
Numerator
Running attempted or completed UNM credits as labeled. Total attempted credits add a recovered transfer-credit block.
Denominator
Not applicable to a credit position; aggregate medians use only eligible positions.
Campus
UNM history can include courses across campuses even when the selected population has a narrower home-campus scope.
Time window
Entering excludes the term itself; after includes it. Neither recovers missing pre-window coursework.
Exclusions
timeline_valid must be true; missing or invalid credit positions are excluded and counted in the local scope note.

Limitations and implementation caveats

  • The transfer block is inferred from contemporaneous overall minus institutional attempted credits and assumed present at entry; its actual arrival dates are unavailable.
  • A valid observed start is a data-window rule, not proof of a complete transcript.

Implementation references (paths relative to the CEDAR repository)

  • R/branches/credit-timeline.R: build_credit_timeline(), attach_credit_position()

Related user guide →

Roadblocks stop-out comparison

Version 1.0.0

Compares the DFW-versus-pass stop-out gap for the selected population with the same gap for other students taking that course.

Population
Students with classifiable outcomes and an observable next-term window in the selected course scope.
Unit
Outcome record for rates and tests; displayed group counts use distinct students.
Numerator
Outcome records flagged as stopped out under the next-term return rule.
Denominator
Eligible outcome records in each DFW/pass group.
Campus
Course scope selects exposure; return is checked across UNM, including other campuses.
Time window
Course outcomes through the grade edge, with follow-up through the separate enrollment observation edge.
Exclusions
Unobservable follow-up and outcomes outside the population window are excluded; thresholds suppress small groups.

Limitations and implementation caveats

  • Repeaters can contribute multiple records and appear in both outcome groups. The current chi-square calculation does not adjust for that dependence.
  • Return includes registered or late-drop next-term records, unlike the registered-only enrollment lookup used by Course Dynamics retention. This is an association, not a causal course effect.

Implementation references (paths relative to the CEDAR repository)

  • R/cones/stopout.R: get_stopout(), compute_stopout_for_group(), build_next_term_lookup()

Related user guide →

Version 2.0.0 (current)

Compares the DFW-versus-pass stop-out gap for the selected population with the same gap for other students, using each student's first eligible observed outcome in a course and campus.

Population
Students with classifiable outcomes and an observable next-regular-term window in the selected course scope and population window.
Unit
One observation per student, course, and delivery campus; the same observations supply counts, rates, DFW context, and tests.
Numerator
Selected students without registered or late-drop enrollment anywhere at UNM in the next fall or spring, except those with a degree in the outcome term.
Denominator
Selected students in each mutually exclusive first-outcome DFW/pass group. DFW context divides the DFW count by the combined DFW and pass counts.
Campus
Outcomes are compared separately by course delivery campus; return is checked across UNM, including other campuses.
Time window
Apply course filters, the population window, the grade edge, and complete next-term follow-up eligibility before choosing the first observed outcome.
Exclusions
Later outcomes do not add observations. Agreeing first-term records collapse to one; conflicting first-term outcomes exclude that student-course-campus comparison. Coverage notes report these counts and invalid records before size thresholds.

Limitations and implementation caveats

  • First eligible observed does not mean first lifetime attempt. The result describes first outcomes within the available, selected window, not repeat-attempt outcomes or permanent departure.
  • The chi-square test uses Yates correction within each population, not a test of the difference between population and baseline gaps. At least five students per outcome group does not guarantee adequate expected cell counts; p-values are unadjusted across courses.
  • Return includes registered or late-drop next-term records, unlike the registered-only lookup used by Course Dynamics retention. Students receiving a degree in the outcome term are counted as completed rather than stopped out.
  • Impact is the positive excess gap multiplied by the population DFW count, using unrounded proportions. It is a descriptive ranking score, not an estimate of students lost because of a course. These are associations, not causal course effects.

Implementation references (paths relative to the CEDAR repository)

  • R/cones/stopout.R: get_stopout(), select_stopout_observations(), compute_stopout_for_group(), build_next_term_lookup(), prepare_roadblock_results()

Related user guide →

Course retention over time

Version 1.0.0 (current)

Among students registered in a course, retention means registered enrollment anywhere at UNM in the follow-up term or a degree awarded within the follow-up window.

Population
Students with registered status in the selected course and anchor term. This record describes the Retention Over Time tables, not every outcome-split persistence view.
Unit
Student within an anchor course/term cohort.
Numerator
Students registered at UNM in the target term or graduating between the anchor and target terms.
Denominator
Eligible cohort students with an observable follow-up window.
Campus
Course delivery campus selects the cohort; follow-up spans all UNM campuses.
Time window
The selected next regular term or year-later window must be observable through the enrollment-complete edge; grade splits also use last_graded.
Exclusions
Future follow-up is missing, not zero. Late-drop-only follow-up records do not count as registered return.

Limitations and implementation caveats

  • This is a course cohort, not the first-time degree-seeking cohort used for official institutional retention reporting.
  • Differences between pass and DFW groups do not establish that a course caused departure.

Implementation references (paths relative to the CEDAR repository)

  • R/cones/course-retention.R: get_retention_trend()

Related user guide →

Course sequence comparison

Version 1.0.0

Compares outcomes in course Y between students who passed course X in an earlier term and students with no observed prior pass in X.

Population
Students with an eligible first classifiable Y outcome and the required program/context records.
Unit
Student at the first eligible course-Y outcome.
Numerator
Nonpassing Y outcomes within each prior-X group.
Denominator
Classified Y outcomes in that comparison group.
Campus
Selected course-campus scope defines observed X and Y exposure.
Time window
X must precede Y in term order. Matching context must precede the outcome; current GPA is descriptive only.
Exclusions
Same-term X passes do not count as prior passes. Required context and optional filters can remove students.

Limitations and implementation caveats

  • No observed prior pass does not mean never exposed to X. Unobserved earlier or external courses are unknown.
  • Group comparisons are observational. Balance diagnostics are not matching or proof of causality; the existing green balance label needs reconciliation with its stricter explanatory threshold.

Implementation references (paths relative to the CEDAR repository)

  • R/cones/course-impact.R: get_course_sequence_effect()

Related user guide →

Version 2.0.0 (current)

Compares outcomes in course Y between students who passed course X in an earlier term and students with no observed prior pass in X. Balance diagnostics classify measured standardized differences as small below 0.10, review from 0.10 through 0.25, or substantial above 0.25.

Population
Students with an eligible first classifiable Y outcome and the required program/context records.
Unit
Student at the first eligible course-Y outcome.
Numerator
Nonpassing Y outcomes within each prior-X group.
Denominator
Classified Y outcomes in that comparison group.
Campus
Selected course-campus scope defines observed X and Y exposure.
Time window
X must precede Y in term order. Matching context must precede the outcome; current GPA is descriptive only.
Exclusions
Same-term X passes do not count as prior passes. Required context and optional filters can remove students. An active HS GPA range excludes students without HS GPA.

Limitations and implementation caveats

  • No observed prior pass does not mean never exposed to X. Unobserved earlier or external courses are unknown.
  • Balance bands summarize measured continuous and binary covariates only. Categorical distributions require direct review, and an unavailable SMD is not evidence of a small difference.
  • The 0.10 and 0.25 thresholds are descriptive review aids. They do not match students, adjust the outcome comparison, establish comparability on unmeasured factors, or prove causality.
  • Restricting both groups to the same HS GPA range is a sensitivity check, not an adjustment for other observed or unobserved differences.

Implementation references (paths relative to the CEDAR repository)

  • R/cones/course-impact.R: get_course_sequence_effect()
  • R/branches/comparison.R: build_comparison(), classify_smd_balance(), summarize_smd_balance(), compute_balance()

Related user guide →

Class-list waitlist demand

Version 2.0.0 (current)

Waitlists, Regstats, and the Department Dashboard count distinct WL students after removing anyone already registered in the same course-title, term, delivery-campus, college, and part-of-term scope.

Population
Class-list enrollment records in the selected course and term scope after the shared excluded-course list is applied.
Unit
Student within course title, term, delivery campus, and available college/part-of-term keys.
Numerator
Distinct WL students remaining after matching RE/RS/RR records are removed.
Denominator
Not applicable to the count; composition percentages use the remaining waitlisted population.
Campus
Course delivery campus is part of the matching key; this is not a university-wide search for any alternative seat.
Time window
The retained class-list snapshot for the selected term. Waitlist status is most informative during active registration.
Exclusions
Students with matching RE/RS/RR registered rows, duplicate waitlist rows within that group, and courses on the shared excluded-course list.

Limitations and implementation caveats

  • Historical pulls can retain only students still waitlisted when the term closed, so a small past-term count is not evidence that earlier demand was small.
  • Waiting is evidence of expressed interest, not proof that a new section will fill.
  • Versions before 2.0.0 did not govern Regstats or the Department Dashboard, which used DESR section-snapshot waitlist counts.

Implementation references (paths relative to the CEDAR repository)

  • R/branches/waitlist-demand.R: get_true_waitlisted_rows(), summarize_waitlist_demand(), get_classlist_waitlist_demand()
  • R/cones/waitlist.R: inspect_waitlist()
  • R/features/regstats.R: get_reg_stats()
  • R/branches/enrl.R: build_high_waitlist_review()

Related user guide →

Version 1.0.0

Waitlists counts WL students after removing those already registered in a matching course group within the selected scope.

Population
Class-list waitlist records in the selected term and course scope.
Unit
Student within course title, term, campus, and available college/part-of-term keys.
Numerator
Distinct waitlisted students remaining after the matching registered records are removed.
Denominator
Not applicable to the waitlist count; composition percentages use the remaining waitlisted population.
Campus
Course delivery campus is part of the matching key; this is not a university-wide search for any alternative seat.
Time window
The class-list snapshot for the selected term.
Exclusions
Matching registered students are removed. Multiple waitlisted sections in the same course group do not imply multiple students.

Limitations and implementation caveats

  • Regstats and dashboard waitlist summaries currently use DESR waitlist counts. They are a different source and grain, so totals need not agree with this view.
  • Waiting is evidence of expressed interest, not proof that a new section will fill.

Implementation references (paths relative to the CEDAR repository)

  • R/cones/waitlist.R: get_true_waitlisted_rows(), inspect_waitlist()

Related user guide →

Registration anomaly screens

Version 4.0.0 (current)

Compares each term with strictly earlier matching offerings. Saturation uses the class-list census proxy over DESR scheduled capacity, drop-volume alerts remain count-based with lifecycle rates for context, and High Waitlists uses shared class-list true demand.

Population
Course groups within selected campus, term, part-of-term, and academic filters. High Waitlists uses class-list groups after the shared excluded-course list is applied.
Unit
Course, course title, term, delivery campus, college, and part-of-term for High Waitlists; the other screens retain the course/term reporting groups defined in 3.0.0.
Numerator
High Waitlists counts distinct WL students after matching registered students are removed. Other numerators retain the enrollment, drop, and saturation definitions from 3.0.0.
Denominator
No denominator applies to High Waitlists. Other denominator and prior population-SD rules retain the 3.0.0 definition.
Campus
Delivery campus and college remain in the waitlist matching key and the other comparison/source-matching keys.
Time window
High Waitlists uses the retained class-list snapshot for the selected term. Other screens use only matching terms strictly before each target for their historical statistics.
Exclusions
High Waitlists requires a true-demand count at least as large as Min Waiting and removes matching registered students, duplicate WL rows, and excluded courses. Other screen exclusions retain the 3.0.0 rules.

Limitations and implementation caveats

  • Waitlist status is a live registration state. Historical pulls can retain only students still waiting when a term closed, and expressed interest does not prove another section will fill.
  • The enrollment, drop, and saturation limitations recorded in 3.0.0 still apply.
  • Versions before 4.0.0 used DESR section-snapshot waitlist counts and a strictly-greater-than threshold for High Waitlists.

Implementation references (paths relative to the CEDAR repository)

  • R/features/regstats.R: get_reg_stats()
  • R/branches/waitlist-demand.R: get_true_waitlisted_rows(), summarize_waitlist_demand()

Related user guide →

Version 3.0.0

Compares each term with strictly earlier matching offerings. Saturation uses the class-list census proxy over DESR scheduled capacity; drop-volume alerts remain count-based and show lifecycle-adjusted rates for interpretation.

Population
Course groups within selected campus, term, part-of-term, and academic filters. Saturation includes only groups that match class-list lifecycle counts to usable DESR scheduled capacity.
Unit
Course, term, delivery campus, college, and part-of-term group; not an individual student's risk.
Numerator
Enrollment and drop alerts use deviation from the prior count mean. Saturation uses class-list registered students plus late drops. Early-drop rate uses early drops; late-drop rate uses late drops.
Denominator
Prior population SD for the count screens; DESR scheduled capacity for saturation; the class-list first-day proxy for early-drop rate; reconstructed class-list census enrollment for late-drop rate.
Campus
Delivery campus and college remain in each course's comparison and source-matching key.
Time window
Only matching terms strictly before each target supply means, population SDs, prior rates, and Terms at Cap. Neither the target nor later terms enter those calculations. Sparklines can show later terms as context.
Exclusions
Count SD screens require at least two prior observations and positive variation. Saturation excludes groups without matched class-list lifecycle counts, groups with unusable capacity, and groups below Min Impacted; source coverage appears in the scope bar. Other display thresholds remain user controlled.

Limitations and implementation caveats

  • These are descriptive screens, not significance tests, forecasts, or control charts. Drop rates explain whether count changes accompany enrollment changes; they do not decide which rows appear.
  • The class-list census numerator is reconstructed from final/current statuses, not a frozen census roster. Capacity comes from the DESR snapshot, so source dates can still differ and the result is not peak occupancy or registration speed.
  • Early-drop rate divides by registered plus all drops, a first-day/ever-registered proxy that can include registration churn. Late-drop rate divides by registered plus late drops, the reconstructed census proxy. Historical rate is the mean of prior offering rates, not a pooled rate.
  • The Saturation table includes Running hot or Chronically full courses. Full now labels their current fill; by itself it does not add a course to the table.
  • Versions before 3.0.0 used DESR enrollment plus class-list late drops as the saturation numerator and did not expose denominator-aware rate context for count-selected drop alerts. Earlier saved results must not be reused.

Implementation references (paths relative to the CEDAR repository)

  • R/features/regstats.R: get_reg_stats(), get_regstats_baseline_info()
  • R/branches/enrl.R: add_classlist_lifecycle_enrl(), capacity_saturation_metrics(), calc_census_enrl_baselines()
  • R/trunk/history-stats.R: prior_history_stats(), add_prior_history_stats()

Related user guide →

Version 2.0.0

Compares each term with strictly earlier offerings of the same course, season, and part of term. Enrollment, drop-count, and fill screens use the mean and population standard deviation from the same prior observations.

Population
Course groups within selected campus, term, part-of-term, and academic filters; each term in a multi-term run has its own earlier baseline.
Unit
Course, term, delivery campus, college, and part-of-term group; not an individual student's risk.
Numerator
Deviation from the prior mean; Outside SD subtracts Min SDs times the prior population SD from the directional enrollment deviation or absolute drop-count deviation.
Denominator
Prior population SD (square root of the mean squared deviation from the prior mean, using n) for SD units; scheduled capacity for fill. Early/late-drop screens compare counts, not rates.
Campus
Delivery campus and college remain in each course's comparison key.
Time window
Only matching terms strictly before each target supply its mean, SD, and Terms at Cap. Neither the target nor later terms enter those calculations. Sparklines can show later terms as context.
Exclusions
SD screens require at least two prior observations and positive historical variation; unscored comparison counts appear in the scope bar. Minimum impacted, waitlist, fill, and historical-evidence thresholds control displayed rows. Saturation history also applies the enrollment-size floor.

Limitations and implementation caveats

  • These are descriptive screens, not significance tests or forecasts. Two prior terms permit a calculation but provide limited evidence; missing and flat histories are unscored, not evidence of normal behavior.
  • Saturation still adds class-list late drops to DESR enrollment and divides by DESR scheduled capacity. Snapshot dates can differ; this is not a census freeze or a registration-speed measure.
  • The Saturation table includes Running hot or Chronically full courses. Full now labels their current fill; by itself it does not add a course to the table.
  • Versions before 2.0.0 could use later terms in means and the target in enrollment/drop spreads; saturation used sample SD. Earlier saved results must not be reused.

Implementation references (paths relative to the CEDAR repository)

  • R/features/regstats.R: get_reg_stats(), get_regstats_baseline_info()
  • R/branches/enrl.R: calc_census_enrl_baselines()
  • R/trunk/history-stats.R: prior_history_stats(), add_prior_history_stats()

Related user guide →

Version 1.0.0

Flags enrollment, drop counts, waitlist counts, and fill measures against same-season course history using adjustable thresholds.

Population
Course groups within selected campus, term, part-of-term, and academic filters.
Unit
Course/term reporting group, not an individual student's risk.
Numerator
Deviation of the selected metric from its comparison mean; Outside SD subtracts the chosen SD band from that deviation.
Denominator
The deviation spread for SD units; scheduled capacity for fill. Early/late-drop screens use counts, not drop-rate denominators.
Campus
Course delivery campus remains part of the comparison key.
Time window
Concrete target terms are excluded from comparison means, but later terms can enter the baseline when reviewing an older target.
Exclusions
Minimum impacted, waitlist, fill, and historical-evidence thresholds control which rows are displayed.

Limitations and implementation caveats

  • Enrollment/drop spreads currently include the target in their squared deviations, while saturation uses sample SD. These are not uniformly population SD or purely prior-term baselines.
  • Saturation adds class-list late drops to DESR enrollment. Different snapshot dates can still affect comparability; the result is not a census freeze or a significance test.

Implementation references (paths relative to the CEDAR repository)

  • R/features/regstats.R: get_reg_stats()

Related user guide →

Saved enrollment projections

Version 1.0.0 (current)

Saved Spring projections estimate first-day / ever-registered class-list demand for the pooled Albuquerque and online market; expected census applies historical retention.

Population
Monitored course-market groups in the saved projection bundle.
Unit
Course and target term in the pooled ABQ/EA market.
Numerator
Selected, calibrated demand estimate; planning sections convert demand using the bundle's section-size assumptions.
Denominator
Historical actual demand for error measures; expected section size for the planning-section conversion.
Campus
ABQ and EA are pooled deliberately, not presented as separate campus forecasts.
Time window
The saved target term, as-of term, build timestamp, and historical evaluation windows are displayed from the bundle.
Exclusions
Unmonitored courses and unsupported target seasons are outside this model. Shiny does not fit or select models during a session.

Limitations and implementation caveats

  • Low or None confidence remains visible. Historical accuracy and empirical error ranges do not guarantee future coverage or causal explanations.
  • The definition version describes the metric. The bundle's separate model_version and schema_version identify the actual calculation and artifact format.

Implementation references (paths relative to the CEDAR repository)

  • R/features/enrollment-projections.R: build_enrollment_projection_view(), load_latest_enrollment_projection_bundle()

Related user guide →

Passing-outcome student credit hours

Version 1.0.0 (current)

Dept Trends and dashboard credit-hour histories sum course credits attached to ordinary passing outcomes in the selected scope.

Population
Student-course records passing the credit-hour helper's grade and scope filters.
Unit
Student-course credit hours; one three-credit completion contributes three hours.
Numerator
Sum of credit values on qualifying records.
Denominator
Not applicable to the total; displayed shares use the labeled total.
Campus
Course delivery campus, with department and course-level filters.
Time window
Graded historical terms under the report's displayed window.
Exclusions
Nonpassing, missing, and audit outcomes are excluded. This helper uses passing_grades, the ordinary-grade portion of the DFW pass set, without passing retake variants.

Limitations and implementation caveats

  • This is not all attempted instructional workload or an official earned-credit transcript total.

Implementation references (paths relative to the CEDAR repository)

  • R/branches/credit-hours.R: get_credit_hours()

Related user guide →

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CEDAR is open source software for higher education analytics.