Domain: Natural Science — Statistics & Data Science
Target concept: Irrelevant features: The points in the scatter plot are randomly distributed without a clear trend.

Video generation prompt: Researchers input paired data from two economic variables into a spreadsheet to generate an uncorrelated scatter plot.

Evaluation guide:
Target concept: "Irrelevant features" defined as the visual absence of systematic spatial structure (trend, clustering, orientation) among paired economic data points in a scatter plot. Minimum mechanistic assumptions: (1) Data entry causes plot regeneration; (2) Economic variables obey real-world plausibility constraints (range, units, sign); (3) Human vision perceives irrelevance via isotropy: equal point density in all directions and quadrants. Phased storyline: (Phase 1) User types 25 rows of paired economic values into labeled spreadsheet columns → (Phase 2) On final Enter, scatter plot auto-renders in adjacent pane with matching axis labels → (Phase 3) Static 2-second hold reveals fully dispersed, trendless point cloud, with no line, curve, gradient, or alignment. Visibility constraints: Must show both spreadsheet (with headers and active cell) and plot simultaneously; no occlusion; axis labels must be legible at 1080p; points must be resolvable as discrete entities (not blurred or overlapping).

Manual:
I. Basic Demonstration Information
Demonstration Title: Irrelevant Features in Economic Data — Uncorrelated Scatter Plot Demonstration
Subject: Natural Science - Statistics & Data Science - Exploratory Data Analysis
Demonstration Purpose: To visually demonstrate the statistical concept of "irrelevant features" by generating a scatter plot from paired economic data that exhibits no discernible trend — confirming absence of linear or monotonic association; to train learners in visual pattern recognition for feature relevance assessment.

II. Demonstration Carrier/Equipment
Core Carrier: Spreadsheet software interface (e.g., Excel or Google Sheets) displaying two economic variables; auto-generated scatter plot pane.
Auxiliary Equipment: Clean desktop background; standard keyboard/mouse; screen recording capability.

III. Demonstration Content Description
Layout: Split-screen view — left 60%: spreadsheet with two labeled columns (e.g., "CPI Annual Change (%)" and "Trade Balance (USD Bil)"); right 40%: live-updating scatter plot.
State Control: Input exactly 25 rows of realistic, uncorrelated economic values (e.g., CPI: −1.2, 2.7, 0.9…; Trade Balance: 42.1, −18.3, 65.7…); ensure no sorting, filtering, or formula interference.
Comparison Baseline: Plot must contain *no trend line*, *no correlation statistic*, and *no axis annotations beyond variable names and units* — isolating pure spatial distribution for visual judgment.

IV. Observation of Core Phenomena
Point Distribution Characteristics: All 25 points are evenly dispersed across the plot area with no alignment along any direction; no concentration in quadrants; no gradient in point density; no outliers pulling perceived center.
Trend Absence Verification: Visual inspection reveals zero evidence of linear slope, curvature, monotonic increase/decrease, or clustering — satisfying "randomly distributed without a clear trend".
Stability: Point positions remain fixed after rendering; no animation, jitter, or redraw artifacts; axes retain fixed scale and origin throughout.
Auxiliary Confirmation: Variable names match real-world economic indicators; numeric ranges are empirically plausible (e.g., CPI: −3% to +10%; Trade Balance: −200 to +150); absence of any statistical overlay reinforces irrelevance as primary visual cue.

V. Summary of Key Knowledge Points and Principles
Core Concept Definition: Irrelevant features describe predictor variables exhibiting no systematic relationship with the target variable — visually identifiable in scatter plots as isotropic, trendless point clouds.
Statistical Principle: Zero correlation (r ≈ 0) implies no linear dependence; visual randomness is the first-line diagnostic before quantitative testing.
Domain Significance: In economic modeling, discarding irrelevant features prevents overfitting, improves interpretability, and aligns with Occam’s razor — prioritizing parsimonious, causally grounded models.

VI. Demonstration Precautions
Data Authenticity: Use empirically sourced but synthetically shuffled values (e.g., real CPI series paired with permuted trade balance) to ensure true independence.
Visual Fidelity: Disable all auto-trendlines, smoothing, or confidence bands; use monochrome points (black, size 4, alpha 0.8) to eliminate color-based bias.
Timing: Complete demonstration in ≤12 seconds — typing 25 rows at natural pace (8–10 sec) + immediate plot render (≤0.5 sec) + 1.5 sec static observation.

Prompt Grounding rubric:
level_1: No spreadsheet interface is shown, no scatter plot appears, and no data-entry action is depicted; neither economic variable (e.g., an inflation-type series and an unemployment- or trade-type series) is named or implied anywhere on screen: the scene could be a bar chart, a map, or plain text unrelated to paired economic data.
level_2: A spreadsheet or a plot appears, but not both together, or the two economic variables are never distinctly named (e.g., generic 'X'/'Y' columns instead of something like 'CPI Annual Change (%)' and 'Trade Balance (USD Bil)'); the plotted points visibly hug a line, curve, or tight cluster rather than looking scattered.
level_3: Spreadsheet and scatter plot both appear and two variable names are present in headers or axis labels, but one is vague (e.g., 'Var1') or the two headers are accidentally identical (e.g., both read 'Sales'); the plotted points look mostly scattered but still show a faint diagonal lean or a curved band, so the 'no clear trend' impression is not fully convincing.
level_4: The spreadsheet clearly shows two labeled economic columns (for example 'Inflation (%)' and 'Stock Index Return (%)') with roughly 15–30 numeric row pairs entered; the scatter plot appears promptly with axis labels matching those column headers, and the points form a cloud with no visible slope, curve, or clustering, except for one small blemish, such as a stray gridline that makes the layout look artificially regular, or one axis label that is cut off.
level_5: Every visual element lines up cleanly: the spreadsheet shows an active cell mid-entry under two clearly legible, realistic economic headers (e.g., 'Consumer Price Index Change' and 'Industrial Production Growth'); the scatter plot appears in an adjacent pane or window with x- and y-axis labels matching those headers; roughly 25 points are spread evenly across the plot area with no visible alignment along any line or curve, no lean toward one quadrant, and no thinning or thickening of point density in any region; all points share the same plain color, size, and opacity, and no trend line, correlation value, or annotation is drawn on the plot.

Scientific and Causal Correctness rubric:
level_1: The demonstration scientifically misrepresents the concept: for instance the two spreadsheet columns are headed with a nonsensical or duplicate pairing (such as an indicator plotted against itself, or two headers that name the same variable), the same numeric pair is typed into every row, or the scatter plot is a static image that never visibly reacts to anything typed; any of these falsely implies a relationship (or absence of a real demonstration) that contradicts the idea of two independent economic variables.
level_2: New points do appear on the plot as rows of data are completed, but at least one column's values are not economically credible for the indicator it is labeled with: for example an inflation-style series is typed with entries running into the hundreds of percent, or a rate-type variable (such as unemployment) is entered with negative values where negative readings are not economically meaningful.
level_3: Both columns use believable-looking magnitudes and the plot only updates from typed input, but the two columns are visibly built from one another by a simple fixed rule (e.g., every entry in the second column is consistently about twice the paired first-column entry, or is the same value with its sign flipped), a hidden mechanical link that undercuts the claim that the two variables are independent, even though no line is drawn connecting them.
level_4: Entered values sit within realistic ranges for the two named economic indicators, the plot visibly changes only after a row of data is completed (never before), and the two columns show no shared arithmetic pattern, but the plot carries one unnecessary statistical add-on, such as a faint fitted line, a printed correlation number, or a shaded band, that is not needed for and slightly works against the point that there is no relationship to see.
level_5: Full scientific coherence: both columns' values and ranges are realistic for the named real-world economic indicators; the plot updates only in direct response to completed rows of typed data, never earlier and never on its own; the two columns show no shared formula or derivation from one another; and nothing on the plot (no fitted line, curve, correlation number, or confidence band) asserts a relationship that the underlying data does not actually have.

Spatiotemporal Consistency rubric:
level_1: Spatial or temporal breakdown dominates the scene: the spreadsheet and the scatter plot never appear together in one coherent view, the plot flashes in and out unpredictably, or the scatter plot appears to update at the exact same instant as typing with no perceivable gap between keystrokes and the plot changing.
level_2: Major spatiotemporal flaws remain: the scatter plot visibly starts rendering before the last row of data has finished being typed, the axis labels shift position or change size while the plot is drawing, or the roughly 25 points appear to stream in from one single off-screen direction rather than looking tied to the rows being entered.
level_3: Smaller but noticeable inconsistencies persist: the plot visibly waits well over a second after the last keystroke before it updates, one axis label sits visibly off-center from the axis it is meant to label, the points fade in gradually rather than appearing crisply once the plot updates, or the text cursor blinks at a distractingly fast, unnatural rate while typing.
level_4: Strong spatiotemporal coherence: the spreadsheet and the scatter plot each hold a stable, non-overlapping position on screen throughout the clip; typing proceeds at a natural human pace with smooth cursor movement between cells; the plot updates promptly, well under a second, after the last entry is confirmed; axis labels stay legibly fixed without drifting or resizing; and the roughly 25 points appear as one settled cloud rather than trickling in gradually.
level_5: Full spatiotemporal continuity: the spreadsheet (left portion of the frame) and the scatter plot (right portion) keep a fixed, proportioned, non-overlapping layout with clean, legible axis labels throughout; typed characters appear at a believable human pace, including natural pauses between rows; the scatter plot updates essentially as soon as the last row is confirmed, with all roughly 25 points appearing together in that single update rather than drawing in one at a time or in stages; and the cursor or pointer only ever rests on the actively used cell or the plot pane, with no stray interface elements (notifications, taskbar, etc.) intruding on the scene.