VCE Data Analytics - U4O1 - Development and Evaluation Hangman

The 103 key terms

1efficiency

How well a solution uses resources such as time, processing, memory, storage and user effort to do its job. An efficient solution is fast, light on memory and storage, and saves the user time.

2Effectiveness

How well a solution does what it was meant to do, giving correct, complete and usable results that meet the requirements and suit its purpose.

3template

A pre-built file with the layout, formulas and formatting already set up, so new data can be entered quickly and consistently every time it is reused.

4clean data

Finding and fixing mistakes in data, like typos, spelling variations, duplicate rows, missing values and impossible values, so the results are correct.

5=TRIM(A2)

A text function that returns a tidy copy of the text in A2 with extra spaces removed. UPPER, LOWER and PROPER work the same way to fix capitals, e.g. =PROPER(A2) gives Mia Chen.

6Sort

Sorting puts the rows of a table in order using the values in one column, like A to Z or smallest to largest, and keeps each row together.

7filter

A filter shows only the rows that match a value you choose and hides the other rows. The hidden rows are not deleted. Clear the filter to see them all again.

8fill handle

The small square at a cell's corner. Drag it down to copy a formula to the cells below. The cell references change row by row, so B2 becomes B3.

10=IF(test, value_if_true, value_if_false)

Checks a test, like B2>=50. Shows the second value if the test is true and the third if it is false. Text results go in quotes, e.g. =IF(B2>=50,"Pass","Fail").

11XLOOKUP

A lookup function that finds a key in one column and returns the matching value from another column, such as a price for a product code. It can show a message if no match is found.

12=SUMIF(range, criteria, sum_range)

Adds only the numbers in sum_range whose matching cell in range meets the criteria, such as the total of all sales for one category.

13pivot table

A tool that summarises a big table by grouping rows under row and column fields, then working out a sum, count or average for each group. Refresh it when the data changes.

14Conditional formatting

A spreadsheet tool that changes a cell's colour or icon automatically when its value meets a rule, so highs, lows and outliers stand out.

15AI prompt

Instructions given to an AI tool. A good one states the data (field names), the chart or summary wanted, the audience and the format, using sample or de-identified data.

16AI-generated data

New data, such as text, images or predictions, created by an AI system. Its quality depends on the data the AI was trained on, so students must verify it before use.

17verify against source data

Check an AI-made chart or summary by comparing its values, labels and totals with the original data. If they differ, correct the prompt and re-run it.

18Responsible generative AI use

Using AI to draft text or images, then checking its output for errors and bias, saying you used the tool, and never typing in personal data.

19=SUM(B2:B10)

A formula that adds up all the numbers in a range of cells. The colon means 'from B2 to B10'. The AutoSum button can type it for you.

20=COUNT(B2:B10)

A spreadsheet formula that counts how many cells in the range B2 to B10 contain numbers. It ignores cells with text or empty cells.

21=COUNTIF(range, criteria)

Counts how many cells in a range match a value or condition, such as "Yes" or ">10". Example: =COUNTIF(C2:C30,"Yes") counts every Yes in C2 to C30.

22=COUNTIF(range,A2)

Used in a frequency table: list each category in column A, then put this beside it to count how many times that category appears in the data range. Copy it down for every category.

23=AVERAGE(B2:B10)

A spreadsheet function that adds up the numbers in cells B2 to B10 and divides by how many there are, to find the mean (the typical value). It is not the total.

24=MEDIAN(B2:B30)

Returns the middle value of the numbers in B2:B30 once ordered. With an even count it averages the middle two. You do not need to sort the cells first.

25=MIN(range) and =MAX(range)

MIN finds the smallest (lowest) value in a range of cells and MAX finds the largest (highest) value. For example, =MAX(B2:B10) shows the top score in cells B2 to B10.

26=MAX(B2:B30)-MIN(B2:B30)

Range is the largest value minus the smallest. It shows how spread out data is, but one outlier can stretch it. Not the same as a cell range like B2:B30.

27=STDEV.S(B2:B30)

Returns the sample standard deviation of the numbers in a range, showing how spread out they are. Use STDEV.P if the range is the whole population.

28standard deviation

A measure of how spread out values are around the mean. A small value means the data is clustered close to the mean. A large value means it is widely spread. It uses the same units as the data.

29statistics.mean(data)

The statistics module calculates descriptive statistics on a list: mean() is the average, median() the middle value, stdev() the spread. Use import statistics first.

30mean vs median

An outlier drags the mean towards it but barely moves the median. If the two differ a lot, the data is skewed, so the median is usually the fairer typical value to report.

31histogram

A chart with touching columns showing how many values fall in each numeric bin. Bins go on the x axis, frequency on the y axis. It shows the shape of the data, unlike a bar chart of categories.

32distribution shape

How values cluster and spread on a histogram: symmetric (bell-shaped), uniform (flat), or bimodal (two peaks), with gaps showing where few or no values fall.

33skew

Data with a longer tail on one side. The tail pulls the mean its way: a right tail is positive skew, a left tail is negative skew, and the median stays nearer the bulk.

34pattern, trend, outlier

Look for patterns and trends in data, like highest, lowest, going up or down. An outlier is a value that stands out from the rest. Compare groups to see differences.

35scatter plot

A chart with one dot per record, using two numeric fields as x and y. The cloud of dots shows if the variables are related, and a dot far from the rest is an outlier.

36trendline

A line fitted through a chart's points that shows the overall direction of the data. A chart tool can add one with its equation, and the R-squared value shows how well it fits.

37=CORREL(range1, range2)

Returns Pearson's r, from -1 to +1, showing the strength and direction of the linear link between two equal-length paired ranges of data.

39correlation is not causation

Two things can rise or fall together without one causing the other. A trend shows a relationship, not the reason, so a hidden third factor may explain both.

40conclusion

A statement that answers a question using evidence from the data, such as numbers. It should only say what the data shows and stay within the data's limits.

41security measures

Controls such as passwords, access control, encryption and backups that protect personal information in a dataset from misuse, loss or unauthorised access.

42security control

A measure that reduces risk by preventing an attack, detecting it or helping recovery. Controls can be technical, physical or procedural, and layering several works best.

43permission

A rule that lets an account read, write or execute a file or resource. Read only views it, write can change or delete it, and execute runs it as a program.

44multi-factor authentication

A login step that asks for a second proof of identity, like a phone code or app prompt, as well as your password. A stolen password alone is not enough.

45Encryption

Turning a readable message into a scrambled, unreadable message using a key, so it can only be read again with decryption.

46Backup strategy

A plan for how and when backups are taken and stored, such as scheduling regular backups and keeping copies in multiple locations.

47task breakdown

Splitting a whole project into small tasks, each with a clear outcome, a time estimate and an order (dependencies), so you can track progress as the work gets done.

48implementation plan

A plan listing each security control with the task, the person responsible, the due date and the resources needed to put it in place, ordered by risk.

49implementation checklist

A list with one security control per line, a yes/no check and evidence, plus who checked and when, used to confirm each control was set up correctly and to fix any failed items.

50control test

Try a security control with a realistic case, like a wrong password or restricted user, then record whether it behaved as expected.

51inclusive content

Content that suits its audience by using plain language, a suitable tone and examples that include different ages, abilities and backgrounds, so everyone can understand it.

52age appropriate

Information is age appropriate when its content, reading level and design suit the age of its audience, including vocabulary, amount of detail, examples and images.

53commonality of language

Using words the audience shares and understands, such as plain English and consistent terms, and avoiding jargon, slang and unexplained abbreviations.

54cultural inclusiveness

Presenting information without stereotypes or assumptions, and respecting the symbols, colours, images, date formats and customs of different cultures.

55gender-inclusive

Information that uses neutral wording, balanced images and fair gender options in forms so no gender is excluded or stereotyped.

56purpose and audience

The reason a visualisation is made and who will view it. Together they decide the content, level of detail, tone and style, so the same data can look different for different audiences.

57Choosing the right chart

Pick the chart that matches your question: a bar chart to compare categories, a line chart for change over time, and a pie chart for parts of a whole.

58long-form infographic

A tall, single-page visualisation that tells one story from start to finish as you scroll down through headed sections of text, graphics and charts.

59poster series

A set of separate infographic posters that share one template and colours, each with one message, linked by a common theme.

60dashboard

A single screen that combines charts, tables and key figures so a viewer can monitor data at a glance, such as sales or attendance.

61slicer

A set of buttons linked to a table, pivot table or chart. Click a button to filter the data, so a viewer can explore it interactively. Clear the filter to show everything again.

62information hierarchy

Ranking information from most to least important and arranging it so the main message is seen first and supporting detail follows in a clear reading order.

63pagination

Dividing content across separate pages or screens in a planned order, so each holds a manageable amount, such as one message per page.

64refresh requirements

Statements of how often, how and by whom the data behind a dynamic visualisation is updated, e.g. a daily automatic refresh from the data source.

65Text and graphics

Titles, headings, captions and key figures (text) plus shapes, pictures and icons (graphics) that frame and explain the data so viewers know what it shows and what matters.

66table

A visualisation component that shows exact values in rows and columns, used when the audience needs the precise numbers. Clear headers and only the rows that matter keep it readable.

67chart

A visualisation component that turns data into shapes such as bars, lines or slices so patterns can be seen quickly. Use one chart per message and place it near its explanation.

68Title, axis labels and legend

The parts that help a viewer read a chart: the title says the topic, axis labels name the data and units, the legend explains colours.

69colour palette

A small, consistent set of colours where each colour has one meaning. Use the same colour for the same category, and never rely on colour alone, so colour-blind viewers can still read it.

70font hierarchy

Using only two or three fonts, with size and weight showing importance from title to heading to body to caption, so a visualisation is easy to read.

71icon

A small simple picture that makes a topic quick to recognise. Keep icons relevant and in one style, use them only where they help the data, and credit or get permission for any you borrow.

72consistent design

Using the same colours, fonts, alignment and spacing on every part of a dashboard or poster series so it looks unified and is easy to read.

73visual hierarchy

Using size, colour, weight and position so the viewer's eye goes to the most important element first, then follows a clear reading order to the rest.

74Clarity of message

When a viewer can state a visualisation's main point in seconds, thanks to a title that states the finding, no clutter, one message per visual and readable labels.

75validation

An automatic check that data is reasonable and in the right form when entered. It blocks bad data early, but it cannot prove the data is true (a valid age of 15 could still be wrong).

76Data Validation

A spreadsheet tool that limits cells to allowed entries, like a whole number from 1 to 100 or a drop-down list, and shows an error message if someone types anything else.

77if name != ""

An existence check tests that the user actually entered something, so the input is not an empty string. len(name) > 0 does the same job. Loop and re-ask until it passes.

78isdigit()

A type check method: returns True if a string holds only digits, so text can be rejected where a number is needed. The alternative is to put int(value) inside try/except.

79if 0 <= mark <= 100:

A range check tests that a number lies between a minimum and maximum. This chained comparison is True only when mark is from 0 to 100 inclusive, so the boundary values 0 and 100 are accepted.

80verification

Checking that data was entered or copied exactly as it appears in the source, such as by double entry or comparing it with the original. It checks accuracy, not reasonableness.

81proofreading

Carefully reading text, labels and figures to find and fix spelling, wording and number errors before you publish your work.

82Integrity

Data stays accurate and unaltered unless an authorised person changes it. Accidental or deliberate changes break it, such as a tampered bank balance.

83End-to-end integrity checking

Following data through every stage, from collection to chart, and confirming at each stage that it is unchanged and correct, for example by matching record counts and totals.

84accuracy

Data is accurate when it is correct and free from errors, so it matches the real-world fact it records. Typos, faulty measurements and out-of-date values make data inaccurate.

85Visual inspection

Looking over a finished visualisation for layout, readability and formatting faults, such as overlapping or cut-off text, hard-to-read labels, poor alignment and spacing, on the target screen.

86representative chart

A chart whose plotted values, axis scales and categories all match the source data, so it shows the data truthfully and does not mislead the viewer.

87misleading chart

A chart whose design, like a cut-off axis, 3D effects or a cherry-picked range, makes the data look different from what it truly shows.

88expected result

The answer you work out by hand using a few rows of data. Compare it with the formula's actual result. If they match, the formula works. If not, check the formula and its range.

89evaluation criterion

A measurable standard used to judge a solution, linked to a requirement and written so it can be answered with evidence, such as a target, a yes/no check or a rating.

90time frame

States when each evaluation activity will happen and how long it has, such as during or after the project, with dates linked to milestones.

91Responsibility

In an evaluation strategy, it names who carries out and reports on each evaluation task, such as the developer, the client or user, or an independent reviewer.

92Evaluation criteria

Measurable standards used to judge how well a finished solution meets its original requirements and purpose

93apply a criterion

Test the solution against a criterion, record the result (met, partly met or not met) and justify the rating with evidence. Recommend improvements if it is not fully met.

94requirements checklist

A list of every functional requirement and success criterion. You test the solution against each one, then record yes or no and note your evidence, such as what you saw or a screenshot.

95user feedback survey

Set questions you ask users after they try your solution. You record their ratings and comments, then sum up the answers to compare with your criteria.

96Gantt chart

A project management tool that shows tasks and their timeframes as horizontal bars along a timeline

97milestone

A marked checkpoint in a project plan, such as a finished prototype, showing a major piece of work is complete by its deadline. Used to check progress.

98Adjusting tasks

Adding, removing, reordering or reassigning tasks when a project changes, and recording each change in the plan so the plan stays accurate and up to date.

99Adjust time frames

Update start dates, durations and deadlines when a task runs long or short, then check the knock-on effect on dependent tasks and work out the revised finish date.

100annotation

A short dated note on a project plan that records what changed and why, and keeps the original plan visible next to the actual dates.

101project log

A record of each work session: the date, what was done, any problems and the next step. It shows actual progress against the plan and evidences why the plan changed.

102role

A job given to one team member with set tasks they are responsible for, so no task is missed and no two people do the same work twice.

103change count

The number of changes made to a project plan, tallied from its annotations. Few changes suggest the plan matched the work well; many suggest it did not.

104avoidable or unavoidable change

A change is avoidable if better planning, such as a poor estimate, could have prevented it. It is unavoidable if it came from outside the developer's control, like new requirements.

105Impact of a change

How much a change affected the finish date, the scope and the quality of the finished solution, such as delay, dropped features and extra effort.