GCSE ICT

1. GCSE ICT Checking data

2. Why do errors happen? Computers do not make mistakes. However if incorrect data is put in errors happen. In ICT this is called GIGO – Garbage in, garbage out! The way to avoid incorrect data being entered is to check it thoroughly.

3. Why do errors happen? There are two main methods of avoiding errors. These are: Verification Validation

4. Verification Verification is the process of checking data. This can be done visually (e.g. by comparing what is on a data capture sheet with what is on screen or with a print out of the data that has been entered). This has the disadvantage that the data on the data capture sheet may be incorrect, and a visual check will not spot this.

5. Verification This can be done by double data entry (i.e. two people enter the same data, and if it is identical the data is accepted). This has disadvantages that this is expensive (two people have to be paid to do the same work) and there is no guarantee that they will not make the same mistakes.

6. Validation Validation is the process of detecting inaccurate, incomplete, or unreasonable data. This can be done by the computer as the data is entered and as a result it is much less likely that errors will occur.

7. Validation There are several ways in which a computer can validate data as it is entered.

8. Validation These include: Character type checks Range checks Presence checks Hash totals Control total Check digits

9. Validation These include: Spelling checkers Custom dictionaries Length checks Lookup tables Parity errors

10. Character type checks Character type checks make sure that the correct type of character has been entered (e.g. that a number has not been entered where a letter should have been or that a letter have not been entered where a number should have been.

11. Range checks Range checks make sure that numerical data falls between pre-determined limits (i.e. within a certain range of numbers). For example, that the age of a pensioner who is a member of a pension scheme and who is 81 is not entered as 18. This is done by setting a bottom limit on the age range.

12. Range checks Range checks are not infallible. In the example of the pension scheme data, if the age of the pensioner had been 96 and it had been entered as 69, the mistake would not have been detected by a range check.

13. Presence checks Presence checks ensure that data that must be entered is entered. For example, the pension scheme would need a pensioner’s National Insurance number. If that was not entered the presence check would detect this and notify whoever was entering the data.

14. Hash totals A hash total is a meaningless total. It is often used on computer-generated invoices.

15. Hash totals

16. Control total A control total is similar to a hash total except that the result has some meaning. For example, the total cost of each item on the invoice added together is a control total.

17. Control total

18. Check digits When large numbers are entered into a data system there is always a chance of error. To help to overcome this problem an additional number is often added to the end of the original number. This number is a check digit, and is calculated from the other numbers in the original number.

19. Check digits Check digits are often found on barcodes. When the barcode is scanned, the computer automatically removes the end number and uses the rest of the numbers to calculate what the check digit should be. If the result is the same, then the number has been entered correctly.

20. Check digits The first number (4) is the check digit. Starting from the left, the next number (7) is multiplied by 11, the second (8) by 10, and so on.

21. Check digits The total is then found: 7 x 11 + 8 x 10 + 0 x 9 + 8 x 8 + 3 x 7 + 2 x 6 + 1 x 5 + 8 x 4 + 1 x 3 + 6 x 2 + 9 x 1 = 315 315 is then divided by 11 (there are 11 numbers). 315 ÷ 11 = 28 with a remainder of 7.

22. Check digits The remainder is then deducted from 11 and the result should equal the check digit (11 – 7 = 4). As the check digit is 4, the barcode has been entered correctly.

23. Spelling checkers Although spellcheckers are usually found in word processing programs, they can also form part of data-handling programs. They can be ‘enabled’ (switched on) so that they check data as it is entered and automatically identify any mistakes.

24. Custom dictionaries If a spellchecker is used it will automatically identify any words that it does not recognise. In particular spellcheckers often fail to recognise proper names (i.e. the names of people or places) or specialist words or jargon.

25. Custom dictionaries It is possible to avoid this by setting up customised dictionaries to which words can be added. Once a word had been add to the customised dictionary, the spellchecker will recognised the new words as being spelt correctly.

26. Length checks Certain types of data are always the same length. For example, a National Insurance number will have 2 letters, followed by 6 numbers, followed by 1 letter (e.g. YY232425A). A length check will identify any NI numbers that have more or fewer characters.

27. Lookup tables A lookup table contains a list of valid codes that can be used to enter data. If a code that is not in the lookup table is entered. it is rejected. This prevents any incorrect data from being processed.

28. Parity errors Data is composed of 1s and 0s (or ‘bits’ of information). When data is transmitted from one computer to another it is important that does not become damaged or ‘corrupted’ during transmission. Parity checking is a means of doing this.

29. Parity errors Parity is the sum of the bits within a piece of data. A parity error occurs when one of the bits is changed. When this happens the parity calculated at the receiving computer is not the same as it was when the data was transmitted.

30. Parity errors The difference in parity alerts the computers to the fact that the data has been corrupted. However, if more than one error occurs they may balance each other out, and parity can appear to be correct even though the data has been corrupted.

31. Common errors Common types of error are: Transcription errors – these usually occur when people entering data misread what they are entering (e.g. mistaking 5 for S or O for 0). Transposition errors – these occur when people entering data get characters out of order or back to front (e.g. 619 instead of 916 or ‘form’ instead of ‘from’).