types of data

Question 1

quantitative data

Answer 1

anything numerical
data that can be easily measured

Question 2

quantitative data advantages

Answer 2

• easy to analyse because data is in numbers which can be summarised using descriptive or inferential statistics
• easy to draw conclusions

Question 3

quantitative data disadvantages

Answer 3

• oversimplifies reality and human experience

Question 4

qualitative data

Answer 4

data in words, pictures or anything non-numerical
typically detailed and in depth descriptions

Question 5

qualitative data advantages

Answer 5

• represents true complexities of human behaviour as its not reduced to numbers
• gain rich details of how people think and behave - higher validity

Question 6

qualitative data disadvantages

Answer 6

• more difficult to detect patterns
• more difficult to draw conclusions from

Question 7

primary data

Answer 7

• data that is collected for the purpose of the study currently being conducted

Question 8

primary data advantages

Answer 8

• data collection is created to fit the aims and hypothesis of the study, so is more useful

Question 9

primary data disadvantage

Answer 9

• very lengthy and time consuming and costly, it takes time to design the correct procedure and instructions and the appropriate measuring tool

Question 10

secondary data

Answer 10

information that was collected for a purpose other than the current study

Question 11

secondary data advantages

Answer 11

• simpler to access someone else’s data and cheaper, as there is less time and equipment needed
• data may have been subjected to statistical analysis and therefore know it is significant

Question 12

secondary data disadvantage

Answer 12

• data may not exactly fit the needs of the study so not be appropriate

Question 13

advantages of the mean

Answer 13

• more sensitive than the median, because it makes use of all the values of the data
• more accurate (scientific)
• represents all data

Question 14

disadvantages of the mean

Answer 14

• can be misrepresentative if there is an extreme value
• can’t be used for nominal data

Question 15

advantages of the mode

Answer 15

• useful when the data is in categories
• easy to calculate

Question 16

disadvantages of the mode

Answer 16

• not a useful way of representing the data when there is multiple modes

Question 17

advantages of the median

Answer 17

• not affected by extreme scores, so can give a representative value
• easy to calculate

Question 18

disadvantages of the median

Answer 18

• less sensitive than the mean, it does not take into account all the values
• less scientific

Question 19

measures of dispersion

Answer 19

how spread out the data is
are scores similar to each other or spread out
- range
- standard deviation

Question 20

standard deviation

Answer 20

tells us the average distance of each score from the mean
68% of normally distributed data is within 1 sd each side of the mean
95% within 2 sd
almost all within 3 sd

Question 21

range advantages

Answer 21

• quick and easy to calculate
• represents difference between scores

Question 22

range disadvantages

Answer 22

• affected by extreme values
• does not take into account all values
• less scientific

Question 23

advantages of standard deviation

Answer 23

• more precise measure of dispersion because all values are taken into account
• less affected by extreme values
• more scientific

Question 24

disadvantages of standard deviation

Answer 24

• much harder to calculate than the range

Question 25

conclusions

Answer 25

- higher the standard deviation the more spread out your scores are, meaning your results are less consistent - smaller the standard deviation the less spread out your scores are, meaning your results are more consistent

Question 26

variance

Answer 26

doing all the steps of SD except the square root at the end

Question 27

conclusions

Answer 27

typically you would do the SD of the 2 conditions of your IV

Question 28

variance

Answer 28

- variance can also tell us more about the range of data, as can the SD - it is referred to as S squared and considers the difference between each data point and the mean - as with SD takes every score into account so unlike the range, not distorted by outliers

Question 29

evaluating variance and SD

Answer 29

- both take all the values into account so it's a precise measurement - not difficult to calculate if you have a calculator - one problem with the variance is that the final answer is a squared number, so its not in the same units as the mean, may hide extreme scores

Question 30

standard deviation

Answer 30

step 1 - calculate the mean for the test scores step 2 - the participant's raw scores minus the mean step 3 - square the score minus mean step 4 - add the total of the squares step 5 - n-1 = total number of participants minus 1 step 6 - divide top row by bottom row step 7 - square root of your calculated value

Question 31

nominal data

Answer 31

data that fits into distinct categories

Question 32

ordinal data

Answer 32

numerical values