Types of data

Question 1

Explain what the term ‘qualitative data’ refers to (2 marks)

Answer 1

Qualitative data is non-numerical data that is expressed in words, e.g. an extract from a diary.

Question 2

Outline one strength and one limitation of using quantitative data (4 marks)

Answer 2

One strength of using quantitative data is that it is easier to analyse quickly, meaning that conclusions can be drawn & patterns can be seen.
One weakness of using quantitative data is that it is less detailed and developed - it may ignore insights that researchers have overlooked, impacting validity.

Question 3

Outline one strength and one limitation of collecting secondary data in psychological research (2 marks + 2 marks)

Answer 3

One strength of using secondary data is that the data is easier and cheaper to access than primary data. The desired information already exists, so there is no need for the researcher to spend time conducting an investigation to find it out, meaning that less time and money are wasted.
A weakness of using secondary data is that the data may be out of date. Because secondary data is conducted by someone else prior to the current research, it may not be relevant for current day life, meaning it has poor historical validity.

Question 4

Explain what the term ‘meta-analysis’ means (2 marks)

Answer 4

Meta-analysis refers to ‘research about research’ - the process of combining results from a number of studies on a particular topic to provide an overall view. For example calculating the effect size.

Question 5

Briefly discuss the use of meta-analysis in psychology (6 marks)

Answer 5

A strength of using meta-analysis in psychology is that it increases the validity of conclusions. The sample size is much larger than it would be otherwise, meaning that we are able to generalise the findings of a meta-analysis to the target population (better external validity).
A weakness of using meta-analysis is that it can be prone to publication bias. This occurs where the researcher may not select all the relevant studies & choosing to ignore studies with negative/negligible results. Therefore data may be biased and incorrect conclusions can be made.

Question 6

Explain what is meant by the term ‘measure of central tendency’ (2 marks)

Answer 6

Measures of central tendency refers to the general term for any measure of the average value in a set of data. It includes the mean, median and mode.

Question 7

Outline one strength and one limitation of using the median as a measure of central tendency (4 marks)

Answer 7

One strength of using the median as a measure of central tendency is that it doesn’t take into account any extreme values as it is measured from taking the central value. This means that the data is not easily distorted by extreme values so is more representative of the overall set.
One weakness of using the median as a measure of central tendency is that the median value may not even lie in the data set. If this occurs, the median is not a very accurate measure of the average.

Question 8

Explain what is meant by the standard deviation (2 marks)

Answer 8

The standard deviation is a single value that tells show far scores deviate from the mean. The larger the standard deviation, the greater the dispersion of spread within a set of data.

Question 9

Explain what is meant by the term ‘measure of dispersion’ (2 marks)

Answer 9

Measures of dispersion refers to a numerical value based on the spread of scores, i.e. how far the scores vary and differ from one another.

Question 10

Outline one strength and one limitation of using the range as a measure of dispersion (2 marks + 2 marks)

Answer 10

One strength of using the range as a measure of dispersion is that it is easy to calculate. Arranging the values in order and subtracting the largest from the smallest is simple and easier than the standard deviation.
A weakness of using the range as a measure of dispersion is that it only takes into account the two most extreme values, making it unrepresentative of the data set as a whole.