Research methods - Data handling and analysis

Question 1

What is quantitative data?

Answer 1

Numerical data

Question 2

What is qualitative data?

Answer 2

Opinion based and wordy

Question 3

What methods collect quantitative data?

Answer 3

Behavioural categories
Participants rate their behaviour on a Likert scale

Question 4

What methods collect qualitative data?

Answer 4

• Structured interviews
• Paragraphs from a diary
• Unstructured observations where the observer carries out continuous recording
• Unstructured interviews
• Video diary

Question 5

What are the strengths of quantitative data?

Answer 5

• Easy to analyse and interpret as the data is numerical
• The techniques used are easy to replicate and so it has high reliability

Question 6

What are the limitations of quantitative data?

Answer 6

• Narrow in scope so consequently lacks ecological validity making it hard to generalise

Question 7

What are the strengths of qualitative data?

Answer 7

• Gathers in-depth data, which is meaningful and detailed. The broader scope means that it has high construct validity

Question 8

What are the limitations of qualitative data?

Answer 8

• As the data tends to come from individual or small group investigations it can be difficult to generalise the findings.
• Statistical tests can’t be done to qualitative data

Question 9

How is primary data collected? Pros and cons?

Answer 9

Collected first hand by the researcher carrying out experiments , self-reports, observations and correlations.
+ Has been specifically designed for a particular investigation so is therefore objective
- Time consuming and costly
- Researcher be biased in their approach

Question 10

How is secondary data collected? Pros and cons?

Answer 10

Collected by other researchers, using the same techniques as primary and has already been subject to data analysis. This is then used as part of another study to support or reject a new research hypothesis.
+ Easily accessible making it a quick and cheap option
- If it is not specific to the new research it may not quite be fit for purpose.

Question 11

What is meta-analysis ? Pros and cons?

Answer 11

A powerful method that researchers use to analyse secondary data from many studies in order to develop a single conclusion that has greater statistical significance.
+ If findings support the research hypothesis the researcher is able to generalise the findings to a wider population.
- Meta-analysis can be subject to researcher bias as they may only choose the studies that support their research hypothesis.

Question 12

How is the Mean calculated? Pros and cons?

Answer 12

The average. Calculated by adding up all the values and dividing by the number of values and dividing by the number of values.
+ Precise and it uses all the data when calculating the central tendency
- Central tendency is easily distorted by data that is very high or low compared with the rest of the data, known as outliers

Question 13

How is the Median calculated? Pros and cons?

Answer 13

Calculated by placing the data into rank order and then selecting the middle value.
+ Can be used when data is skewed by high or low numbers
- It is less precise as it does not use all the data available

Question 14

How is the Mode calculated ? Pros and cons?

Answer 14

The mode is the most frequently occurring number in a set of data.
+ Can be used with non-numerical data
- There may be more than one mode and it does not use all the data gathered.

Question 15

How is the Range calculated? Pros and cons?

Answer 15

Subtracting the lowest score from the highest score
+ Easy to calculate
- May not be representative because the two most extreme values are used to calculate it.
For example: 1 1 1 1 1 1 2 2 3 3 9 9 9 9
9-1=8 This is not representative of the lower values : 1,2 and 3

Question 16

What does low and high standard deviation measure? Pros and cons?

Answer 16

Standard deviation - measures how much the scores deviate from the mean in a normal distribution.

Low standard deviation - indicates that the data points tend to be very close to the same value (the mean)

High standard deviation - indicates that the data are ‘spread out’ over a large range of values.

+ It uses all the scores in a set of data and is therefore more precise than the range and so is the best measure of dispersion to use.

• Can be distorted by outliers

Question 17

What is a bar chart? How does it present data? Why are they used?

Answer 17

A bar chart consists of rectangular bars of lengths proportional to that value that they represent. Bar charts are used for comparing two or more values. The bars represent discreet categories so are not touching.

Question 18

What is a histogram? How does it present data? Why are they used?

Answer 18

Histograms shows the frequency of continuous data and this is represented by the bars touching each other.

Question 19

What is a line graph? How do they present data? Why are they used?

Answer 19

Often used to show a trend over a number of days or hours, therefore represents continuous data. It is plotted as a series of points, which are then joined with straight lines. Typically the IV is plotted on the X axis and the DV is placed on the Y axis. The ends of the line graph do not have to join to the axis.

Question 20

What does a positive skewed distribution look like?

Answer 20

The value of the mode is a smaller number than the mean. (the bump is first)

Question 21

What does a negative skewed distribution look like?

Answer 21

The value of the mean is smaller than the mode in a negative skewed distribution. The mode is the largest value. (The bump is last)

Question 22

What is the pro and con of using correlations?

Answer 22

+ Allow us to discover strength and direction of relationship that exists between variables
- Tells us little about cause and effect (could be confounding variables causing movement)

Question 23

What does correlated mean?

Answer 23

When one variables changes, so does the other

Question 24

What does the sign of the correlation coefficient indicate?

Answer 24

The direction of the relationship
Positive = variables move in the same direction
Negative = variables move in opposite direction

Question 25

What is a correlation coefficient (r)?

Answer 25

It is a number from -1 to +1 that indicates the strength and direction of the relationship
Closer to 1 = more strongly related variables, more predictable changes in once variables will be as the other variable changes

Closer to 0 = weaker the relationship, less predictable the relationship between the variables become.

Question 26

What type of data can correlational analysis only be carried out on? Why?

Answer 26

Quantitative data - it is essentially a statistical test for a relationship between two co-variables.

Question 27

What is the normal distribution?

Answer 27

The normal distribution describes a set of data where scores are very common in the middle of the distribution (close to the mean) and become progressively less common the further they are from the mean. On a line graph, a normal distribution appears as a bell-shaped curve.

Question 28

What is skewed distribution?

Answer 28

A skewed distribution is one where frequency data is not spread evenly (i.e. normally distributed); the data is clustered at one end.

Question 29

What happens in a positively skewed distribution?

Answer 29

The mode is a lower value than the mean and median. The skew is to the right.

Question 30

What happens in a negatively skewed distribution?

Answer 30

When data is skewed to the left (negatively skewed), the median will typically be greater than the mean.

Question 31

What is an advantage of using a table?

Answer 31

It is easier to find information than from a written text

Question 32

Why can’t qualitative data be analysed using statistical tests?

Answer 32

Qualitative data uses words instead of numbers

Question 33

What does content analysis try to do?

Answer 33

Tries to quantify (put into numbers) qualitative data . Essentially all the data is broken into categories. By breaking the data into categories, the data can be more objectively analysed.

Question 34

What is the method for content analysis?

Answer 34

1. A representative sample of the qualitative data is taken
2. The data is then analysed according to coding units (categories) .
3. It is crucial that the coding units are operationalised because this will improve the validity and reliability of the results.
4. The data is then analysed according to the coding units - either examining how often or how much of these categories are used.
5. One the frequency or amount of coding units has been collected, stat tests can be carried out. (descriptive or inferential)

Question 35

What are the strengths of content analysis?

Answer 35

+Allows for statistical tests to be applied
+ The coding system can establish clear patterns in the data
+ It is relatively inexpensive
+ if the coding system is properly set up, other scientists can easily apply the same system to repeat studies (replicability)
+ Fewer ethical issues as participants aren’t involved in the analysis section

Question 36

What are the weaknesses of content analysis?

Answer 36

• Qualitative data is rich in detail. This method reduces the level of detail when creating coding units .
• When the coding units are first established, there can be a certain degree of subjectivity. For example, when coding the parental praise vs parental criticism, someone could be subjective about what actual praise and what are more neutral or critical statements.

Question 37

What does thematic analysis look at?

Answer 37

Looks at the overall themes of the data

Question 38

What does thematic analysis involve?

Answer 38

Involves the scientist looking over the data to familarise themselves. This allows them to establish the key themes within the data - themes they can define and name. From there they can write a report. The hypotheses are based on the themes of the data

Question 39

What are the strengths of thematic analysis?

Answer 39

+ Unlike content analysis, the level of detail is maintained
+ Objectivity is possible. This is done through triangulation which involves comparing other sources of data i.e previous interviews to verify the conclusions drawn.
+ By formulating hypotheses grounded in the data, new understandings are established. For example, the Delaney et al. study found that many interviewees wanted to return to work but felt hopeless and assumed that unemployment would continue.

Question 40

What are the weaknesses of thematic analysis?

Answer 40

• It can be difficult at first to establish the themes and categories
• Subjectivity can come into play when deciding how certain statements fit into these categories
• It can be time-consuming to comb through a vast amount of text.
• By summarising data, some of the text will be left out - it is challenging to decide which data to leave out
• Overall, subjectivity and researcher bias can affect the validity of the results