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Flashcards in Research Methods - Data Handling and Analysis Deck (47)
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1
Q

What are tables?

A

Raw scores displayed in columns and rows. A summary paragraph beneath the table explains the results.

2
Q

What are bar charts?

A
  • Used for presenting nominal data (in the form of categories). Categories (discrete data, the independent variable) are usually placed along the x axis, with the frequency (or dependent variable) on the y axis. This can be reversed.
  • The height of each column represents the frequency.
  • Compound bar charts tend to be difficult to interpret.
3
Q

What are histograms?

A
  • Bars are touching each other.
  • Data is continuous rather than discrete.
  • There is a true zero.
  • It is used when data falls on a continuous scale (ordinal or interval).
  • Frequency is plotted on the y axis.
  • Dependent variable is on the x axis.
  • Any gaps suggest that there was no data in that class.
  • The width of a histogram shows the range of results.
  • The shape can also indicate the trend in data.
4
Q

What are line graphs/frequency polygons?

A
  • Frequency on one axis, data on the other axis is continuous.
  • The line often shows how something changes, e.g. over time.
  • Can be used in similar ways to the histogram (ordinal and interval data).
  • Useful for displaying two or more sets of data (e.g. individual results in two conditions).
  • Useful to display trend.
5
Q

What are scattergrams?

A
  • Used for correlational analysis. Each dot represents one pair of related data.
  • The data on both axes must be continuous.
6
Q

What is a normal distribution?

A
  • Symmetrical, bell-shaped curve. Most people are in the middle area of the curve with very few at the extreme ends.
  • The mean, medium and mode all occupy the same mid-point of the curve.
7
Q

What is a skewed distribution?

A

Distributions that lean to one side or the other because most people are either at the lower or upper end of the distribution.

8
Q

What is a negative skew?

A

Most of the distribution is concentrated towards the right of the graph, resulting in a low tail on the left.

The mode is the highest point of the peak, the median comes next to the left, and the mean is dragged across to the left.

9
Q

What is a positive skew?

A

Most of the distribution is concentrated towards the left of the graph, resulting in a long tail on the right.

The mode is the highest point of the peak, the median comes next to the right, and the mean is dragged across to the right.

10
Q

What are the levels of measurement?

A
  • When carrying out research, psychologists collect data.
  • Sometimes the data is qualitative, but many of the techniques produce quantitative data.
  • The information collected varies in how precise it is.
  • The “levels of measurement” refers to these differences in precision.
  • It’s important to assess the level of measurement.
11
Q

What are the three types of data, from the most basic to the most precise?

A
  1. nominal
  2. ordinal
  3. interval
12
Q

What is nominal data?

A
  • This is the most level of measurement,
  • Used when data is put into tally charts/categories. For this reason, it is sometimes referred to as category data.
  • Gives very little information as it is basically a headcount, it only tells us how many people are in each group.
  • Each item can only appear in one category. There is no order.
13
Q

What is ordinal data?

A
  • This is used when data can be put into order, e.g. 1st, 2nd and 3rd.
  • If there is a scale, it’s ordinal data.
  • It cannot tell us what gap is between 1st and 2nd, or between 4th and 5th (intervals are variable).
  • Intervals are subjective.
  • Usually based on opinion therefore tend to be subjective rather than objective, and so lacks precision.
14
Q

What is interval data?

A
  • The most precise level of measurement.
  • Interval data is based on numerical scales that include units of equal, precisely defined size.
  • e.g. the gap between 1 and 3 seconds is exactly double the gap between 1 and 2 seconds.
  • e.g. the gap between 2 and 3cm is exactly the same as the gap between 10 and 11cm.
  • Public units of measurement.
  • Interval data is ‘better’ than ordinal data because more detail is preserved as the scores are not converted to ranks.
15
Q

What are the measures of central tendency?

A
  • mean
  • median
  • mode
16
Q

What are the measures of dispersion?

A
  • range

- standard deviation

17
Q

What measure of central tendency would you use for each level of measurement used?

A

interval - mean
ordinal - median
nominal - mode

18
Q

What is the mean?

A

The arithmetic average, add up all the scores and divide by the number of scores.

19
Q

What are the advantages of using the mean?

A
  • Sensitive.
  • Includes all the scores in the data set within the calculation.
  • More of an overall impression of the average than median or mode.
20
Q

What are the disadvantages of using the mean?

A
  • May be unrepresentative.
  • One very large or small number makes it distorted.
  • The median or the mode tend not to be so easily distorted.
21
Q

What is the median?

A

The middle value, place scores in ascending order and select middle value. If there are two values in the middle, the mean of these is calculated.

22
Q

What are the advantages of using the median?

A
  • Unaffected by extreme scores.
  • The median is only focused on the middle value.
  • It may be more representative of the data set as a whole.
23
Q

What are the disadvantages of using the median?

A
  • Less sensitive than the mean.
  • Not all scores are included in the calculation of the median.
  • Extreme values may be important.
24
Q

What is the mode?

A

The most frequent or common value, used with categorical/nominal data.

25
Q

What are the advantages of using the mode?

A
  • Relevant to categorical data.

- When data is ‘discrete’, i.e. represented in categories, sometimes the mode is the only appropriate measure.

26
Q

What are the disadvantages of using the mode?

A
  • An overly simple measure.
  • There may be many modes in a data set.
  • It is not a useful way of describing data when there are many modes.
27
Q

What is the range?

A

The difference between the highest and lowest value (+1).

28
Q

What are the advantages of using the range?

A
  • Easy to calculate.
  • Arrange values in order and subtract smallest from largest.
  • Simple formula, easier than the standard deviation.
29
Q

What are the disadvantages of using the range?

A
  • Does not account for the distribution of the scores.
  • The range does not indicate whether most numbers are closely grouped around the mean or spread out evenly.
  • The standard deviation is a much better measure of dispersion in this respect.
30
Q

What is standard deviation?

A

A measure of the average spread around the mean. The larger the standard deviation, the more spread out the data are.

31
Q

What are the advantages of using standard deviation?

A
  • More precise than the range.
  • Includes all values within the calculation.
  • A more accurate picture of the overall distribution of the data set.
32
Q

What are the disadvantages of using standard deviation?

A
  • It may be misleading.
  • May ‘hide’ some of the characteristics of the data set.
  • Extreme values may not be revealed, unlike with the range.
33
Q

What is quantitative data?

A

Numerical data.

34
Q

What are the advantages of quantitative data?

A
  • Easier to analyse.
  • Can draw graphs and calculate averages.
  • Can ‘eyeball’ data and see patters at a glance.
35
Q

What are the disadvantages of quantitative data?

A
  • Oversimplifies behaviour.
  • Means that individual meanings are lost.
  • Qualitative data can be turned into quantitative data, but the reverse cannot be done.
36
Q

What is qualitative data?

A

Non-numerical, descriptive data.

37
Q

What are the advantages of qualitative data?

A
  • Represents complexities.
  • More detail included.
  • Can also include information that is unexpected.
38
Q

What are the disadvantages of qualitative data?

A
  • Less easy to analyse.
  • Large amount of detail is difficult to summarise.
  • Difficult to draw conclusions.
39
Q

What is primary data?

A

‘First hand’ data collected directly for the purpose of the investigation.

40
Q

What are the advantages of using primary data?

A
  • Fits the job.
  • Study designed to extract only the data needed.
  • Information is directly relevant to research aims.
41
Q

What are the disadvantages of using primary data?

A
  • Requires time and effort.
  • Design may involve planning and preparation.
  • Secondary data can be accessed within minutes.
42
Q

What is secondary data?

A

Collected by someone other than the person who is conducting the research, e.g. taken from journal articles, books, websites or government records.

43
Q

What are the advantages of secondary data?

A
  • Inexpensive.
  • The desired information may already exist.
  • Requires minimal effort making it inexpensive.
44
Q

What are the disadvantages of secondary data?

A
  • Quality may be poor.
  • Information may be outdated or incomplete.
  • Challenges the validity of the conclusions.
45
Q

What is meta-analysis?

A

A type of secondary data that involves combining data from a large number of studies. Calculation of effect size.

46
Q

What are the advantages of meta-analysis?

A
  • Increases validity of conclusions.
  • The eventual sample size is much larger than individual samples.
  • Increases the extent to which generalisations can be made.
47
Q

What are the disadvantages of meta-analysis?

A
  • Publication bias.
  • Researchers may not select all relevant studies, leaving out negative or non-significant results.
  • Data may be biased because it only represents some of the data and incorrect conclusions are drawn.

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