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Psychology > Research Methods - Data Handling and Analysis > Flashcards

Research Methods - Data Handling and Analysis Flashcards

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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.

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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.
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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.
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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.
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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.
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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.
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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.

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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.

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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.

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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.
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11
Q

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

A
  1. nominal
  2. ordinal
  3. interval
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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.
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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.
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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.
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15
Q

What are the measures of central tendency?

A
  • mean
  • median
  • mode
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16
Q

What are the measures of dispersion?

A
  • range

- standard deviation

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17
Q

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

A

interval - mean
ordinal - median
nominal - mode

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18
Q

What is the mean?

A

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

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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.

Psychology (68 decks)

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