Introducing Research and Data in Psychology

A Guide to Methods and Analysis

Ann Searle

• Publisher: Routledge
• Year: 2002
• ISBN:
  9781134659500
• Edition: 1
• Topic: Psychologie
• Subtopic: Histoire et théorie en psychologie

Introducing Research and Data in Psychology shows how research design and data analysis are attainable and useful skills. It introduces both experimental and non-experimental methods of research and the analysis of data using both descriptive and inferential statistics. The uses, interpretation and calculation of common two sample statistical tests are explained. This comprehensive textbook includes the following designed features to help with technique:
* Practice exam answers to show how to achieve a higher grade
* Chapter summaries
* Glossary
* Case studies and examples
* Exercises and a full bibliography

Section Nine

Summary tables

Graphical representation

Line graphs

Histograms and bar charts

Pie charts

Stem and leaf diagrams

Box and whisker plots

Scattergrams and correlations

Measures of central tendency

Mean

Median

Mode

Distribution curves

Normal distributions

Skewed distributions

Bimodal distributions

Measures of the spread of scores

Range

Semi-interquartile range

Standard deviation and variance

Standard scores and z-scores

Presentation of data in reports

This involves the use of descriptive statistics. Don’t panic at the mention of the word statistics—you will probably find that you are already familiar with nearly all of the material in this section.

Descriptive statistics—as the name indicates—are simply ways of summarising your research findings that do not go beyond description. They enable you to present your data so that someone else can see at a glance what you found, rather than being presented with lists of raw scores.

Even though you are probably familiar with this material do read the next section—what you are asked about this in a psychology exam will not be the same as in a maths exam!

The eyeball test Students often underestimate the importance and usefulness of just looking carefully at the raw data. Don’t underestimate the importance of the eyeball test—plus a dollop of common sense! For instance are the means of two sets of scores very different from each other? If they are, yet when you work out more complex statistics these indicate that there is no difference between the sets of scores, then perhaps you have gone wrong somewhere!

Tables of scores

These provide the most basic way to present a summary of your data. Always make sure they have an informative title and are clearly labelled. (See example below.)

If your research hypothesis suggests that there may be a difference between the sets of scores, you should present at least one measure of central tendency and one measure of dispersion. (These are discussed fully later in this section.) For example:

Table 9.1 Symmary table to show the number of trigrams recalled

If your research hypothesis suggests that there will be a correlation between two variables, it may not be meaningful to give means or medians. A measure of the spread of the two sets of scores (such as the range or standard deviation) might still be useful, however.

If you have tested a fairly small number of participants in a correlational study, you could present the data in a table as shown below. If there is going to be a long list of scores, it is better to include th...