  Chapter 

SPSS is a statistical computer program used by scientists to collect, analyze and process data. It is mainly used to investigate research results. The abbreviation SPSS stands for Statistical Package for the Social Sciences. The program is therefore used in particular in social science.

Three important situations in which you can use SPSS:

  1. Checking the reliability of a sample. If you want to do a research in the Netherlands, it is of course not feasible to test every resident. For this reason, we almost always use a sample (a selection of people from the population). It is important that this sample is as representative as possible for the entire population so that the outcome results can be well generalized (after all, you want to say something about the entire population and not just about the sample).

  2. Checking the reliability of your results. SPSS can provide information as to whether the connection you have found (for example, men vote for SGP (i.e., a Dutch political party) more often than women) is a coincidence or whether the difference has something to do with something else.

  3. Visualize data. It can be useful to visualize your results through graphs and tables. You can do this by using SPSS.


Introduction: What is SPSS?

SPSS is a statistical computer program used by scientists to collect, analyze and process data. It is mainly used to investigate research results. The abbreviation SPSS stands for Statistical Package for the Social Sciences. The program is therefore used in particular in social science.

Three important situations in which you can use SPSS:

  1. Checking the reliability of a sample. If you want to do a research in the Netherlands, it is of course not feasible to test every resident. For this reason, we almost always use a sample (a selection of people from the population). It is important that this sample is as representative as possible for the entire population so that the outcome results can be well generalized (after all, you want to say something about the entire population and not just about the sample).

  2. Checking the reliability of your results. SPSS can provide information as to whether the connection you have found (for example, men vote for SGP (i.e., a Dutch political party) more often than women) is a coincidence or whether the difference has something to do with something else.

  3. Visualize data. It can be useful to visualize your results through graphs and tables. You can do this by using SPSS.

General information related to research

SPSS can answer research questions by doing analyzes; tests. An example of a research question is: do men more often choose a technical profession than women? The first step is to collect your data (what percentage of men choose a technical profession and what percentage of women). This data is mentioned in SPSS data . When you have collected your data (for example by means of questionnaires) you can enter this data in SPSS. You can then have SPSS perform a test that examines whether there is actually a difference between the data of men and women.

How to plan the set up of a study?

A good research study is highly dependent on a detailed planning. The book gives the following tips when starting an study:

  • Choose the design of your research (for example, experiment, questionnaire, observational). Weigh all the pros and cons of each method.

  • If you opt for an experiment: decide whether you opt for an between-groups design (different test subjects in each experimental condition) or a repeated measures design (all test subjects in all conditions).

  • If you choose an experiment: make sure you have enough levels in your independent variable.

  • Always select more test subjects than necessary (given the high risk of dropping out).

  • If possible, randomly assign test subjects to each experimental condition. It is important that these groups do not differ in other matters (check this with a covariance analysis).

  • Choose reliable and valid dependent variables.

  • Anticipate possible confounding variables. These are variables other than the independent variable that can provide a possible explanation for your result. If possible, check variables for these confounding.

  • If you choose a questionnaire study (survey), check in advance whether the instructions, questions and scales are clear. You do this through pilot testing.

How to choose the appropriate scales and methods?

When choosing the right scale and method, two concepts are important: reliability and validity. Both terms can influence the quality of your data.

Reliability

The reliability of a scale indicates to what extent the scale is free from random error. There are two types of reliability:

  1. Test-retest reliability: this is measured by offering the relevant scale to two different people in two different situations and then calculating the correlation between these two scores. The higher this correlation, the greater the test-retest reliability.

  2. Internal consistency: the extent to which the items of a scale are interrelated. This can for example be calculated with the Cronbach's cofficient alpha in SPSS. A Cronbach's alpha of .7 or greater indicates a reliable scale.

Validity

The validity of a scale refers to the extent to which the methods measure what they are intended to measure. There are different forms of validity:

  1. Content validity: the degree of accuracy with which the method or scale covers the intended domain or content.

  2. Criterion Validity: the relationship between different scales and a specified measurement criterion.

  3. Construct validity: the relationship with other constructs, both related constructs (convergent validity) and unrelated constructs (discriminant validity).

How to prepare a questionnaire?

When drawing up a questionnaire, it is important to keep in mind which statistical methods you need to analyze the data. Depending on the statistical technique you have to ask a specific question in a specific way.

Types of questions

Many questions can be classified into two groups: open questions and closed questions. A closed question gives respondents multiple answer options. Closed questions can be quickly converted into a numerical format in SPSS. For example, answer 'yes' can be coded with number 1 and answer 'no' with number 2. The answers to open questions can be divided into different categories, for example work or relationships. A combination of open and closed questions often works best in an study.

Format of answers

It is important to choose the right scale when drawing up answer formats. For example, if you want to calculate a correlation, you need to know the exact ages. In addition, it is often useful to use a Likert-type scale. People do not simply answer whether or not they agree with the question, but to what extent (for example, on a scale of 1 to 6).

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