College aantekeningen MTO-B MAW: Inleiding Statistiek

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1. Data-handling en descriptive statistics...............................................................................................2
1.2 descriptive statistics......................................................................................................................2
1.3 Missing values...............................................................................................................................2
1.4 computing variables (nieuwe variabelen).....................................................................................3
1.5 recoding variables.........................................................................................................................4
1.6 entering data  create data-file......................................................................................................4
2. Syntax en T-test..................................................................................................................................6
2.1 introduction to syntax..................................................................................................................6
2.2 data handling using syntax...........................................................................................................7
2.3 one-sample T-test (1)....................................................................................................................8
2.4 one-sample T-test (2)....................................................................................................................8
2.5 bonus............................................................................................................................................8
3. T-test & correlation/association.........................................................................................................9
3.1 independent samples T-Test.........................................................................................................9
3.2 paired samples T-Test...................................................................................................................9
3.3 correlations.................................................................................................................................10
3.4 Chi2Test......................................................................................................................................11
What do people think is the most important factor of job satisfaction, and is this related to
whether or not they have flexible working hours?...........................................................................11

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1. Data-handling en descriptive statistics
1.2 descriptive statistics
Descriptive statistics are values that give us an impression of what the data look like as a whole. Examples
of descriptive statistics are the mean, standard deviation, and frequencies.
Histogram maken:
- Navigate to Graphs → Legacy Dialogs → Histogram
- Make sure to check the box 'Display Normal Curve'.
- Click 'Ok' to run the analysis.

Next up is to generate a table with descriptive statistics.
 Navigate to Analyze → Descriptive Statistics → Descriptives
 Add the variable SATIS and OPTIM to the 'Variable(s)' box.
 Click on “Options” and check the box “Variance”.
 Click 'Ok' to run the analysis.

Besides getting an overall impression of the data, another reason to look at the descriptive statistics is to
see if there are any errors in the data file, such as answers that are outside the range of expected values.
In descriptives kijken naar min en max score.
To find these, you can sort the data file by a variable.
 Navigate to Data → Sort Cases
 Put the variable OPTIM in the 'Sort by' box.
If you find a strange value, you may select the whole row and delete it.

Now that we’ve “cleaned” the data file, it’s time to answer your first research question!
The question is: “Are non-smokers more satisfied with their life than smokers?”
To answer this question, we first have to split the participants into two groups: Smokers and Non-smokers.
 Navigate to Data → Split File → Compare Groups
 Select 'compare groups' and put the variable SMOKE in the box


1.3 Missing values
In het frequency table van een variabele kun je de missende waarden vinden.

Note that the values in the columns “Percentage” and " Valid percentage" differ. This is due to these
missing values!
“Percentage” is obtained by dividing the observed frequency by the total N (including respondents
with a missing value), whereas “Valid Percentage” is obtained by dividing the observed frequency by the
number of respondents with a valid score (thus, excluding the persons who had a missing value).
You could also calculate these percentages by hand by using the frequencies given in the first
column. You might want to try this for some of the (valid) percentages to get more insight in the table.

Flag question: Spacer
In the current dataset, the missing values are just empty cells. SPSS sees the empty cells as so called
“system missing”. It simply tells us that data in these cells are missing.

Although this may work for now, a better strategy is to use codes for the missing values. For example, we
may code our current missing values by 999.

Proceed as follows:
1. Go to the data view, and fill in the value 999 for the missing values on the variable stress.
(You may want to use the “sort cases” option to find the missing values faster.)