DE200- Methods, Statistics, Spss at Open University | Flashcards & Summaries

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# Lernmaterialien für DE200- methods, statistics, spss an der Open University

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Stacked histogram
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Shows frequency distribution of a variable within different conditions.
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Why do we need t-test?
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Variations in the data mask differences between means. T-test control this by showing if the means are truly SS.
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Elements property box
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Appears in SPSS graph design.
Allows choice regarding numerical aspects of data which you want to be produced in your graph.
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Bar chart investigates...
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Mean scores of variable within different conditions.
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Histogram
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Shows the frequency distribution of participants answers/a variable.
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Simple bar chart
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Investigates the mean scores of a single variable across its multiple conditions.
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1 tailed hypothesis
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Directional
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Inferential statistics
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Tests the null hypothesis to ensure differences found between means are statistically significant and not due to sample error or simply the expected, natural, difference.
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Error bars
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Provides an idea of dispersion in your data and representatativness of your sample.
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2 tailed hypothesis
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Non directional
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Generalisability
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The ability to apply your data/findings to a wider population.
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Clustered bar chart
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Investigates mean scores of a variable within different conditions against another variable.
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Q:
Stacked histogram
A:
Shows frequency distribution of a variable within different conditions.
Q:
Why do we need t-test?
A:
Variations in the data mask differences between means. T-test control this by showing if the means are truly SS.
Q:
Elements property box
A:
Appears in SPSS graph design.
Allows choice regarding numerical aspects of data which you want to be produced in your graph.
Q:
Bar chart investigates...
A:
Mean scores of variable within different conditions.
Q:
Histogram
A:
Shows the frequency distribution of participants answers/a variable.
Q:
Simple bar chart
A:
Investigates the mean scores of a single variable across its multiple conditions.
Q:
1 tailed hypothesis
A:
Directional
Q:
Inferential statistics
A:
Tests the null hypothesis to ensure differences found between means are statistically significant and not due to sample error or simply the expected, natural, difference.
Q:
Error bars
A:
Provides an idea of dispersion in your data and representatativness of your sample.
Q:
2 tailed hypothesis
A:
Non directional
Q:
Generalisability
A:
The ability to apply your data/findings to a wider population.
Q:
Clustered bar chart
A:
Investigates mean scores of a variable within different conditions against another variable.

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