# Inferential Statistics

Mean
arithmetic average- add all of the scores up and then divide them by how many there are
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Mode
the most common result
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Median
the middle score when the results are ordered from highest-lowest/lowest-highest
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Range
the difference between the lowest and the highest score
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Standard Deviation
the spread of data around the mean
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Scattergraph
displays correlation data
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Bar chart
shows data is in separate categories
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Histogram
shows data measured on a continuous scale
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Content Analysis
using a coding system on a collection of written data e.g. the amount of times the word happy is used in a newspaper article
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Categorisation
grouping together similar items
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Level of Significance
If the result hasn't been caused by chance then the pattern can be described as significant e.g. testing men and women to see who is better at reading map- results favour men- this could be due to chance
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What is a sample?
the participants involved in a study
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What is a population?
the total amount of people the finding apply to e.g. in the map study- the entire world population of men and women
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Null hypothesis
the assumption that their is no relationship between in the population in which two samples are taken from e.g. no difference in the men and women in the map study
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Alternative hypothesis
alternative to the null where there is a belief that something is going on- the two samples are different in some way
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Chance
to what extent are the results true- to what extent are they chance
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Type 1 Error
false positive e.g. convicting a guilty man of murder
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Type 2 Error
false negative e.g. letting a guilty man go free
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What test do you use for a directional hypothesis?
one tailed test
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What test do you use for a non-directional hypothesis?
two tailed test
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Why are statistical tests used?
to determine the level of significance or chance
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Why is 95% significance used?
because it is seen as no too lenient or stringent, after 5% chance many are then certain that the results are significant
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When would you use Spearman's Rank Order Correlation?
when the hypothesis predicts a correlation between two co-variables, when the two sets of data are from one person (repeated measures) & when data is ordinal (ordered in some way)
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When would you use a Chi-squared test?
when the hypothesis predicts a difference between two conditions or an association between variables, sets of data must be independent measures, data is nominal
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When would you use the Sign test?
when the hypothesis predicts a difference between the two tests, when the two sets of data are from the same person or matched pairs & when the data is nominal
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When would you use the Wilcoxon T test?
when the hypothesis predicts a difference between the two sets of data, when the two sets of data are from one person or matched pairs & when the data is ordinal
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When would you use the Mann- Whitney U test?
the hypothesis predicts a difference between two sets of data, independent groups & data is ordinal
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## Other cards in this set

### Card 2

#### Front

the most common result

Mode

### Card 3

#### Front

the middle score when the results are ordered from highest-lowest/lowest-highest

### Card 4

#### Front

the difference between the lowest and the highest score

### Card 5

#### Front

the spread of data around the mean