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Testing for a difference between groups (one non-numerical variable) in discrete data

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Testing for a difference between groups (one non-numerical variable) in discrete data

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Non-Normal Data: Spearman Correlation Test

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Non-Normal Data: Spearman Correlation Test

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Used to determine if there is a statistical dependence (correlation) between two variables. It is appropriate for data for non-normal distribution (distribution is not known) and assesses the degree of association between the X & Y variables. The values must be monotonic, meaning as the values of X & Y increase/decrease together or one increases while the other decreases.

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Indicates the strength of a linear association between two variables as shown by a value (r).  The linear association is a best fit line and indicates how the change in one variable proportionally affects the other; ex: one variable increase causes an equally constant increase in the other.

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ANOVA test can determine if there is a statistically significant difference between at least one sample, but not which one. Often which sample is different can be concluded based on analysis of the graph

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12 - Analysis of Variance (ANOVA) Overview in Statistics - Learn ANOVA and How it Works.

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The Unpaired T-Test compares two different subjects; ex: Suitability of clay pots vs plastic for plant growth or lung capacity of asthmatic and non-asthmatic individuals

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Chips Ahoy Lab: Mean, Standard Deviation, & T-Tests

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The Paired T-Test compares two different times or occurrences; ex: Suitability of plant growth before and after fertilizer treatment or reaction time of a group before and after yoga training course

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Test for a Correlation: Finding how one value affects another

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Test for a Correlation: Finding how one value affects another

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Create an X-Y scatter plot graph

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The data do not plot in a straight line; ex: oxygen consumption at different temperatures

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The data plot in a straight line; ex: clutch size vs body size

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Testing for a difference (relationship) between numerical variables

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Testing for a difference (relationship) between numerical variables

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Chi-Squared: Testing an association between groups of counts

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Chi-Squared: Testing an association between groups of counts

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Used to test for the association of one category with another in the same area

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Chi-squared test for association (IB Biology)

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Chi-Squared in Genetics: Comparing observed counts to an expected count

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Chi-Squared in Genetics: Comparing observed counts to an expected count

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Used to test the outcome of dihybrid crosses against an expected (predicted) Mendelian ratio

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Ex: counting the number of a particular group in comparison to expected counts