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Published byDominick Aubrey Harrell Modified over 9 years ago
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Test for Significant Differences T- Tests
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T- Test T-test – is a statistical test that compares two data sets, and determines if there is a significant difference between two data sets.
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T- Test
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Calculating T-Test To calculate a test test (t-values) you need the following information: – Mean – Standard deviation – Sample size You don’t need to calculate t-values – excel will do it for you.
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T-Tables Degrees of freedom (df): Sum of sample sizes minus 2 Probability Values (p-value) – Probably that the difference occurred by chance alone
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Degrees of Freedom What is our sample size? 20 What is the degrees of freedom? 20 – 2 =18 Boys Scores Girls Scores 16098 26242 36888 47092 56338 66556 76595 85892 96450 106389
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What does it all mean? If your sample size is 10 and your t-value is 5.00, what is your probably (p-value) that the difference between two sets occurred by chance? Degrees of freedom (df) = 8 P-value is 0.001 which means there is a 0.1% chance that the difference occurred by chance. Thus the difference between the two data sets is probably statistically significant.
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Null Hypothesis H 0
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Significant Differences If you carry out a statistical significance test, such as the t-test, the result is a P value, where P is the probability that there is no difference between the two samples. – A. When there is no difference between the two samples: A small difference in the results gives a higher P value, which suggests that there is no true difference between the two samples
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Significant Differences If you carry out a statistical significance test, such as the t- test, the result is a P value, where P is the probability that there is no difference between the two samples. B. When there is a difference between the two samples: – A larger difference in results gives a lower P value, which makes you suspect there is a true difference (assuming you have a good sample size). – By convention, if P < 0.05 you say the result is statistically significant.
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P-Value Summary
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P-value & Null Hypothesis In biology the critical probability (P-value) is usually taken as 0.05 (or 5%). This may seem very low, but it reflects the facts that biology experiments are expected to produce quite varied results. If P > 5% then the two sets are the same (i.e. accept the null hypothesis). – Null hypothesis is always A PREDICTION stating that there is no significant differences between data sets. If P < 5% then the two sets are different (i.e. reject the null hypothesis). – Null hypothesis is always A PREDICTION stating that there is no significant differences between data sets.
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T-Test & Excel
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Your turn. Day 2 Run a T-test comparing the data sets to test to see if you have a significant difference between snail shells in habitats with and without crabs.. Screen shot you excel calculations and insert them into a word document. In an organized table report your p- value, t-value, degrees of freedom. State your null hypothesis. State whether you accept of reject your null hypothesis. Provide a reason for your statement in d. Your reason should include your p- values. Provide a scientific reason for your results.
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