01 SB-1203 Lecture 7_t-test & F-test frm miss

# 01 SB-1203 Lecture 7_t-test & F-test frm miss - SB 1203...

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SB 1203 Skills in Biological Sciences Lecture 7: t-tests & F-tests

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Hypothesis testing Biological (or research) hypothesis – a concise statement about the predicted or theorised nature of a population or populations It usually proposes that there is an effect of a treatment Logically, theories (and thus biological hypothesis) cannot be proved, only disproved Therefore, a null hypothesis (H 0 ) is formulated to represent all possibilities except the hypothesised prediction (i.e. H 1 ) Evidence against the null hypothesis (i.e. rejecting H 0 ) therefore provides evidence that the biological hypothesis (H 1 ) can be accepted
T-tests & F-tests Both t-tests and F-tests are used when we want to compare just two populations We use a t-test to answer the question: How confident can I be that the two populations have different means ? We use an F-test to answer the question: How confident can I be that the two populations have different variances ? Another version of the t-test can be used to test whether the mean of one population is a particular value i.e. The one-sample t-test

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Interpreting the results – t-tests The result of a t-test is a t-value (or t-statistic or t calculated ): Once you obtain this value, you look it up in a t-table to obtain an equivalent p-value at that particular df If p-value < 0.05 , the result is significant and you can conclude that the means of the two samples are significantly different from each other If p-value ≥ 0.05 , the result is not significant and you can conclude that the means of the two samples are not significantly different from each other Statistical software will give the p-value automatically
Interpreting the results – F-tests The result of a F-test is an F-value (or F-statistic or F calculated ): Once you obtain this value, you look it up in an F-table to obtain an equivalent p-value at that particular df If p-value < 0.05 , the result is significant and you can conclude that the variances of the two samples are significantly different from each other If p-value ≥ 0.05 , the result is not significant and you can conclude that the variances of the two samples are not significantly different from each other Statistical software will give the p-value automatically

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One-sample t-test Used to test the null hypothesis (H 0 ) that a population parameter is equal to a specific value i.e . H 0 : µ = θ
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