Biostatistics Exam 3 with verified solutions

Paired Design - correct answer ✔Both treatments are applied to every sampled
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unit.
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Two-Sample Design - correct answer ✔Each treatment group is composed of an
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independent, random sample of units.
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Paired t-test - correct answer ✔Used to test a null hypothesis that the mean
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difference of paired measurements equals a specified value.
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Paired t-test Assumptions - correct answer ✔1) The sampling units are
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randomly sampled from the population.
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2) The paired differences have a normal distribution in the population.
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Standard Error of Y₁-Y₂ - correct answer ✔√s²p((1/n¹)+(1/n₂))
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Pooled Sample Variance - correct answer ✔s²p=(df₁s²₁+df₂s²₂)/(df₁+df₂) The
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average of the variances of the samples weighted by their degrees of freedom.
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Two-Sample t-test - correct answer ✔The simplest method to compare the
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means of a numerical variable between two independent groups.
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t=(Y₁-Y₂)/SEy₁-y₂

, Two-Sample t-test Assumptions - correct answer ✔1) Each of the two samples
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is a random sample from its population.
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2) The numerical variable is normally distributed in each population.
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3) The standard deviation (and variance) of the numerical variable is the same
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in both populations.
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Welch's Approximate t-test - correct answer ✔Compares the means of two
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groups and can be used even when the variances of the two groups are not
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equal.
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F-test - correct answer ✔Tests whether the variances of two populations are
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equal. F=s²₁(larger sample variance)/s²₂ (smaller sample variance)
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F-test Assumptions - correct answer ✔1) Both samples are random samples
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2) The numerical variable is normally distributed within both populations.
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Levene's Test - correct answer ✔Tests the difference between the variances of
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two or more populations.
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Levene's Test Assumptions - correct answer ✔1) Both samples are random
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samples
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2) The distribution of the variable is roughly symmetrical in both populations.
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Four Alternative Options for Analyzing Data that do not meet assumptions -
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correct answer ✔1) Ignore the violations of assumptions
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2) Transform the data
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