lecture 7 + 10 (stats) Flashcards

1
Q

What is an independent t-test used for?

A

to compare two means from different groups (i.e., independent conditions)

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2
Q

When is a paired-samples t-test used?

A

A paired-samples t-test, or dependent t-test, is used to compare two means from the same or related entities (i.e., repeated measures or matched samples)

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3
Q

What is the rationale behind the t-test?

A

if two samples come from the same population, their means should be roughly equal under the null hypothesis, and any difference reflects sampling variation

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4
Q

steps to get a t distribution?

A
  1. take a random sample from a population
  2. calculate the mean and the standard deviation of the sample
  3. determine the SE of the sample
  4. calculate t statistic
  5. repeat the process with multiple random samples of the same size
  6. Each sample’s t-value will make up the t distribution (which is a sampling distribution)
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5
Q

what is the t statistic?

A

represents the deviation of the sample mean from the population mean, considering the sample size, expressed as the degree of freedom = n – 1

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6
Q

large sample size and its consequences?

A
  • the higher the sample size the lower the SE
  • when sample size large enough, t distribution is normally distributed
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7
Q

What is the role of the standard error in a t-test?

A

measures how much sample means fluctuate, allowing comparison of the observed mean difference to the expected difference under the null hypothesis

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8
Q

main difference paired samples and indepedent t test equation?

A
  • how we arrive at the values of interest
  • with independent samples we’re not dealing with difference scores because there’s no connection between scores in the two conditions that we want to compare
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9
Q

independent t test equation and sample sizes?

A

equation is only true when the sample sizes are equal

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10
Q

How do you run an independent t-test in JASP?

A
  1. Click on t-test in the analysis menu
  2. Select “Classical Independent Samples t-test.”
  3. Transfer the outcome variable to the variable box and the predictor variable to the grouping box.
  4. Set confidence intervals (CI) and effect size options
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11
Q

How do you run a paired-samples t-test in JASP?

A
  1. Select “Classical Paired Samples t-test.”
  2. Transfer pairs of variables to the variables pairs box.
  3. Ensure effect size and Cohen’s d are selected.
  4. If using repeated measures, select “Correct for Correlations.”
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12
Q

What additional statistics should you report in a t-test?

A

Report confidence intervals (CI) for parameters and effect size, such as Cohen’s d

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13
Q

effect size d (Cohen’s d)?

A
  • the standardized difference between the mean and the expected μ
  • in the t-test, effect-size can be expressed as d (Cohen’s d)
  • independent of sample size
  • 0 to 0.1 small effect sizes, 0.1 to 0.3 medium effect sizes, 0.3 to 0.5 large effect sizes
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14
Q

effect size r?

A
  • another way to express effect size
  • similar to correlation coefficient
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15
Q

Why do paired-samples t-tests have more statistical power than independent samples t-tests?

A

because they reduce unsystematic variance by using the same participants across conditions, making it easier to detect systematic variance

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16
Q

How should comparisons between two means be reported?

A

State the finding alongside the test statistics, degrees of freedom, probability value, effect size, and include a visual aid like a raincloud plot

17
Q

assumptions independent t test?

A
  • independence of observations
  • normality
  • equal variances
18
Q

check homogeneity on jasp?

A

with levene test

19
Q

check normality assumption on jasp?

A
  • using hypothesis test (Shapiro-Wilk): p < a -> assumption violated
  • Assess using a plot (Q-Q plot): Points should be along the diagonal
20
Q

how to handle violations on jasp?

A
  • Unequal variance: Welch t-test
  • Non-normality: nonparametric test
21
Q

assumptions of paired samples t testing?

A
  • differences between paired observations should be indepedent
  • normality of differences
22
Q

assumptions NHST?

A
  • random sampling
  • normality
  • measurement level (interval or ratio)
23
Q

t vale for two sided NHST test?

A

Need a higher t-value when doing a two-sided test since the alpha is spread across two tales