Between Subject T tests Flashcards

1
Q

What type of data is used in between-subject tests?

A

Continuous data (scale data) e.g scores out of 10, temperature

Examples include scores out of 10 and temperature.

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2
Q

What question does the t test help answer?

A

Are two means significantly different from each other?

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3
Q

What does the t statistic represent?

A

t = variance explained by our IV / unexplained variance

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4
Q

What is the most common test of normality?

A

Shapiro-Wilk test

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5
Q

What does a large p value from the Shapiro-Wilk test indicate?

A

No significance - we want this

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6
Q

What is the p value threshold for the Shapiro-Wilk test to meet the assumption for normality?

A

Greater than 0.05

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7
Q

What does a one sample T-test compare?

A

Data from your experiment with one single number

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8
Q

What are the assumptions for a one sample T-test?

A
  • Data are independent - one score per person
  • Data are continuous - interval or ratio
  • Data are normally distributed
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9
Q

What is the non-parametric alternative to a one sample T-test?

A

One Sample Wilcoxon signed-rank test

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10
Q

What is the design of an independent samples T-test?

A

Between subjects design

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11
Q

What are the assumptions for an independent samples T-test?

A
  • Data are independent - one score per person
  • Data are interval or ratio
  • N of at least 12
  • Data are normally distributed
  • Homogeneity of Variance
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12
Q

What does homogeneity of variance refer to?

A

Is the variance in condition 1 similar to the variance in condition 2

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13
Q

What is Levene’s Test used for?

A

For equality of variance

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14
Q

What is the desired outcome for p value in Levene’s Test?

A

p > .050 = no significant difference

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15
Q

What does a Q-Q plot help visualize?

A

Homogenous data will fall roughly on the diagonal line

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16
Q

What is the non-parametric alternative to an independent samples T-test?

A

Mann-Whitney U Test

17
Q

What reporting elements are included when presenting results?

A
  • Data Handling
  • Descriptive Statistics
  • Which test? And why
  • Assumptions
  • Test statistic, df, p