Parametric and Non-Parametric Tests Flashcards

1
Q

Parametric vs Non-Parametric: Distribution

A

Parametric: Equal
Non Parametric: Unequal Distribution

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2
Q

Parametric vs Non-Parametric: Randomization

A

Parametric: Randomization of Sample
Non-Parametric: No Randomization

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3
Q

Parametric vs Non-Parametric: Curve Characteristics

A

Parametric: Bell Shaped Curve: Normal Distribution
Non-Parametric: Skewed Curve

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4
Q

Parametric vs Non-Parametric: Data Types

A

Parametric: Interval or Ratio
Non-Parametric: Nominal or Ordinal

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5
Q

What type of research is considered to be more “powerful” parametric or non-parametric?

A

Parametric

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6
Q

What is a T-Test? Parametric or Non

A

Parametric

  • Compares the difference between 2 independent groups
  • Equal sized groups
  • Different Characteristics

e.g: 30 athletes vs 30 non-athletes

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7
Q

What is a paired T-Test?

A

Compares difference between 2 matched samples

  • Paired; sample characteristics are the same

e.g: Comparing 30 of the same athletes pre and post training

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8
Q

Are Tailed Tests exclusive to either paired or independent t-tests?

A

No, tailed tests can be used for both types

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9
Q

Why would we implement a 1 tailed test?

A

If we have an hypothesis and we are inferring/know the direction of the hypothesis/tail.

  • Directional Hypothesis

e.g: comparing pre and post test, we can infer the post test scores would be better

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10
Q

Why would we implement a 2 tailed test?

A
  • Non-direction
  • 2 ends of distribution positive or negative

Done when we cannot assume which group would be better or worse based on our hypothesis

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11
Q

When would we use an ANOVA?

A

When we have greater than 2 groups with equal sample size in each group

  • Parametric
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12
Q

When to use a One Way Anova

A

More than 2 independent groups compared on 1 intervention/variable

e.g Comparing 30 Gymnasts to 30 Football players to 30 baseball players with an exercise

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13
Q

When to use a 2-Way ANOVA

A

More than 2 independent groups compared on 2 interventions/variables

e.g Comparing 30 Gymnasts to 30 Football players to 30 baseball players with an exercise and gender

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14
Q

When to use a repeated measures ANOVA?

A

When we are trying to measure individuals over time

  • Repeatedly looking at the same group
  • At baseline
  • 2 weeks
  • 4 weeks
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15
Q

What is an ANCOVA?

A

Comparing more than 2 groups while controlling for covariance.

  • Trying to control this to eliminate bias
  • Eliminated the covariance
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16
Q

What is covariance?

A

A variable that has the potential to strongly influence the results

17
Q

What is a Chi-Squared Test? Type of Data it used?

A
  • Non-Parametric
  • Nominal or Ordinal
  • Trying to find the difference between two groups that are mutually exclusive to each other
18
Q

Type of data used in a Mann-Whitney U?

A

Continuous or Ordinal Data, to test the null hypothesis with 2 independent samples from the same population

19
Q

When is a Kruskal Wallis Test used?

A
  • Non-Parametric
  • compares 3 or more groups

Similar to an ANOVA

20
Q

An unpaired/independent T-Test is similar to what type of non-parametric test?

A

Mann-Whitney U

21
Q

A Paired/dependent-T test is similar to what type of non-parametric test?

A

Wilcoxon Signed Rank Test

22
Q

An ANOVA is similar to what type of non-parametric test?

A

Kruskal Wallis Test

23
Q

The Pearson Product Correlation is similar to what type of non-parametric correlation?

A

Spearman Rho Correlation