T-Test and Anova Flashcards

1
Q

If 2 sets of data are completely separate, what would we do to compare them?

A
  • Complete a Spearman (p) correlation or Pearson(r) correlation to see if they are RELATED positively or negatively
  • Determine the coefficient of determination by squaring the correlation (p^2 or r^2)
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2
Q

If 2 sets of data are of the same parameter but for 2 independent groups, what would we do to compare them?

A

Conduct an independent t-test to determine if there is a significant difference between the means of the groups

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3
Q

If 2 sets of data are dependent and represent the same subjects in a pre-test/post-test scenario, what would we do to compare them?

A

Conduct a dependent t-test to determine if there is a significant difference between the means of the pre and post test

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4
Q

What is the t-test?

A

the statistical test to determine if there is a real difference between the means of 2 sets of scores

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5
Q

What is the Null Hypothesis (Ho)?

A
  • a statement that indicates that for the 2 sets of scores, the means for the test are pretty well the same
  • no significant difference between the means
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6
Q

When would we accept the null hypothesis?

A
  • when there is no significant difference

- if the t-test value is less than the critical value from the table value

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7
Q

When would we reject the null hypothesis?

A
  • when there is a significant difference in the means

- if the t-test value is greater than the critical value from the table value

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8
Q

Rejecting the null hypothesis is the same as …

A

accepting the alternative hypothesis (Hl)

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9
Q

What is the level of significance?

A

the probability of rejecting the null hypothesis when it is true

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10
Q

The most common levels of significance are…

A

.05 or .01

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11
Q

A .05 level of significance means that…

A
  • there is a 5% chance that you are rejecting the null hypothesis when it is true
  • there is a 5% chance that our conclusion will be wrong
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12
Q

Typically, we use what level of significance for physical education?

A
  • p = 0.05

- maybe p = 0.01 but not that common

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13
Q

What is the degrees of freedom?

A

the number of values that are free to vary in a distribution so that the mean is the same

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14
Q

How is the degrees of freedom calculated in independent samples?

A

df = n1 + n2 -1

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15
Q

How is the degrees of freedom calculated in dependent samples?

A

df = N - 1

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16
Q

When would we use t-test for independent samples?

A
  • when we want to find out if 2 groups of students differ significantly on a particular test
  • we want to know if one group is superior on some particular trait (ex. strength, fitness, skill)
17
Q

In medical research, we might use what level of significance?

A

p = .001

18
Q

In social science work, we might use what level of significance?

A

p = 0.10

19
Q

What is ANOVA?

A
  • analysis of variance
  • a statistical technique used to determine whether there are significant differences among means of three or more sets of data
20
Q

The test statistic we calculate in ANOVA tests is the

A

F ratio (instead of the t value)

21
Q

_______ is also one of the most commonly used statistical techniques used in sport science research.

A

ANOVA

22
Q

When is independent ANOVA used?

A
  • when the same test is administered to different groups
  • sample groups are not related to each other
  • The samples are randomly drawn from a normally distributed population
  • The variances of the samples are approximately equal
23
Q

When is ANOVA for repeated measures (dependent) used?

A

administration of different treatments given to the same group of subjects.

24
Q

What would we do after we accepted or rejected the Null for ANOVA tests?

A
  • if you accept the Null, you are done, do not do this

- if you reject the Null, you must do your Turkey’s Honestly Significant Difference (HSD) test

25
Q

If your HSD is 1.595655, this means that …

A

the means of the groups must differ by 1.59 to be honestly significantly different

26
Q

When is repeated measures (dependent) ANOVA used?

A
  • when repeated measures are made on the same subjects
  • The samples are randomly selected from a normal population
  • The variances for all measurements are approximately equal