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?

18
Q

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

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.

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
If your HSD is 1.595655, this means that ...
the means of the groups must differ by 1.59 to be honestly significantly different
26
When is repeated measures (dependent) ANOVA used?
- 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