T-Tests, ANOVAS, ANCOVAS Flashcards

(33 cards)

1
Q

T-Tests are:

A
  1. Test whether the regression coefficient (b), is significantly different from zero
  2. Provides some idea of how well a predictor predicts the outcome variable
  3. Can be used to see whether a predictor variable makes a statistically significant contribution to the regression model
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2
Q

Independent T-Test

A

Tests for differences between means of groups containing different participants when the sampling distribution is normal, the groups have equal variances and data are at least interval

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3
Q

Paired Samples T-Test

A
  1. Same participants take part in both experimental conditions
  2. Ought to be less unsystematic variance compared to the independent t-test
  3. Other things being equal, you do not need as many participants as you would for an independent samples design
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4
Q

T Distribution becomes closer to normal when…

A

Degrees of freedom increase

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5
Q

One-Sample T Test Assumptions

A

IV is continuous, independent scores, normal distribution, homogeneity of variances

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6
Q

One- Sample T Test

A

Compares the mean of the sample data to a known value (IQ of class compared to IQ of society)

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7
Q

Independent Sample T-Test Assumptions

A

Independence of groups, normal distribution, equal variances, homogeneity of variances, DV is interval or continuous, IV is categorical

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8
Q

Independent Samples T-Test

A

Most common form of T Test
Compares the differences between the means of groups containing different participants when the sampling distributions is normal, the groups have equal variances, and data are at least interval

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9
Q

Paired T Test Assumptions

A

DV is continuous, related samples, normal distribution

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10
Q

Paired T Test

A

Compares the means between two related groups on the same continuous, dependent variable (same group will be used in both trials)

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11
Q

ANOVA stands for…

A

Analysis of variance

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12
Q

When should ANOVA be used?

A

if you are comparing more than 2 groups

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13
Q

Family Wise Error

A

alpha level is our probability of rejecting the null hypothesis when the null hypothesis is true

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14
Q

How can you avoid/minimise family wise error?

A

adjusting the alpha level by (finish on slide)

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15
Q

Bonferroni test, tests what?

A

Guarantees control over type 1error, test to investigate which groups differ in a 1-way ind ANOVA

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16
Q

When the between-groups variance is a lot larger than the within-groups variance, the F-value is ____ and the likelihood of such a result occurring because of sampling error is _____

17
Q

Imagine you compare the effectiveness of four different types of stimulant to keep you awake while revising statistics using a one-way ANOVA. The null hypothesis would be that all four treatments have the same effect on the mean time kept awake. How would you interpret the alternative hypothesis?

A

At least two of the stimulants will have different effects on the mean time spent awake

18
Q

An experiment was done to look at whether different relaxation techniques could predict sleep quality better than nothing. A sample of 400 participants were randomly allocated to one of four groups: massage, hot bath, reading or nothing. For one month each participant received one of these relaxation techniques for 30 minutes before going to bed each night. A special device was attached to the participant’s wrist that recorded their quality of sleep, providing them with a score out of 100. The outcome was the average quality of sleep score over the course of the month.

Which test could we use to analyse these data?

A

Regression or ANOVA

19
Q

Differences between group means can be characterized as a regression (linear) model if:

A

The experimental groups are represented by a binary variable (i.e. code 1 and 0).

20
Q

Other things being equal, compared to the paired-samples (or dependent)t-test, the independent-test:

A

Has less power to find an effect.

21
Q

Standard error…

A

It is the standard deviation of the sampling distribution of a statistic

22
Q

In t-distribution, as the df increase the distribution becomes closer or further away from normal

23
Q

Partial eta squared is reported for…

A

ANOVA and ANCOVA

24
Q

Assumptions of ANOVA

A
  1. Independence of data
  2. DV is continuous, IV is categorical
  3. No significant outliers
  4. DV is approximately normally distributed for each category of the IV
25
ANCOVA is an extension of...
Multiple Regression
26
ANCOVA allows you to test...
All the regression lines to see which have different intercepts as long as all your slopes are equal
27
Unlike an ANOVA and ANCOVA also...
1. Controls for covariance 2. Studies combinations of categorical and continuous variables, the covariate becomes the variable of interest RATHER than the one you control
28
In a study where we test if technique has an impact on exam scores, but we want to account for the students current grade what is the covariate?
The current grade
29
Assumptions of ANCOVA
1.Independent variables should be categorical variables. 2. The dependent variable and covariate should be continuous variables (measured on an interval scale or ratio scale.) 3. Make sure observations are independent - don’t put people into more than one group. 4. Normality: the dependent variable should be roughly normal for each of category of independent variables. 5. Data (and regression slopes) should show homogeneity of variance. 6. The covariate and dependent variable (at each level of independent variable) should be linearly related. 7. Your data should be homoscedastic 8. The covariate and the independent variable shouldn’t interact. In other words, there should be homogeneity of regression slopes.
30
What do we partition in an ANCOVA?
Total variance into IV, DV, and covariate
31
What do we partition in an ANOVA
Total variance into IV and DV
32
Dummy Variables in an ANOVA
Binary value (0 or 1) Control is always 0 One value will be 1 the other 0, they will not both be one
33