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Research Methods > Chapter 9 - Statistics > Flashcards

Chapter 9 - Statistics Flashcards

1
Q

What two things do statistics inform about?

A
  1. Reliability

2. Meaningfulness

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2
Q

What are the most fundamental components of most statistical techniques?

A

Measures of central tendency and variability.

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3
Q

What does the nominal level of measurement provide info about?

A

About difference, but not much more. It is used to name, identify, or classify into categories.

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4
Q

What does the ordinal level of measurement provide info about?

A

Shows direction of difference, but we do not know amount of difference. Numbers indicate rank or order, allow for greater or less than.

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5
Q

What does the interval level of measurement provide info about?

A

The intervals or distances between numbers, but it is not known how far any of the numbers are from zero. There is an equality of units, but no true zero.

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6
Q

What does the ratio level of measurement provide info about?

A

Each number can be thought of as a distance measured from zero.

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7
Q

What does the absolute zero point in the ratio level of measurement represent?

A

It represents the absence of the variable being measured.

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8
Q

What is non-parametric data?

A

Data that does not meet the assumption of normality.

i.e. Nominal, ordinal levels.

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9
Q

What is parametric data?

A

Data that does meet the assumption of normality.

i.e. Interval, ration levels.

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10
Q

What does variability estimate and what is its formula?

A

It is the best estimate of the spread of scores.

s^2 = The sum of ((X - Xav)^2) / (N - 1)

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11
Q

What are the levels of a normal distribution?

A

+1 sd = 68%
+2 sd = 95%
+3 sd = 99%

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12
Q

What does positive skewness look like?

A

Peak near the y-axis.

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13
Q

What does negative skewness look like?

A

Peak far away from the y-axis.

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14
Q

What does kurtosis represent?

A

Peakedness of distribution.

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15
Q

What does the leptokurtic distribution look like?

A

Strong peak.

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16
Q

What does the platykurtic distribution look like?

A

No peak, close to even distribution throughout.

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17
Q

What does correlation measure?

A

A measure of the strength of the relationship between two variables, X and Y.

18
Q

What does the pearson product-moment correlation assume?

A

That the X and Y variables are normally distributed and are interval or ratio scale scores.

19
Q

What is the spearman rank-order correlation used for?

A

It is used for ordinal scale data, or interval or ration scale data that deviate substantially from normality.

20
Q

What is the pearson r relationship independent of?

A
  1. The # of scores.
  2. The size of scores.
  3. The dispersion of scores.
21
Q

What is pearson r derived from?

A

Covariance.

22
Q

What is covariance?

A

How much the deviations in the mean of your X variable related to the deviations in the mean of your Y variable.

23
Q

Null Hypothesis:

A

The observed correlation is due to error.

24
Q

When is r significant?

A

When it meets or exceeds the tabled critical value of r.

25
Q

What is statistical significance based on?

A

Largely based on sample size.

26
Q

When are one-tail significance levels used?

A

When the direction of the correlation has been predicted in advance.

27
Q

What does causation depend on?

A

Depends on methodology, not analysis.

28
Q

One Sample t-test:

A

Comparing one sample to the population. You need to know the population mean.

29
Q

Chi-square goodness of fit test:

A

When your data is not normally distributed but you still want to compare it to the population.

30
Q

Independent t-test:

A

Compare two independent samples (between factor).

Has a normal distribution, also called a two sample t-test.

31
Q

Dependent t-test:

A

Compares scores from the same or matched sample (within factor). One observation does depend on the other. Has a normal distribution.

32
Q

Mann-Whitney U:

A

When the data is skewed, not normally distributed.

Non-parametric independent sample test.

33
Q

Wilcoxon t-test:

A

Want to look at pre and post test but the data is not normally distributed.
Non-parametric dependent sample test.

34
Q

ANOVA:

A

Analysis of variance.

35
Q

One-way ANOVA:

A

One independent variable, normally distributed.

36
Q

Repeated measures one-way ANOVA:

A

Repeatedly measuring one group over time. Normally distributed.

37
Q

2 x 2 Split-Plot Factorial ANOVA:

A

Two independent variables. Between factor, time factor.

38
Q

Randomized factorial ANOVA

A

All groups are independent of each other. There are two IV. No within factors.

39
Q

MANOVA:

A

Has more than one DV.

40
Q

ANCOVA or MANCOVA:

A

Allows you to control for a third variable.

41
Q

What is regression used for?

A

Prediction and/or explanation

Research Methods (7 decks)

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