SIRBL Flashcards

1
Q

Statistics used to analyze nominal and ordinal data are referred to as

A

nonparametric tests.

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2
Q

do not involve the use of any population parameters. In other words, mean and standard deviation are not needed, and the underlying distribution does not have to be normal.

A

Nonparametric tests

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3
Q

is a nonparametric statistical test used for comparing categorical information against that we would expect based on previous knowledge. As such, it tests the observed frequency against the expected frequency

compares how well an observed frequency distribution of one nominal variable fits some expected pattern of frequencies

the data are in frequencies

A

The Chi-Square (X2) Goodness-of-fit Test

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4
Q

*related in chi square

simply count how many individuals from the sample are in each category

A

Observed Frequency

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5
Q

Is a statistical technique for finding the best-fitting straight line for a set of data. The resulting line is called the regression line.

A

Regression

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6
Q

is used when you want to predict variables. (e.g., how much will be the jeepney fare if the distance is 5 kilometers?)

A

Regression

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7
Q

is a model building.

A

Regression

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8
Q

The is used to determine whether a sample comes from a population with a specific mean.

A

one-sample t-test

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9
Q

The ________________ is a parametric statistical test that compares the means of two different samples of participants. It indicates whether the two samples perform so similarly that we conclude they are likely from the same population or whether they perform so differently that we conclude they represent two different populations.

control vs treatment group design

A

independent-groups t-test

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10
Q

The ____ compares the means between two related groups on the same continuous, dependent variable.

A

dependent t-test (called the paired-samples t-test in SPSS Statistics)

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11
Q

-assumes that the source population is normally distributed

A

Parametric Tests

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12
Q

-does not make assumptions on the source population

A

Non-parametric tests

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13
Q

is a type of inferential statistic used to determine if there is a significnt difference between the means of two groups, which may be related in certain features.

A

T-test

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14
Q

is a statistical test that is used to compare the means of two groups.

it is often used in hypothesis testing to determine whether a process or treatment actually has an effect on the population of interest, or whether two groups are different from one another.

A

T-test

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15
Q

Is there a difference between a group and the population

A

One Sample t-test

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16
Q

Is there a difference between two groups

A

Independent T-test

17
Q

Same group measured twice
pre and post test

indicates whether there is a difference in teh sample means and wheteher this difference is great than would be expected based on chance

includes two scores for each person

A

Paired T-test

18
Q

is there a difference in a group between two points in time

A

Paired samples t-test

19
Q

Correlation is a statistical technique that is used to measure and describe the relationship between two variables.

neither variable is manipulated.

A

Correlation

20
Q

*Related with correlation

in which higher scores on one variable tend to be associated with higher scores on the other.

A

positive relationship,

21
Q

*related with correlation

is one in which higher scores on one variable tend to be associated with lower scores on the other.

A

A negative relationship

22
Q

Is a hypothesis testing procedure that is used to compare the differences in the means of two or more groups.

can compare two or more treatments.

A

ANOVA

23
Q
  • the variable that distingiushes the groups in ANOVA is called
A

Factor (independent variable)

24
Q

The invidual conditions or values that define the factor in ANOVA are called the

A

Levels of the factor

25
Q

Is used in conjunction with ANOVA to identify exaclty the comparisons that have a significant difference.

A

Post hoc test