Flashcards in Stats 2 First Exam Deck (61)

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## Descriptive research

### Describes population we are studying

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## Central tendency demonstrates

### Mid-points

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## Spread

### Range, SD, D, etc.

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## Frequency

### Number of times it occurs, percent/portion of time it occurs: n, f, p

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## Inferential research

### Infer from the sample to the population

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## Parameter

### Value corresponding to population

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## Statistic

### Value corresponding to sample

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## Historical research

### Looking at past using causal comparative, descriptive, and inferential analysis

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## Regression

### Type of correlation research positing temporal order of variable

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## Causal-Comparative

### Allows for making causal statements

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## Ex-post facto

### Identify settings with differing characteristics and assume difference in results is due to different characteristics

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## Pre-experimental designs

### Are limited. Example: One-shot case study

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## Quasi-experimental design

### Control group and experimental group but no randomization.

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## True experimental design

### Researcher manipulation and randomization

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## Meta-analyses

### Aggregate results from many different studies (frequently based on effect sizes)

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## Continuous variable

### Allows values in-between

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## Categorical variable

### Groups, no in-between

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## Fixed variable

### Allows only certain range (e.g., ages 20-40)

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## Random variable

### Allows all possibilities. Each has equal and independent chance of occurring

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## Multivariate

### More than one DV

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## Univariate

### One DV

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## Multiple regression

### More than one IV

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## Factorial

### More than one IV with analysis of variance

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## Sampling distribution

### Graph statistics of infinite number of samples (graph of means)

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## Central limit theorem

### Graph of means will be equal to population mean (The mean of the means (Samples) is the mean (population mean)

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## Mean distribution

### Unit normal curve

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## Chi square distribution

### Summation of variances

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## T distribution

### Difference between means divided by standard errors

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## F distribution

### Variances compared as ratio

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