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Flashcards in Stats 2 First Exam Deck (61)
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1

Descriptive research

Describes population we are studying

2

Central tendency demonstrates

Mid-points

3

Spread

Range, SD, D, etc.

4

Frequency

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

5

Inferential research

Infer from the sample to the population

6

Parameter

Value corresponding to population

7

Statistic

Value corresponding to sample

8

Historical research

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

9

Regression

Type of correlation research positing temporal order of variable

10

Causal-Comparative

Allows for making causal statements

11

Ex-post facto

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

12

Pre-experimental designs

Are limited. Example: One-shot case study

13

Quasi-experimental design

Control group and experimental group but no randomization.

14

True experimental design

Researcher manipulation and randomization

15

Meta-analyses

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

16

Continuous variable

Allows values in-between

17

Categorical variable

Groups, no in-between

18

Fixed variable

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

19

Random variable

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

20

Multivariate

More than one DV

21

Univariate

One DV

22

Multiple regression

More than one IV

23

Factorial

More than one IV with analysis of variance

24

Sampling distribution

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

25

Central limit theorem

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

26

Mean distribution

Unit normal curve

27

Chi square distribution

Summation of variances

28

T distribution

Difference between means divided by standard errors

29

F distribution

Variances compared as ratio

30

Why is normal curve mother of all curves?

Given an infinite number of samples for any statistic, all will collapse to normal curve