Basic Terms and Definitions Flashcards Preview

Behavioral Statistics > Basic Terms and Definitions > Flashcards

Flashcards in Basic Terms and Definitions Deck (44):
1

Descriptive statistics

summarize, understand, and describe a group of numbers from a research study

2

What are examples of descriptive stats

1. measure of central tendency (mean, median, mode)
2. variability (range, varience, sd)

3

Inferential statistics

1. draw conclusions and make inferences based on numbers from a research study, but go beyond these numbers
2. if there is a difference between groups
3. how sure we are about our conclusions

4

Variable

condition or characteristic that can have different (varying) values (ex. male/female, ...22,23,24...,

5

Score

the value of a particular person's answer (ex. male, 25yrs old, 15 sexual partners)

6

Variability

how much change there is in a group of scores

7

Variance

a specific measure of variability

8

Correlational Research Designs

examines if there is a relationship between variables
- "what does knowledge of x tell us about y"
- naturally occurring variables

9

Experimental Research Designs

goal is to determine why something happens
- "what causes X?"
- control and manipulation of variables

10

Independent variable

variable that the researcher manipulates/changes

11

Dependent variable

variable that changes because of IV

12

Components of an experiment

1. Must have more than one level of IV
2. several, stable/reliable DVs
3. control variables
4. random assignment

13

Control variables

keeping everything else constant

14

Random assignment

purpose of random assignment is to create equivalent groups

15

Population

set of all cases of interest, generally a theoretical concept (not always measurable)

16

Sample

subset of population that is being studied; something to be concerned about is biased samples

17

Biased Samples

sample that systematically underselects or overselects from certain groups in the population

18

Parameter

Some characteristic of population

19

Statistic

some characteristic of sample

20

Scales of measurement

1. Nominal
2. Ordinal
3. Interval
4. Ratio

21

Nominal

mutually exclusive categories (yes or no)

22

Ordinal

placing variables in a "ranked" order (no, somewhat, yes)

23

Interval

equal distances between points on the scale (temp., on scale from 1-10 how helpful)

24

Ratio

exactly like interval scale, but has a true zero (#oof cigs smoked today)

25

IV measurement

often at a nominal level

26

DV measurement

Data analysis is limited when using nominal or ordinal data
- interval data is desirable

27

Unimodal data

only one very high area (mode)

28

Bimodal data

two very high areas

29

Multimodal data

many very high areas

30

Rectangular data

all values have about the same frequency

31

Symmetrical data

many psychological variables (height, weight, attitudes, work productivity); distribution looks the same on both sides if you split it down the middle

32

Skewed data

majority of responses are at low or high ends of the scale

33

Central tendency

a measure that refers to the typical score in a distribution
- "center of data," "best representation"

34

Measures of central tendency

mean, median, mode

35

mean

average - interval/ratio data

36

median

middle score - ordinal data (very skewed interval/ratio data)

37

mode

most frequent - nominal data - bimodal distribution

38

Properties of the mean

1. the value is the value around which all observed values are balanced
2. the point at which the sum of the squared deviations is minimized
3. influenced by extreme values (main disadvantage)

39

Variability

the spread of scores in a distribution

40

Types of variability

range, variance, standard deviation

41

Range

the distance between the larges and smallest scores (only reflects two most extreme scores

42

Variance

the sum of the squared deviations from the mean, divided by N-1

43

Steps for calculating the varience

1. subtract the mean from each of the scores to get deviations
2. square each deviation
3. add all squared deviations
4. divide by the total number of scores minus 1

44

Standard deviation

the most widely used measure of variability (square root of variance)