Statistics Unit 1 Test

Front 1

(1)Statistics

Back 1

A field of study that measures, organizes, and interprets data

Front 2

Data

Back 2

Information/results

Front 3

Empiracle field

Back 3

Truths that are based on evidence/data

Front 4

Descriptive Statistics

Back 4

Involves using numbers to condense or describe a larger group of numbers

Front 5

Inferential Statistics

Back 5

Involves researchers drawing conclusions or making inferences about a large group of numbers based on the data from a smaller sub-group of numbers

Front 6

Population

Back 6

Each and every member of a defined group; impossible to deal with all at the same time

Front 7

Sample

Back 7

A sub-group of the population that can be mamanged

Front 8

Random sample

Back 8

Each and every member of the population has an equal probability of being selected for the inclusion in the sample; impossible to achieve

Front 9

Parameters

Back 9

Pulling numbers from the population; numerical characteristics of a population

Front 10

(2) Statistics

Back 10

numerical characteristics of samples

Front 11

Sampling Error

Back 11

the discrepancy btw a statistic and its corresponding parameter

Front 12

Biased Sample

Back 12

both over select and under select from certain subgroups in the population

Front 13

Variable

Back 13

anything that changes or varies

Front 14

Quantitative

Back 14

variable dealing with amount

Front 15

Qualitative

Back 15

variable not involving amounts

Front 16

Real Limits

Back 16

refers to the range of possible values for a score on a quantitative variable

Front 17

Nominal Scale

Back 17

-using numbers as labels or names

-no indication of value

-qualitative and nominal are the almost interchangeable

Front 18

Ordinal Scale

Back 18

-allows us to distinguish one thing from another

-some indication of value; more or less of something being measured

-lacks equal intervals

Front 19

Interval Scale

Back 19

-has a value indication/allows distinction

-equal intervals/spacing btw score values

-does not have a true zero point

Front 20

Ratio Scale

Back 20

-allows distinction/indication of value/equal intervals

-expresses a true zero point

Front 21

S.S. Stevens

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Who came up with the 4 scales of measurement?

Front 22

Lord

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Who argued with Stevens about the scales of measurement?

Front 23

"Numbers don't know where they came from." AKA quit relying on the scale, instead use your brain to extract as much meaning from the data as possible

Back 23

What was Lord's argument?

Front 24

Correlational Research

Back 24

type of research where the goal is to describe the degree of association btw two or more variables

Front 25

Experimental Research

Back 25

Research where the goal is to determine a cause and effect relationship between two variables

Front 26

Surveys

Back 26

type of research with a standardized list of questions

Front 27

Naturalistic Observation

Back 27

Research where the variables are recorded as they change in their natural habitat

Front 28

Case Study

Back 28

research used extensively in the medical community; defined as a highly detailed investigation of a single person

Front 29

Operational Definitions

Back 29

specifying in precise terms, exactly what is meant by each of the variables

Front 30

Confounding/Extraneous Variables

Back 30

variables other than the IV, that could potentially impact the DV

Front 31

Mean

Back 31

arithmetic average that finds the balance point

Front 32

x̄ = ( Σ x ) / n

Back 32

Formula for the mean

Front 33

Interval and ratio scales

Back 33

Which scales of measurement is the mean appropriate for?

Front 34

Median

Back 34

the middle most score; equal number of scores that fall below and above it

Front 35

Ordinal Scale

Back 35

Which scale of measurement is appropriate for the median?

Front 36

Mode

Back 36

the most often occurring score

Front 37

Nominal

Back 37

The mode is the only measure of central tendency that can be used for the... scale of measurement

Front 38

Normal Distribution

Back 38

symmetrical distribution with an asymptotic tail that is also called the bell curve; 3 measures of central tendency are all equal

Front 39

Asymptotic tail

Back 39

never reaches the abscissa but gets closer and closer into infinity

Front 40

Normal Distribution

Back 40

Distribution in which we assume fits the population because of its high frequency of occurrence

Front 41

Positively Skewed Distribution

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Distribution in which there is a disproportionately large numbers of low scores and a few extreme high scores

Front 42

Positively Skewed Distribution

Back 42

Front 43

Negatively Skewed Distribution

Back 43

Distribution in which there is a disproportionately large number of high scores and a few extreme low scores

Front 44

Negatively Skewed Distribution

Back 44

Front 45

Bi-modal Distribution

Back 45

A distribution in which there are 2 curves or 2 modes in the data set; 2 high frequency sets of scores

Front 46

Bi-modal Distribution

Back 46

Front 47

Measures of Central Tendency

Back 47

Mean, Median, Mode

Front 48

Measures of Variability

Back 48

Range, Inter Quartile Range, Variance, and Standard Deviation,

Front 49

Range

Back 49

the distance btw the highest and lowest scores in a distribution

Front 50

(1) XH - XL =

(2) ULXH - LLXL =

Back 50

Formulas for the range

Front 51

Inter Quartile Range

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the distance btw the 3rd and the 1st quartile

Front 52

Ordinal

Back 52

The range and inter quartile range are the appropriate measures of variability for the... scale of measurement

Front 53

Standard Deviation

Back 53

most widely used measure of variability that is the approximation of the average distance of scores from the mean

Front 54

Back 54

formula for population standard deviation

Front 55

Back 55

formula for a sample standard deviation

Front 56

Back 56

Variance formula

Front 57

Variance

Back 57

a measure of how spread out a data set is

Front 58

1. Change raw scores into deviation scores (X- μ)

2. Square the Deviation Scores

3. Calculate the sum of squares [Σ (x - x̄)2]

4. Analysis of Variance

5. Take the square root of the variance

Back 58

The Five steps to finding population variance

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underestimate

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samples tend to underestimate/overestimate the variability in the population

Front 60

Z-scores

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Specifies the precise location of its corresponding raw score within a distribution; the sign of the *blank* indicates whether the raw score is above or below the mean, while the absolute value of the *blank* indicates the number of standard deviations btw the raw score and the mean

Front 61

Standardize

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What do Z-scores do to the data?

Front 62

z = (x – μ) / σ [Population]

z = (x – μ) / S [Sample]

Back 62

Z-score formulas