Unit 12: Analyzing Quantitative Data

Question 1

level of measurement

Answer 1

is away to classify quantitative measure

Question 2

levels of measurement

Answer 2

1.nominal measurement - involves using numbers simply to categorize attributes
> provided information only about categorical equivalence and non equivalence
2. ordinal measurement ranks objects on their relative standing on an attribute.
3. interval measurement occurs when researcher can specify the ranking of objects on an attribute and the distance between those objects.
4. ratio measurement is the highest level of measurement. have meaningful zero
>provide information about the absolute magnitude of the attribute

Question 3

descriptive statistic

Answer 3

statistic used to describe and summarize data

Question 4

parameter

Answer 4

indexes are calculated on data from a population

Question 5

statistic

Answer 5

a descriptive index from sample

Question 6

frequency distribution

Answer 6

is a systematic arrangement of numeric values from lower to highest, together with a count or percentage of the number of times each value was obtained

Question 7

symmetric distribution

Answer 7

occurs of when folded over, the two halves of frequency polygon would be superimposed

Question 8

skewed distribution

Answer 8

asymmetric distribution when the peak of off center and one tail is longer than the other

Question 9

positive skew

Answer 9

is tail is longer of the right side

Question 10

negative skew

Answer 10

is tail is longer on the left side

Question 11

normal distribution

Answer 11

bell shape is a symmetric unimodal and not very peaked

Question 12

central tendent

Answer 12

a stat index of the typicality of a set of scores, derived from the center of the score distribution; indexes of central tendency include the mode, median and mean

Question 13

variability

Answer 13

the degree to which values on a set of scores are dispersed

Question 14

range

Answer 14

the highest score minus the lower score in a distribution

Question 15

standard deviation

Answer 15

the most widely used variability. it is calculated based on every value in a disturbance. summarizes the average amt of deviation of values from the mean

Question 16

bivariate descriptive statistics

Answer 16

two variable descriptive statistic describe relationship between two variable
>contingency table is two dimensional freq distribution in which the freq of two variable cross tabulated
»correlation. relationship between two variables, positive or negative
range from-1 to 0 or 0-1

Question 17

cross tabulation

Answer 17

a determination of the # of cases occurring when two variable are considered simultaneously. the results are typically presented in a table with rows and columns divided according to the values of the varaible

Question 18

product moment correlation coefficient

Answer 18

persons r which is computed with interval or ration measures

Question 19

spear’s rank order correlation

Answer 19

r(s) or spearman’s rho one correlation index for ordinal measure

Question 20

correlation matrix

Answer 20

in which variables are displayed in both rows and columns

Question 21

descriptive statistic are useful for

Answer 21

summarizing data more than simply describe

Question 22

inferential statistic

Answer 22

which are based on the laws pf probability, provide a means for drawing conclusion about a population given data from a sample

Question 23

sample distribution of the mean

Answer 23

which is a theoretical distribution rather than actual distribution because in practice no one draws consecutive sampled from a population and plots their means

Question 24

statistic have deonstrated

Answer 24

means follow a normal distribution

mean of sampling distribution for an infinite # of sample means equals the population mean

Question 25

standard error of the mean (SEM)

Answer 25

problem is to determine the standard of deviation of he sampling distribution
increasing the sample size increased the accuracy
the more homogeneous the population the more accurate

Question 26

hypothesis testing

Answer 26

consist of two major techniques:
estimation procedure are used to estimate a single population characteristic, such as a mean value
statistical hypothesis provides objectives criteria for deciding whether research hypotheses should be accepted as true or rejected as false

Question 27

type 1 and type 2

Answer 27

type one error is rejecting the null hypothesis when it actually is true
type two accepted a false null hypothesis a false negative conclusion

Question 28

level of significance

Answer 28

is the term used to signify the probability of making a type one error (alpha)

Question 29

beta

Answer 29

probability of type two error estimated power analysis

Question 30

test of statistical significance

Answer 30

every test statistic there is theoretical sampling distribution, analogous t the sampling distribution of means

Question 31

hypothesis testing

Answer 31

uses the practical distribution to establish probable and improbable values for the test statistic

Question 32

parametric and non-parametric tests

Answer 32

have three attributes 1. they focus on population parameter
2. they require measurements on at least an interval scale
3. they involve other assumption such as assumption that the variables int he analysis are normally distributed n the population
>more powerful and preferable than nonparametric

Question 33

nonparametric test

Answer 33

do not estimate parameters and involve less restrictive assumption about the shape of he distribution of the critical variables

Question 34

hypothesis testing procedure

Answer 34

selecting an appropriate test statistic
selection the level of significance
computing a test statistic
comparing the test statistic to a tabled value

Question 35

degree of freedome

Answer 35

refers to the # of observation degree to vary about a parameter

Question 36

bivariate statistical tests.- t tests

Answer 36

the procedure used to test to statistical significance pf a difference between the means of two groups is the parametric test
the value of the t statistics is calculated based on group means, variability, and sample size
establishes an upper limit to what is probable;e of the null hypothesis is true

Question 37

ANOVA

Answer 37

analysis of variance is a parametric procedure uses to test mean group differences of three or more groups
variation between groups is contrasted with variation within groups to yield the statistic ca;;ed F ratio

Question 38

multiple comparison procedures

Answer 38

are needed to isolate the differences between group means that are responsible for rejecting the general ANOVA null hypothesis

Question 39

repeated measures of ANOVA

Answer 39

is sued when the means being compared are means at a diff points in time

Question 40

chi squared

Answer 40

is non-parametric procedure used to test hypotheses about the proportion of cases that fall into various categories, as in contingency table
by summing difference between the observed freq in each cell and the expected freq- the freq that would be expected if there were no relationship between the two variable

Question 41

multivariate

Answer 41

refer to analyses dealing with at threat three but usually more variable simultaneously

Question 42

multiple regression

Answer 42

which allows them to use more than one independent variable to explain predictor a dependent variable

Question 43

independent variable

Answer 43

are either interval level or ratio level variables or dichotomous nominal level variable such as male/female

Question 44

multiple correlation coefficent

Answer 44

R used to predict a dependent variable the resulting statistic varies from .00 to 1.00
> the overall relationship between the independent variable and the dependent variable and the dependent variable is likely to be real or the results of chance fluctuations
> second way of evaluating R is to determine whether the addition of new independent variables adds further predictive power
> the magnitude of R is also informative
when squared it can be interpreted as proportion of the variability in the depend variable accounted for or explained by the independent variables

Question 45

other multivariate techniques

Answer 45

discriminant function analysis is used to make predictions about membership in groups-that is, about a dependent variable measured on the normal scale

Question 46

logistic regression

Answer 46

analyzes the relationship between multiple independent variables and a nominal level dependent variable

Question 47

odds ratio

Answer 47

OR which is the factor by which the odds change for a unit change om the predictor

Question 48

factor analysis

Answer 48

is widely used by researchers who develop, refine, or validate complex instruments

Question 49

multivariate analysis of variance

Answer 49

MANOVA is the extension of ANOVA to more than one dependent variable

Question 50

causal modeling

Answer 50

involves the development and statistical testing of a hypothesized explanation of the causes of a phenomenon, usually with non experiential data

Question 51

pathanalysis

Answer 51

which is based on multiple regression, is a widely used approach tp casual modeling

Question 52

LISREL

Answer 52

linear structural relations analysis are highly complex stat tech whose utility relies on a sound underlying casual theory