Week 9 Quiz: Data Analysis Chap 16

Front 1

Descriptive statistics (list)

Back 1

describe & summarize, measure of central tendency: mean, median, & mode, measures of variability (range and SD), correlation techniques (scatter plot). NOTE: Not testing- just describing.

Front 2

Inferential statistics (list)

Back 2

predict and generalize, analyze, test hypotheses, & answer questions, used to draw conclusions that extend beyond the immediate data of the study. *Use the research questions.

Front 3

Inferential stats: parameter

Back 3

characteristic of a POPULATION

Front 4

Inferential stats: statistic

Back 4

characteristic of a SAMPLE

Front 5

NOTE hypothesis testing:

Back 5

percentage of chance, how strong associations are between variables, effect of intervention.

Front 6

Scientific hypothesis

Back 6

is what the researcher thinks will come true.

Front 7

Null hypothesis

Back 7

the hypothesis that actually can be tested

Front 8

Probability

Back 8

what the chances of obtaining the same reslut from a study that can be carried out many times under identical conditions. Repeat trials to test hypotheses.

Front 9

P-value

Back 9

likelihood that the researcher would observe this association in their sample if in truth no association existed in the population from which the sample came.

Front 10

Type I error

Back 10

researcher rejects a null hypothesis when it is actually true. More serious b/c differences are reported that actually do not exist. Patients care is more likely to be affected.

Front 11

Type II error

Back 11

occurs when a researcher accepts a null hypothesis that is actually false. Happens when sample is too small.

Front 12

level of significance: alpha level

Back 12

probability of making type I error, probability of rejection true null hypothesis. Minimum accepted 0.05.

Front 13

Normal Distribution

Back 13

symmetric, bell shaped curve; mean, median, mode are the same;

-68% fall within 1 SD,

-95% fall within 2 SD,

-99.7% fall within 3 SD

Front 14

Nonparametric

Back 14

less powerful & flexible, nominal & ordinal use, no estimation of population, distribution of data is skewed, does not have normal distribution, chi-square test use. bases on the estimation of population parameters. involve less restrictive assumptions

Front 15

Parametric

Back 15

more powerful & flexible, interval & ratio use, estimate of at least one population parameter, normally distributed, has normal distribution +with bell shaped, t test and anova use.

Front 16

t test

Back 16

tests whether 2 group means are DIFFERENT; used for continuous variables: interval & ratio; Parametric test; most commonly used in experimental & quasi-experimental.

Front 17

Degrees of freedom (df)

Back 17

freedom of a score's value to vary given what is known about the other scores and the sum scores; df=N-1. Reported with the t statistic & the probability value (p-value).

Front 18

Analysis of variance (ANOVA)

Back 18

test of difference, more than 2 groups or measurements taken more than once.

Front 19

Chi-Square (x2)

Back 19

test of difference, used for nominal level of data (categorical data), Nonparametric, determine whether the frequency in each category is different from what would be expected by chance,

Front 20

fisher's exact probability test

Back 20

type of chi-square test, used when <6 in each cell. small sample & have expected frequencies.

Front 21

chi-square & t tests

Back 21

both test in differences between groups, they give p-values, make inferences in population,

Front 22

NOTE if p value is <.05...

Back 22

reject the null hypothesis

Front 23

**descriptive statistics (definition)

Back 23

procedures that allow researchers to describe & summarize data.

Front 24

**inferential statistics (definition)

Back 24

procedures that allow researchers to estimate how reliable they can make prediction & generalize findings based on the data. Combine mathematical processes & logic & allow researchers to test hypotheses about a population using data obtained from probability samples.

Front 25

frequency distrubution

Back 25

number of times each event occurs is counted

Front 26

continuous variable

Back 26

represent a measurement that contains a range of values along a continuum and can include ordinal, interval, and ratio level of data (EX: HR).

Front 27

Measure of tendency

Back 27

used to describe the pattern of responses amonga sample; mean, median mode.

Front 28

mean

Back 28

average of all scores. Add all and divede by total number.

Front 29

median

Back 29

50% of scores are above and below. number in the middle.

Front 30

mode

Back 30

most frequent value in a distribution

Front 31

modality

Back 31

the number of modes contained in a distribution

Front 32

Measures of variablility

Back 32

range, percentile, sd

Front 33

sampling error

Back 33

tendency for statistics to fluctuate from one sample to another

Front 34

parametric stats characteristics (3)

Back 34

-involve estimation of at least one population parameter, -require measurement on at least an interval scale, -involve certain assumptions about the variables being studied.